A system and method for managing and distributing an electrical power system is provided. In one embodiment, the system and method comprise at least one powered device that receives electrical power from an electrical power system utilizing multiple energy sources. Structure and devices are provided within the system to command, regulate, monitor, and transmit power to a device or devices in an efficient, reliable manner based on resource availability, energy cost, and environmental factors. The system selects and manages the resources to optimize the energy output to the device(s) to achieve the specific requirements in resiliency, cost, and the environmental impact of the application.
1. A method comprising:
providing a portable microgrid system;
wherein the portable microgrid system comprises:
a battery operably connected to a first behind-the-meter energy source and a second behind-the-meter energy source; and a microgrid controller operably coupled to the battery; harvesting, by the portable microgrid system, energy from the first behind-the-meter energy source and the second behind-the-meter energy source;
wherein a first energy source controller is associated with the first behind-the-meter energy source; wherein a second energy source controller is associated with the second behind-the-meter energy source; and wherein the microgrid controller is operably connected to the first energy source controller and the second energy source controller; storing, in the battery of the portable microgrid system, at least a portion of the harvested energy; receiving, by the microgrid controller and via a network, a charge or load request associated with an electric charge or load request; receiving, by the microgrid controller, real-time information associated with the availability of energy from the first behind-the-meter energy source and/or the second behind-the-meter energy source; controlling the first energy source controller and/or the second energy source controller, using the microgrid controller and based on the real-time information and the charge or load request, to control the amount of energy being harvested; and supplying, by the portable microgrid system, at least a portion of the requested charge or load using the harvested energy. 2. The method of wherein the portable microgrid system is provided along a high-traffic path; and wherein the high-traffic path is an evacuation path. 3. The method of 4. The method of 5. The method of 6. A method of using a stranded energy asset during a grid failure, the method comprising:
connecting, via a behind-the-meter connection, the stranded energy asset and a portable microgrid system;
wherein the portable microgrid system comprises:
a first energy source; a battery operably connected to the stranded energy asset and the first energy source; and a microgrid controller operably coupled to the battery and the first energy source; harvesting, by the portable microgrid system, energy from the stranded energy asset via the behind-the-meter connection and energy from the first energy source; storing, in the battery of the portable microgrid system, at least a portion of the harvested energy; receiving, by the microgrid controller and via a network, a charge or load request; receiving, by the microgrid controller, real-time information associated with availability of energy from the stranded energy asset and the first energy source; controlling, using the microgrid controller and based on the real-time information and the charge or load request, the amount of energy being harvested from the stranded energy asset and the first energy source; and supplying, by the microgrid system connected to the stranded energy asset, at least a portion of the requested load or charge using the harvested energy. 7. The method of 8. The method of 9. The method of 10. The method of 11. The method of 12. A portable microgrid system comprising:
a battery configured to be operably connected to a first behind-the-meter energy source and a second behind-the-meter energy source; a microgrid controller operably coupled to the battery; and a non-transitory computer readable medium having stored thereon a plurality of instructions, wherein the instructions are executed with one or more processors so that the following steps are executed:
harvesting energy from the first behind-the-meter energy source and the second behind-the-meter energy source;
wherein a first energy source controller is associated with the first behind-the-meter energy source; wherein a second energy source controller is associated with the second behind-the-meter energy source; and wherein the microgrid controller is operably connected to the first energy source controller and the second energy source controller; storing, in the battery of the portable microgrid system, at least a portion of the harvested energy; receiving, by the microgrid controller and via a network, a charge or load request associated with an electric charge or load request; receiving, by the microgrid controller, real-time information associated with the availability of energy from the first behind-the-meter energy source and/or the second behind-the-meter energy source; controlling the first energy source controller and/or the second energy source controller, using the microgrid controller and based on the real-time information and the charge or load request, to control the amount of energy being harvested; and supplying, by the portable microgrid system, at least a portion of the requested charge or load using the harvested energy. 13. The portable microgrid system of wherein the portable microgrid system is provided along a high-traffic path; and wherein the high-traffic path is an evacuation path. 14. The portable microgrid system of 15. The portable microgrid system of 16. The portable microgrid system of 17. The portable microgrid system of 18. The portable microgrid system of 19. The portable microgrid system of wherein the second behind-the-meter energy source comprises a solar panel; and wherein the portable microgrid system further comprises the solar panel. 20. The portable microgrid system of wherein the second behind-the-meter energy source comprises an engine-driven generator; and wherein the portable microgrid system further comprises the engine-driven generator.
This application is a continuation of U.S. patent application Ser. No. 18/467,285, filed on Sep. 14, 2023, which claims priority to and the benefit of the filing date of U.S. Provisional Application No. 63/375,649, titled “Controller for an Electric Vehicle Charger” and filed on Sep. 14, 2022, the disclosure of which is incorporated herein in its entirety. The disclosure herein relates, in general, to a system and method for managing and distributing electrical power, specifically, using a controller for a portable microgrid system configured to receive power from a plurality of different energy resources. In recent years, there has been an increase in demand for electric vehicles (EVs) in order to reduce reliance on fossil fuels and decrease the overall carbon footprint. Many automobile manufacturers have announced plans to release a new line of EVs, become fully electric, or invest a certain amount of capital toward EVs. However, like all new technology, problems have arisen with its introduction. In particular, the adoption of EVs is challenged considerably by the lack of fast-charging resources in some areas. Further, utility power will inevitably be slow to expand access to the rapid EV charging facilities that are necessary for widespread adoption. Thus, one of the biggest challenges to the deployment of EV chargers is the absence of adequate grid infrastructure necessary to support the high intensity and variability of Level 3 charger loads. Further, as natural events like hurricanes and tornadoes become more intense, widespread damage to existing electrical infrastructure required to provide fast-charging, both for EVs and other electric devices, will become more prevalent. Thus, those evacuating, living in those areas affected by natural disasters, and/or visiting those areas will require something to replace or supplement the standard charging infrastructure in the immediate time before an event, during the event, and after the event. As such, EV and other large portable chargers will require unconventional means of charging both in the near and long term. A potential solution to the lack of adequate grid resources for reliable, fast-charging, is the use of off-grid or behind-the-meter energy resources. Off-grid and/or behind-the-meter charging will require a mix of energy resources, advanced control and data analytics to provide safe, effective, and economically optimal solutions. The mix of energy resources creates an unavoidable variability in cost and environmental impact that must be measured, controlled, communicated, and optimized. Additionally, advancing the adoption of off-grid or behind-the-meter charging must be attractive with risk mitigation for private investment. Further, messaging to the consumer is key to achieving a disruptive force in the adoption of new technology and methods. Here, some key questions for the consumer would be “Would you like to know what type of energy resource was used to charge your vehicle or device?” and “If you could choose an option that was more environmentally friendly, would you be willing to pay more for it?” For effective and rapid adoption, technology must align with social and political trends. Thus, a system and method for managing and controlling the variabilities inherent with off-grid and behind-the-meter charging methods can be effective in providing safe, reliable fast-charging to EVs and other devices in the absence of adequate grid resources, while also leading to a viral adoption by consumers and investors and maximizing the economic viability of the electrical power system delivering the charge. Generally, the system 100 receives and/or generates electricity via the number of resources and, depending on the amount of energy received and/or generated, creates an energy mix (e.g., 25% received via the power grid, 25% generated via engine-driven generators, and 50% generated via the solar array). Because each energy resource has different costs and environmental impacts, different energy mixes will result in different costs, environmental impacts, etc. In some embodiments, the system 100 controls the energy mix to meet a preferred cost, preferred environmental impact, etc. Cost and environmental impact are just examples of target parameters that the system 100 receives. Other target or preferred parameters may be a carbon intensity value, an energy efficiency value, or a resiliency value. Using the target parameter(s), the system 100 can alter the energy mix so that it meets the target parameter(s). In some examples, the target parameter(s) can be received from a user that wants to buy electricity to, for example, charge his or her electric vehicle via one of the charging stations 110. Regarding the structure 105, the structure 105 may be or include a moveable trailer, mobile shipping container, a portion of a vehicle such as a truck, etc. In other embodiments, however, the structure 105 may be a semi-permanent or permanent installation, such as when the structure 105 is connected “directly” or “behind-the-meter” to a permanently located energy resource such as a wind or solar farm. In that embodiment, the system 100 is a microgrid system 100. As used herein, “behind-the-meter”refers to receiving electricity from an energy resource prior to the electricity being stepped up for transmission to the grid. Regarding the charging stations 110, in some embodiments, the charging stations 110 are Level 3 EV charging stations. In one or more embodiments, the system 100 includes six charging stations, but the number of charging stations can be as low as one charging station and can also be greater than six. In some embodiments, the charging stations 110 are Level 3 DC Fast Chargers. In one or more embodiments, in operation, the portable microgrid system 100 has the charge capacity to charge 6 vehicles simultaneously, providing a 30 kWh charge, which is about 90 miles in range in approximately 20 minutes in each vehicle. In some embodiments, any Level 3 charging system can be integrated in the portable microgrid system 100. In some embodiments, another Level charging station can be used (e.g., Level 2 chargers). In some embodiments, the charging stations 110 are capable of supporting other three-phase and single-phase loads (e.g., for emergency preparedness needs). In one or more embodiments, the charging stations 110 can be scaled up or down for multiple charges to fit the need and/or application. The charging stations 110 may be powered by one or more energy resource. Generally, the charging stations 110 are configured to be connected a plurality of charging loads. In some embodiments, the charging loads may include an electric vehicle. In other embodiments, the charging loads may include banks of electric devices, such as mobile phones, battery packs, personal computers, or tablets. In further embodiments, the charging load may be a combination of both electric vehicles and banks of electric devices, but are not limited to either. For example, the charging loads may be associated with semi-permanent housing, temporary medical aid, temporary communication stations, etc. making it an extremely valuable and potentially lifesaving asset. Regarding the solar array 115, the solar array 115 illustrated in Regarding the power grid 120 or multi-MW generating device, in some embodiments the power grid 120 refers to a Wide Area Synchronous Grid (also known as an Interconnection), and is a regional scale or greater electric power grid that that operates at a synchronized frequency and is electrically tied together during normal system conditions. Generally, the power grid 120 includes: (i) generation stations that produce electrical power at large scales for delivery through the grid, (ii) a point of interconnection (“POI”) where the generation station equipment connects to the transmission equipment and where generation-side metering occurs, (iii) at least one step up transformer located between the generation station and the transmission equipment (in some instances at the POI) for increasing the generated power's voltage for transmission (iv) high voltage transmission lines that carry the grid power from the generation stations to demand centers, and (v) distribution networks that carry grid power to individual customers. Regarding the fuel storage 125, the fuel storage 125 stores fuel for the one or more engine-driven generators 205. In some embodiments, the fuel storage 125 includes a 2,000-gallon propane tank. In some embodiments, the fuel storage 125 is 46″ diameter, 55″×288″, and 3400 lbs. In one or more embodiments, the fuel storage 125 may hold 1585 gallons of LPG. In one or more embodiments, 3.3 gallons produces 30 kWh charge, as such 480 total galloons produces 30 kWh charges per tank and may produce 14,409 total kWh per tank. Regarding the controller 130, in some embodiments the controller 130 is a stand-alone controller that can be integrated into other charging or electrical systems than those described or contemplated herein. In one or more embodiments, the controller 130 includes software, such as predictive modeling software, and hardware, such as physical controllers that are capable of communicating and controlling inputs from the number of energy resources. In some embodiments, the controller 130 of the portable microgrid system 100 enables an effective path towards enabling energy transition away from carbon-based energy to renewable energy. In some embodiments, the portable microgrid system 100 and its controller 130 provide the necessary baseload power required for reliability and power-on-demand while integrating and effectively utilizing renewable energy resources. The system 100 and its controller 130 provide unique advantages and capabilities that solve difficult challenges to our energy infrastructure and can be an enabling technology for advancing the adoption of EVs. The portable microgrid system 100 (as one example of a microgrid) can provide EV and other charging in remote areas and serve as a rapid response, and deployable resource supporting the evacuation and management of disaster areas, as noted above. Regarding the communication device 135, the communication device 135 may be a computer system, including without limitation, personal computers, iPads, smartphones, and cell phones. While the communication device 135 is illustrated as separate from a vehicle in the Regarding the network 140, the network 140 includes the Internet, one or more local area networks, one or more wide area networks, one or more cellular networks, one or more wireless networks, one or more voice networks, one or more data networks, one or more communication systems, and/or any combination thereof. In some embodiments, the network 140 also includes WIFI, Bluetooth, and Long-Term Evolution (“LTE”) or other wireless broadband communication technology. Regarding the one or more engine-drive generators 205, in some embodiments the one or more engine-driven generators 205 are fuel powered and receive fuel from the fuel storage 125. In one embodiment, the one or more engine-driven generators 205 may be two 130 KW propane-fueled generators receiving propane from fuel storage 125. In other example embodiments, only one propane-fueled generator may be used. In one or more example embodiments, the portable microgrid system 100 uses two 120 KW generators that operate on natural gas, CNG, RNG, or LPG in a fuel switching configuration. Fuel switching capability allows the system 100 to detect and switch between the various gaseous fuels and operate normally without human intervention, depending on which fuel is available. Using two generators improves efficiency and adds redundancy and resiliency. The same generator configuration(s) could be deployed using gasoline, diesel, or JP8-fueled generators. Onboard power distribution and overload protection may provide the energy for up to six DC fast chargers, 400 amps of AC power, and dual six-station cell charging kiosks. Regarding the hybrid battery and inverter system 210, the battery and inverter system 210 may be used to distribute power to the charging stations 110. In some embodiments, the hybrid battery and inverter system 210 includes two separate components: a battery 210 In an example embodiment, the portable microgrid system 100 is a mobile microgrid that utilizes low-emissions, engine-driven generators, battery energy storage, and photovoltaic (PV) panels to power multiple level 3 DC chargers, three-phase and single-phase AC power, and low voltage DC power effectively and efficiently for charging of cell phones and other devices. The system 100 is self-contained, mobile, rapidly deployable, and can be safely operated as an unmanned resource. In another example embodiment, the portable microgrid system 100 operates independent of the power grid 120 and incorporates ultra-clean, gas-powered generators, battery energy storage, and renewable energy is an effective way. In some embodiments, the portable microgrid system 100 operates solely on clean, renewable energy sources. The portable microgrid system 100 can also provide invaluable, and potentially life-saving services in the event of a significant disaster event when existing charging resources are overwhelmed with heavy traffic flow during evacuations and/or if the grid supporting those charging resources is unavailable. Combining the hybrid power aspect with conventional internal combustion engines (e.g., one or more generators 205) provides multiple cost and capability advantages to both the routine charging of EV's as well as disaster planning organizations. Specifically, these benefits include: (1) providing level 3 EV charging in remote areas where grid connection is unavailable or unreliable; (2) providing level 3 EV charging in rural areas to increase adoption of electric vehicles; (3) avoiding long and costly interconnection queues and utility upgrades to expedite EV adoption, (4) better environmental stewardship relative to the transmission grid in many areas of the U.S.; and (5) providing level 3 EV charging as well as remote supply of power during the evacuation of large population areas. In some embodiments, the portable microgrid system 100 is connected to the power grid 120 via the grid interface device 120 In some embodiments, and as illustrated in the schematic diagram 300, the system controller 130 is in communication with and may give commands to the resource controllers and/or interface devices (e.g., the solar array controller 115 In an example embodiment, the system controller 130 controls multiple energy resources and system devices. The system controller 130 generally commands, regulates, monitors, and controls transmission of power to the charging stations 110 so that a vehicle or device can charge in an efficient and reliable manner based on resource availability, energy cost, and environmental factors. The system controller 130 selects and manages the resources via the device 120 In some embodiments, the system controller 130 provides automation, system operation, supervisory control, and data acquisition (SCADA). The system controller 130 may be configured to identify each power generation resource, such as the engine-driven generator(s) 205, the solar array 115, the grid power 120, and the like, as well as to manage the charging and discharging of the battery 210 In an example embodiment, the total power output and/or potential total power output/availability of the number of resources is reported to the system controller 130. For example, the total power produced by the solar array 115, the total power available from the power grid 120, and the total power available in the battery 210 The solar controller 115 In some embodiments, the system controller 130 calculates the carbon intensity per kWh produced by the solar array 115 and distributed by the solar controller 115 In some embodiments, the system controller 130 determines that the operating parameters of the solar array 115 must be adjusted. This decision may be based on a charge request from a user, a desired net profit per charge, available energy resources, or other internal or external factors. In the event that the system controller 130 determines that the operating parameters of the solar array 115 must be adjusted, the system controller 130 may control the solar controller 115 In some embodiments, the grid interface device 120 In some embodiments, the system controller 130 calculates the carbon intensity per kWh produced by the grid 120 using the current indicated by the current sensing device 500. In some embodiments, the system controller 130 calculates the cost per kWh using the information provided by the grid interface device 120 In some embodiments, the system controller 130 determines that the amount of power being received into the portable microgrid system 100 from the power grid 120 via the grid interface device 120 In some embodiments, the fuel status device 125 In some embodiments, the system controller 130 calculates the carbon intensity per kWh produced by the generator(s) 205 using the indicated fuel and current produced. In some embodiments, the system controller 130 calculates the cost per kWh using the fuel source indicated. In some embodiments, the system controller 130 calculates the percent of the stored and available energy produced by the generator(s) 205 and available to the connected charging stations 110 and ancillary loads. In some embodiments, the system controller 130 calculates the cost per kWh of the stored and available energy produced by the generator(s) 205 and available to the connected charging stations 110 and ancillary loads. In some embodiments, the system controller 130 determines that the operating parameters of the generator(s) 205 must be adjusted. This decision may be based on a charge request from a user, a desired net profit per charge, available energy resources, or other internal or external factors. In the event that the system controller 130 determines that the operating parameters of the generator(s) 205 must be adjusted, the system controller 130 may control the generator controller 205 In some embodiments, the system controller 130 calculates the carbon intensity per kWh that is received from the battery 210 In some embodiments, the system controller 130 determines that the operating parameters of the battery 210 Carbon intensity per charge can be calculated and compared to the prevailing grid 120 to show the clean advantage per charge. In some embodiments, this advantage may be communicated to the user or potential users of the portable microgrid system 100. In some embodiments, the system controller 130 considers the expected return on investment (ROI) per charge on each charging station 110. In some situations, the portable microgrid system 100 may be privately owned and can be configured to use a specific rate of return that aligns with the owner's commercial strategy. For example, cost comparison on sources of energy for a 30-KwH charge may be $1.80 for natural gas, $7.20 for LP (propane), $0.50 for solar, and $3.30 for utility. However, at a 40% Margin, the cost comparison on sources of energy for a 30-kWh charge may be $3.00 for natural gas, $12.00 for LP (propane), $0.83 for solar, and $5.50 for utility. In other situations, the portable microgrid system 100 may be municipal owned equipment. These municipal owned portable microgrid systems 100 may have lower cost and a lower ROI to reflect community incentives (e.g., for affordable and reliable charging resources for underserved communities). In some embodiments, the system controller 130 is communicatively linked via wireless or wired means to the internet (e.g., the network 140) or receives input into a human machine interface (HMI) (e.g., communication module 130 In some embodiments, real time pricing of grid power is reported to the system controller 130 (time of use and peak charges may influence this cost). In some embodiments, the “energy mix” already present in portable microgrid system 100 and available for charging is used along with a programmed ROI to provide current pricing to the consumer or user. The system controller 130 is configured to calculate the cost of the stored and/or produced energy from the various resources, for example, using generator fuel cost/kWh plus O&M, solar $0 fuel cost plus O&M, and the real-time grid pricing rate (grid charging can be avoided if the peak or time of use impact is prohibitively significant). Then a user adjusted ROI is added to the per charge cost to ensure commercial viability, and the cost of energy stored plus ROI threshold equals the consumer cost per charge. In some embodiments, the portable microgrid system 100 may present a user with options associated with the user's charge request, as illustrated in For example, in one or more embodiments, the system controller 130 can manipulate the energy resources to achieve the desired user preferences in three modes of operation: lowest carbon intensity, lowest cost, and a “resiliency mode” where the only consideration is providing charges regardless of cost or carbon intensity. If carbon intensity per charge is the priority, the system controller 130 would source energy first from renewable resources (e.g., the solar array 115), second from the low-emissions generator (e.g., the generator 205), and third from the grid 120. If the lowest cost per charge is the goal, then renewables first (e.g., the solar array 115), the grid 120 second (dependent on real-time pricing rates), and the generator(s) 205 last. If resiliency is the goal, renewables (e.g., the solar array 115) would be sourced first, followed by the generator(s) 205. This assumes the grid 120 is not available, thus switching the electrical power system into “resiliency mode” via the system controller 130. In some embodiments, the system controller 130 could harvest energy to achieve a specific, selected carbon intensity. In exchange, this may limit the number of charges available at a given time to allow renewable energy to charge the battery 210 The portable microgrid system 100 may also include or be configured to access a database 800 associated with the system controller 130. In some embodiments, the database 800 may be used to store historical data, including, but not limited to, historical pricing for energy from power grid 120, data related the use/efficiency of each of the energy resources of the portable microgrid system 100, and historical user selections for charge parameters. The system controller 130 may receive and use the historical user selections from the database 800 to identify trends in user selections for preferred charge parameters. These trends may be tied to a number of external factors (e.g., geographic areas, demographics, times of the year, etc.). The system controller 130 may then use the identified trends to predict future user preferred or target charge parameters. In some embodiments, the system controller 130 may then control and adjust the operating parameters of the various energy resource inputs of the portable microgrid system 100 to optimize for the predicted future user preferred charge parameters such that the portable microgrid system 100 has the proper energy resources available to fulfill future requests for charges with the preferred charge parameters. During step 905, the portable microgrid system 100 receives real time data associated with an energy resource via a controller associated with an energy resource input. In some embodiments, the controller associated with an energy resource input is one of the controllers 115 During the step 910, the portable microgrid system 100 identifies a first energy mix that is currently being produced and/or stored by the portable microgrid system 100. The first energy mix is the specific combination of energy resources used to produce the power distributed or stored by the portable microgrid system 100. For example, the first energy mix may be determined to be 20% solar power, 15% grid power, and 65% power from generators. The first energy mix may be identified by determining the amount of current and/or power being presently produced by each of the energy resource inputs of portable microgrid system 100, summing the current and/or power being produced by each of the energy resource inputs to determine a total current and/or power produced by portable microgrid system 100, and allocating percentages of the total current and/or power produced by each of the energy resource inputs. In some embodiments, the first energy mix may also be identified by determining the charge of battery 210 During the step 915, the portable microgrid system 100 receives a charge request from a user. In some embodiments, the charge request is received by a communication module 130 During step 920, the portable microgrid system 100 calculates a set of first charge parameters for the charge request. In one or more embodiments, the calculations are carried out by the system controller 130. The first set of charge parameters is calculated based on certain parameters of the charge request (e.g., the quantity of charge requested in kWh) and the first energy mix that is currently available for distribution in the portable microgrid system 100. In some embodiments, the first set of charge parameters includes an energy cost (usually per kWh), a carbon intensity value, an energy efficiency value, and a resiliency value. The energy efficiency value may be determined by the percentage of the total available energy resources that would be used to complete the charge compared to the amount of energy currently produced and/or stored in portable microgrid system 100 that would need to be generated (e.g., by generators) or received via the local power grid to fulfill the charge request. The resiliency value may be determined based on the reliance on grid resources for the charge, wherein less reliance on grid resources will mean a higher resiliency value for the charge. During the step 925, the portable microgrid system 100 identifies preferred charge parameter(s) for the charge request. In one or more embodiments, the system controller 130 identifies the preferred charge parameter(s) based on one or more of a number of factors, including user input, available resources, charging demand, a proposed ROI per charge, etc. In some embodiments, the preferred charge parameter(s) includes any one or more of a preferred energy cost, a preferred carbon intensity, a preferred energy efficiency value, and a preferred resiliency value. During the step 925 During the step 925 During the step 925 During the step 925 During the step 925 During the step 925 In some embodiments, the user may select to optimize multiple charge parameters (e.g., optimize cost and carbon intensity). In such cases, the method may further comprise the system controller 130 determining the best combination of optimized charge parameters possible based on the available energy resources. This may mean that the individual optimized parameters are no longer the most optimized that they can be. For example, if a system were to solely optimize for cost it may be able to deliver a charge at $0.02 per kWh and if the same system was solely optimized for carbon intensity it may be able to deliver a charge at 10 g of CO2per kWh. However, if the same system were optimized for both cost and carbon intensity concurrently it may only be able to deliver a charge at $0.04 per kWh and 20 g of CO2per kWh. The options presented to the user and/or selectable by the user are not limited to optimized energy mixes (e.g., minimum cost, minim carbon intensity). Referring back to During the step 935, the portable microgrid system 100 controls the amount of electrical power being generated by or received via each energy resource to achieve the second energy mix. In some embodiments, the system controller 130 controls the generation and/or receipt of power from each energy resource via communication with the resource controller associated with each respective energy resource. In some embodiments, the system controller 130 commands the resource controllers associated with the energy resource inputs to adjust certain operating parameters affecting the generation of electrical power (e.g., by the generator(s) 205) or the amount of electrical power that may be received into the system from the energy resource input (e.g., by the battery 210 In some embodiments, once the portable microgrid system 100 is producing and/or able to supply power using the preferred second energy mix, the portable microgrid system 100 will supply power to fulfill the charge request through the charging stations 110 or another auxiliary power output. The portable microgrid system 100 and related methods described herein result in multiple improvements to one or more of the technical fields of: mobile charging, microgrids, EV Controllers, EV charging, and modeling. The portable microgrid system 100 and related methods provide many advantages in the technological fields of EV and mobile charging through: (1) improved modeling capabilities, (2) providing an alternate to grid connected EV charging, (3) improving rural EV charging, (4) reducing delays experienced in interconnection queues, (5) improving environmental attributes relative to the utility grid, and (6) impacting emergency planning, each of which will be discussed more below. First, the use with and/or integration of the Moser DISASTERTECH® platform, or similar platforms, for modeling associated with the portable microgrid system 100 will enable unmatched capabilities to predict natural events and model scenarios involving the needs, and ultimately, the optimal positioning of power generation and other critical services. Second, the North American electric grid is becoming less stable and more unreliable. The electric grid is becoming increasingly strained by the abundance of intermittent resources. Interconnection, even when available, takes too long and is costly. The ability to provide charging for EV's and other devices without dependence on the suitability of the local transmission grid is one advantage of the portable microgrid system 100. Third, manufacturers of farm equipment are quickly moving to implement EV technologies into their products. Unfortunately, the investment in, and construction of, rural charging infrastructure is lagging far behind. The portable microgrid system 100 proposes to demonstrate the utility of mobile, Level 3 charging in rural areas with the potential to be a shared asset among members of the farming community. Besides providing Level 3 charging, the portable microgrid system 100, in some embodiments, also has the capability of charging 6-10 vehicles per hour depending on the type of vehicle. Fourth, the proliferation of wind and solar generation projects has created unprecedented costs and delays in the traditional utility interconnection study and approval process. In fact, there was an estimated 1,000 GW of generation and an estimated 427 GW of storage capacity as of the end of 2021; over 930 GW of zero-carbon generating capacity is currently seeking transmission access; solar and battery storage is nearly 85% of new capacity entering the queues in 2021; and much of this proposed capacity will not ultimately be built—only 23% of the projects seeking connection from 2000 to 2016 have subsequently been built and this number is declining. Proposed fossil fuel generation is on the decline. Interconnection wait times are on the rise: the typical duration from connection request to commercial operation increased from ˜2.1 years for projects built in 2000-2010 to ˜3.7 years for those built in 2011-2021. The portable microgrid system 100 does not require interconnection to the transmission grid. Fifth, much of the energy produced and distributed over the U.S. transmission grid is still produced by carbon-based assets. In some embodiments, when fueled with RNG or propane, along with emissions control system, the portable microgrid system 100 can provide charging to EV's and other devices with lower emissions than the comparable energy supplied from the grid. For example, emissions from a car with a typical internal combustion engine produces 411 grams of CO2per mile, which equates to 6.8 tons of CO2per year (at 15,000 miles/year); whereas, in some embodiments, a typical portable microgrid system 100 may produce around 308 grams of CO2/kWh or 107 grams of CO2per mile (at 3 miles/kWh). Therefore, in some embodiments, the typical portable microgrid system 100 is able to save 248 grams of CO2per mile, which equates to 3,720,000 grams or 4.1 tons of CO2per year, which is about the same as 170 mature trees can absorb in a year. Charging with the portable microgrid system 100 is more environmentally friendly (cleaner) than using just an internal combustion engine. In some embodiments, the portable microgrid system 100 produces an average of 0.68 pounds/kWh, 0.23 pounds/kWh less than natural gas power plants, and 1.53 pounds/kWh less than coal-fired power plants. A natural gas-fired power plant produces 0.91 pounds of CO2/kWh, 3 EV miles per kWh, and 0.303 pounds of CO2per EV mile, which is 4,550 pounds of CO2per year. Whereas, in some embodiments, the portable microgrid system 100 produces 0.68 pounds of CO2/kWh, 3 EV miles per kWh, and 0.226 pounds of CO2per EV mile, which equates to 3,400 pounds of CO2per year. Thus, in some embodiments, the portable microgrid system 100 outputs 1,150 less pounds of CO2per year than the natural gas-fired power plant. In some embodiments, the portable microgrid system 100 also meets CA AQMD requirements. In one or more embodiments, the portable microgrid system 100 is fueled by natural gas or propane and has the ability to also integrate renewables. Sixth, in the event of natural disasters requiring the evacuation of large populations, the significant increase in the number of EV's utilizing the primary high-traffic evacuation routes will undoubtedly overwhelm the current charging infrastructure. It is possible that the grid will be unavailable and incapable of providing sufficient charging capability during such an evacuation. The portable microgrid system 100 will provide Level 3 charging quickly, reliably, and with the ability to relocate to accommodate the uncertainties that natural disasters create. In some embodiments, the portable microgrid system 100 is mobile such as carried by a truck, semi, or the like. In other embodiments, the portable microgrid system 100 is stationary. In some embodiments, the portable microgrid system 100 is serviced and maintained by one company. In many cases, these evacuation routes are near grid-tied solar power plants that are reduced to a stranded asset during a catastrophic grid failure. In some embodiments, the portable microgrid system 100 harvests this energy during the outage event with the appropriate interconnection and switchgear design. In other embodiments, the portable microgrid system 100 harvests this energy behind-the-meter. In some embodiments, the portable microgrid system 100 also provides energy for cellular telephones as well as critical infrastructure facilities such as aid stations and food storage facilities in addition to EV charging. The portable microgrid system 100 is extremely flexible, and its capabilities will enable emergency charging services for vehicles as well as other battery-operated devices along evacuation paths that may remain fluid as the crisis evolves. By using multiple energy resources, the ability to have direct control over the cost of energy (in some cases for each individual charge) by manipulating and commanding the connected resources, and by sensing and gathering actual data from the resources rather than assuming grid conditions are all additional advantages of the portable microgrid system 100 and related methods. Additionally, the system controller 130 provides further advantages as it calculates pricing per charge using ROI thresholds provided by the user, ensures fair pricing and protecting commercial viability by accounting for variable costs of several different sources of energy used to create the energy available for each charge, and provides a means to inform consumers on not only the price of the available charging resources, but also the environmental impact. In some embodiments, the system controller 130 makes “decisions” based on resiliency, pricing, and carbon intensity, and controls the energy resources to precisely measure the energy mix composing the charge of the battery and the charge of the actual EV. For example, and when the portable microgrid system 100 is connected to the utility grid, the system controller 130 may identify a strike price for energy received via the utility grid and change the source of energy based on the price being above or below the strike price. Additionally, the portable microgrid system 100 and related methods in some embodiments eliminates charging via the utility grid during peak demand periods to eliminate peak charges. The system 100 and method 900 identify a new, preferred energy mix to achieve the set of preferred parameters and use the system controller 130 to command resource controllers associated with the different energy resources to vary the amount of electrical power generated, received, and/or used from that energy resource to create the preferred energy mix. In some embodiments, the set of preferred parameters is determined by the user who makes the charge request. In such instances, the user may have control over the energy mix that is used to complete their individual charge request and may prioritize the parameters that are most important to the user. A big challenge inhibiting greater adoption of EVs is the availability and reliability of the charging infrastructure. This is particularly true in the case of rural and underserved communities where the grid infrastructure is unavailable or insufficient to afford the community the charging infrastructure that larger metropolitan areas take for granted. The portable microgrid system 100 will benefit these and other communities by providing an alternative to grid-connected chargers that is more efficient, more reliable, and cleaner than the grid alternative. An additional benefit to stakeholders and the communities involved is the ability, in one or more embodiments of the present disclosure, to relocate the portable microgrid system 100. This may be very important during early adoption of the technology when the EV traffic patterns and other charging needs are not yet known. The portable microgrid system 100 may also allow for seasonal or event-driven traffic variability and provides a means to help determine the optimal location of permanent charging facilities during the evaluation process. A permanent location may include a national park, a landmark, remote travel plazas, truck stops, areas with grid congestion or reliability issues, or the like. The portable microgrid system 100 may be brought to a location for a music festival, entertainment event, conferences, or as mentioned for disaster relief. These same communities will also benefit from the energy security provided by the portable microgrid system 100 in the event of a natural disaster. With the proper advance warning and planning, the portable microgrid system 100 could be deployed to areas impacted, or expected to be impacted, by intense weather events or other disasters and follow the flow of the evacuation traffic during the event. Further, conventional or previous systems had many problems that are solved by the portable microgrid system 100 and related methods described herein. First, conventional EV chargers are permanent and are not mobile. The portable microgrid system 100 may be configured to be both movable (mobile) and permanent. Second, conventional EV chargers are only capable of using one energy resource or ineffectually using multiple resources. The portable microgrid system 100 is configured to efficiently and effectively utilize multiple energy resources, both individually and/or simultaneously. Third, the previous systems do not have direct control over the cost of energy through the ability to manipulate each of the connected energy resources. The portable microgrid system 100 is configured so that the energy produced or received from each resource may be adjusted, in some cases in real time. Fourth, the conventional models assume grid conditions rather than gathering actual data. The portable microgrid system 100 is configured to constantly monitor gird conditions and various operating parameters of the other energy resource inputs into the system 100. In an example embodiment, as illustrated in In several example embodiments, one or more of the components of the systems described above and/or illustrated in In several example embodiments, one or more of the applications, systems, and application programs described above and/or illustrated in In several example embodiments, a computer system typically includes at least hardware capable of executing machine readable instructions, as well as the software for executing acts (typically machine-readable instructions) that produce a desired result. In several example embodiments, a computer system may include hybrids of hardware and software, as well as computer sub-systems. In several example embodiments, hardware generally includes at least processor-capable platforms, such as client-machines (also known as personal computers or servers), and hand-held processing devices (such as smart phones, tablet computers, personal digital assistants (PDAs), or personal computing devices (PCDs), for example). In several example embodiments, hardware may include any physical device that is capable of storing machine-readable instructions, such as memory or other data storage devices. In several example embodiments, other forms of hardware include hardware sub-systems, including transfer devices such as modems, modem cards, ports, and port cards, for example. In several example embodiments, software includes any machine code stored in any memory medium, such as RAM or ROM, and machine code stored on other devices (such as floppy disks, flash memory, or a CD ROM, for example). In several example embodiments, software may include source or object code. In several example embodiments, software encompasses any set of instructions capable of being executed on a node such as, for example, on a client machine or server. In several example embodiments, combinations of software and hardware could also be used for providing enhanced functionality and performance for certain embodiments of the present disclosure. In an example embodiment, software functions may be directly manufactured into a silicon chip. Accordingly, it should be understood that combinations of hardware and software are also included within the definition of a computer system and are thus envisioned by the present disclosure as possible equivalent structures and equivalent methods. In several example embodiments, computer readable mediums include, for example, passive data storage, such as a random-access memory (RAM) as well as semi-permanent data storage such as a compact disk read only memory (CD-ROM). One or more example embodiments of the present disclosure may be embodied in the RAM of a computer to transform a standard computer into a new specific computing machine. In several example embodiments, data structures are defined organizations of data that may enable an embodiment of the present disclosure. In an example embodiment, a data structure may provide an organization of data, or an organization of executable code. In several example embodiments, any networks and/or one or more portions thereof may be designed to work on any specific architecture. In an example embodiment, one or more portions of any networks may be executed on a single computer, local area networks, client-server networks, wide area networks, internets, hand-held and other portable and wireless devices and networks. In several example embodiments, a database may be any standard or proprietary database software. In several example embodiments, the database may have fields, records, data, and other database elements that may be associated through database specific software. In several example embodiments, data may be mapped. In several example embodiments, mapping is the process of associating one data entry with another data entry. In an example embodiment, the data contained in the location of a character file can be mapped to a field in a second table. In several example embodiments, the physical location of the database is not limiting, and the database may be distributed. In an example embodiment, the database may exist remotely from the server, and run on a separate platform. In an example embodiment, the database may be accessible across the Internet. In several example embodiments, more than one database may be implemented. In several example embodiments, a plurality of instructions stored on a non-transitory computer readable medium may be executed by one or more processors to cause the one or more processors to carry out or implement in whole or in part the above-described operation of each of the above-described example embodiments of the system, the method, and/or any combination thereof. In several example embodiments, such a processor may include one or more of the microprocessor 1100 In several example embodiments, the elements and teachings of the various illustrative example embodiments may be combined in whole or in part in some or all of the illustrative example embodiments. In addition, one or more of the elements and teachings of the various illustrative example embodiments may be omitted, at least in part, and/or combined, at least in part, with one or more of the other elements and teachings of the various illustrative embodiments. The present disclosure introduced a method for controlling, a plurality of energy resources of an electrical power system to create a preferred energy mix, comprising: calculating a first energy mix using a system controller, comprising: receiving, by the system controller, real time data via at least one resource controller associated with an energy resource, wherein the energy resource is one of the plurality of energy resource, wherein the data received by the system controller comprises an amount of electrical power being generated by or received via the energy resource, wherein each energy resource sources energy from a different type of energy resource, wherein the different types of energy resources and the amount of electrical power being generated by each energy resource associated with the different types of energy resources make up a first energy mix of the electrical power system; and identifying, based on the real time data received, the first energy mix of the electrical power system; calculating, based on the first energy mix of the electrical power system, a set of first charge parameters comprising: a first energy cost, a first carbon intensity value, a first energy efficiency value, and a first resiliency value; identifying preferred charge parameter(s) for a charge request, wherein the preferred charge parameter(s) comprises at least one of: a preferred energy cost associated with the charge request, a preferred carbon intensity value associated with the charge request, a preferred energy efficiency value associated with the charge request, or a preferred resiliency value associated with the charge request; identifying, using the system controller, a second energy mix that comprises an amount of electrical power needed from each energy resource input to achieve the preferred charge parameter(s); wherein the second energy mix is the preferred energy mix; and controlling, by the system controller, the amount of electrical power being generated by or received via the energy resource associated with each resource controller to achieve the preferred energy mix. In one embodiment, the charge request is received from a user, wherein the charge request is associated with a charge of an electric vehicle; and wherein identifying the preferred charge parameter(s) for the charge request comprises: identifying a set of optimized charge parameters for the charge request comprising: an optimized energy cost, and an optimized carbon intensity value; displaying, for selection, one or more of the optimized charge parameter(s) to the user; and receiving a selection of one of the optimized charge parameters, wherein the selected optimized charge parameters is the preferred charge parameter(s). In one embodiment, the method also includes storing the selected optimized charge parameter; identifying, based on the stored selected optimized charge parameter, a trend in user selections; predicting future preferred charge parameter(s) based on the identified trends; and optimizing placement of the electrical power system and the types of energy resources available to fulfill charge requests with the predicted future preferred charge parameter(s). In one embodiment, identifying the set of preferred charge parameter(s) for the charge request comprises: receiving a preferred net profit per charge; determining a total price to charge for completing the charge request; and calculating the preferred energy cost based on the preferred net profit per charge and the total price to charge for completing the charge request. In one embodiment, different types of energy resources comprise one or more of: solar power, the electric power grid, battery power, an engine driven generator, or a hybrid generator. In one embodiment, controlling the amount of electrical power being generated by or received via the energy resource sourcing energy from solar power comprises: monitoring, by the system controller, an amount of current being produced by a solar array and an amount of current being presently received from the solar array; determining, by the system controller, a preferred current to be received from the solar array by the electrical power system to create at least a portion of the second energy mix; and adjusting, by the resource controller associated with the solar array and based on a set of one or more commands from the system controller, the amount of current being presently received from the solar array such that the amount of current being presently received from the solar array is the same as preferred current to be received from the solar array. In one embodiment, controlling the amount of electrical power being generated by or received via the energy resource sourcing energy from the electric power grid comprises: monitoring, by the system controller, a set of present parameters associated with the electric power grid comprising (i) a present status of the electric power grid, (ii) a real time price of receiving electricity from the electric power grid, and (iii) an amount of current being presently received from the electric power grid; determining, by the system controller and based on the second energy mix, a set of preferred operating parameters associated with the electric power grid comprising a preferred amount of current to be received from the electric power grid; and adjusting, by the resource controller associated with the electric power grid and based on a set of one or more commands from the system controller, the amount of current being presently received from the electric power grid such that the amount of current being presently received from the electric power grid is the same as the preferred amount of current to be received from the electric power grid. In one embodiment, controlling the amount of electrical power being generated by or received via the energy resource sourcing energy from a generator comprises: monitoring, by the system controller, a set of present operating parameters of the generator comprising (i) a type of fuel or fuel mix being used to power the generator, and (ii) a current being produced by the generator; determining, by the system controller, a set of preferred operating parameters for the generator to generate at least a portion of the second energy mix; and adjusting, by the resource controller associated with the generator and based on a set of one or more commands from the system controller, the operation of the generator such that the present operating parameters are the same as the preferred operating parameters. In one embodiment, controlling the amount of electrical power being generated by or received via the energy resource sourcing energy from battery power: monitoring, by the system controller, a set of present operating parameters of a battery energy storage device comprising (i) an amount of energy available in the battery energy storage device, (ii) the types of energy resources being used to charge the battery energy storage device, and (iii) a rate of charge or discharge of the battery; determining, by the system controller, a set of preferred operating parameters for the battery energy storage device to provide at least a portion of the second energy mix; and adjusting, by the resource controller associated with the battery energy storage device and based on a set of one or more commands from the system controller, the operation of the battery energy storage device such that the present operating parameters are the same as the preferred operating parameters. In one embodiment, each of the different types of energy resources are off-grid or behind-the-meter. In one embodiment, the method also includes receiving a carbon intensity value for a local electric power grid; comparing the preferred carbon intensity value to the carbon intensity value for the local grid; and displaying the difference in the preferred carbon intensity value and the carbon intensity value of the local grid. The present disclosure also introduces a system configured to control a plurality of energy resources of an electrical power system to create a preferred energy mix, the system comprising a non-transitory computer readable medium having stored thereon a plurality of instructions, wherein the instructions are executed with one or more processors so that the following steps are executed: calculating a first energy mix using a system controller, comprising: receiving, by the system controller, real time data via at least one resource controller associated with an energy resource, wherein the energy resource is one of the plurality of energy resources, wherein the data received by the system controller comprises an amount of electrical power being generated by or received via the energy resource, wherein each energy resource sources energy from a different type of energy resource, wherein the different types of energy resources and the amount of electrical power being generated by each energy resource associated with the different types of energy resources make up a first energy mix of the electrical power system; and identifying, based on the real time data received, the first energy mix of the electrical power system; calculating, based on the first energy mix of the electrical power system, a set of first charge parameters comprising: a first energy cost, a first carbon intensity value, a first energy efficiency value, and a first resiliency value; identifying a set of preferred charge parameter(s) for a charge request, wherein the set of preferred charge parameter(s) comprises at least one of: a preferred energy cost associated with the charge request, a preferred carbon intensity value associated with the charge request, a preferred energy efficiency value associated with the charge request, or a preferred resiliency value associated with the charge request; identifying, using the system controller, a second energy mix that comprises an amount of electrical power needed from each energy resource input to achieve the set of preferred charge parameter(s); wherein the second energy mix is the preferred energy mix; and controlling, by the system controller, the amount of electrical power being generated by or received via the energy resource input associated with each resource controller to achieve the second energy mix. In one embodiment, the charge request is received from a user, wherein the charge request is associated with a charge of an electric vehicle; and wherein identifying the preferred charge parameter(s) for the charge request comprises: identifying a set of optimized charge parameters for the charge request comprising: an optimized energy cost, and an optimized carbon intensity value; displaying, for selection, one or more of the optimized charge parameter(s) to the user; and receiving a selection of one of the optimized charge parameters, wherein the selected optimized charge parameters is the preferred charge parameter(s). In one embodiment, the instructions are executed with the one or more processors so that the following step is also executed: storing the selected optimized charge parameter; identifying, based on the stored selected optimized charge parameter, a trend in user selections; and predicting future preferred charge parameter(s) based on the identified trends. In one embodiment, identifying the set of preferred charge parameter(s) for the charge request comprises: receiving a preferred net profit per charge; determining a total price to charge for completing the charge request; and calculating the preferred energy cost based on the preferred net profit per charge and the total price to charge for completing the charge request. In one embodiment, different types of energy resources comprise one or more of: solar power, the electric power grid, battery power, an engine driven generator, or a hybrid generator. In one embodiment, controlling the amount of electrical power being generated by or received via the energy resource sourcing energy from solar power comprises: monitoring, by the system controller, an amount of current being produced by a solar array and an amount of current being presently received from the solar array; determining, by the system controller, a preferred current to be received from the solar array by the electrical power system to create at least a portion of the second energy mix; and adjusting, by the resource controller associated with the solar array and based on a set of one or more commands from the system controller, the amount of current being presently received from the solar array such that the amount of current being presently received from the solar array is the same as preferred current to be received from the solar array. In one embodiment, controlling the amount of electrical power being generated by or received via the energy resource sourcing energy from the electric power grid comprises: monitoring, by the system controller, a set of present parameters associated with the electric power grid comprising (i) a present status of the electric power grid, (ii) a real time price of receiving electricity from the electric power grid, and (iii) an amount of current being presently received from the electric power grid; determining, by the system controller and based on the second energy mix, a set of preferred operating parameters associated with the electric power grid comprising a preferred amount of current to be received from the electric power grid; and adjusting, by the resource controller associated with the electric power grid and based on a set of one or more commands from the system controller, the amount of current being presently received from the electric power grid such that the amount of current being presently received from the electric power grid is the same as the preferred amount of current to be received from the electric power grid. In one embodiment, controlling the amount of electrical power being generated by or received via the energy resource sourcing energy from a generator comprises: monitoring, by the system controller, a set of present operating parameters of the generator comprising (i) a type of fuel or fuel mix being used to power the generator, and (ii) a current being produced by the generator; determining, by the system controller, a set of preferred operating parameters for the generator to generate at least a portion of the second energy mix; and adjusting, by the resource controller associated with the generator and based on a set of one or more commands from the system controller, the operation of the generator such that the present operating parameters are the same as the preferred operating parameters. In one embodiment, controlling the amount of electrical power being generated by or received via the energy resource sourcing energy from battery power: monitoring, by the system controller, a set of present operating parameters of a battery energy storage device comprising (i) an amount of energy available in the battery energy storage device, (ii) the types of energy resources being used to charge the battery energy storage device, and (iii) a rate of charge or discharge of the battery; determining, by the system controller, a set of preferred operating parameters for the battery energy storage device to provide at least a portion of the second energy mix; and adjusting, by the resource controller associated with the battery energy storage device and based on a set of one or more commands from the system controller, the operation of the battery energy storage device such that the present operating parameters are the same as the preferred operating parameters. In one embodiment, each of the different types of energy resources are off-grid or behind-the-meter. In one embodiment, the instructions are executed with the one or more processors so that the following step is also executed: receiving a carbon intensity value for a local electric power grid; comparing the preferred carbon intensity value to the carbon intensity value for the local grid; and displaying the difference in the preferred carbon intensity value and the carbon intensity value of the local grid. Any spatial references such as, for example, “upper,” “lower,” “above,” “below,” “between,” “bottom,” “vertical,” “horizontal,” “angular,” “upwards,” “downwards,” “side-to-side,” “left-to-right,” “right-to-left,” “top-to-bottom,” “bottom-to-top,” “top,” “bottom,” “bottom-up,” “top-down,” etc., are for the purpose of illustration only and do not limit the specific orientation or location of the structure described above. In several example embodiments, while different steps, processes, and procedures are described as appearing as distinct acts, one or more of the steps, one or more of the processes, and/or one or more of the procedures may also be performed in different orders, simultaneously, and/or sequentially. In several example embodiments, the steps, processes and/or procedures may be merged into one or more steps, processes, and/or procedures. In several example embodiments, one or more of the operational steps in each embodiment may be omitted. Moreover, in some instances, some features of the present disclosure may be employed without a corresponding use of the other features. Moreover, one or more of the above-described embodiments and/or variations may be combined in whole or in part with any one or more of the other above-described embodiments and/or variations and this is within the contemplated scope of disclosure herein, unless stated otherwise. The phrase “at least one of A and B” should be understood to mean “A, B, or both A and B.” The phrases “one or more of the following: A, B, and C” and “one or more of A, B, and C” should each be understood to mean “A, B, or C; A and B, B and C, or A and C; or all three of A, B, and C.” The foregoing outlines features of several implementations so that a person of ordinary skill in the art may better understand the aspects of the present disclosure. Such features may be replaced by any one of numerous equivalent alternatives, only some of which are disclosed herein. One of ordinary skill in the art should appreciate that they may readily use the present disclosure as a basis for designing or modifying other processes and structures for carrying out the same purposes and/or achieving the same advantages of the implementations introduced herein. One of ordinary skill in the art should also realize that such equivalent constructions do not depart from the spirit and scope of the present disclosure, and that they may make various changes, substitutions and alterations herein without departing from the spirit and scope of the present disclosure. The Abstract at the end of this disclosure is provided to comply with 37 C.F.R. § 1.72(b) to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Methods within the scope of the present disclosure may be local or remote in nature. These methods, and any controllers discussed herein, may be achieved by one or more intelligent adaptive controllers, programmable logic controllers, artificial neural networks, and/or other adaptive and/or “learning” controllers or processing apparatus. For example, such methods may be deployed or performed via PLC, PAC, PC, one or more servers, desktops, handhelds, and/or any other form or type of computing device with appropriate capability. Although several example embodiments have been described in detail above, the embodiments described are example only and are not limiting, and those of ordinary skill in the art will readily appreciate that many other modifications, changes and/or substitutions are possible in the example embodiments without materially departing from the novel teachings and advantages of the present disclosure. Accordingly, all such modifications, changes and/or substitutions are intended to be included within the scope of this disclosure as defined in the following claims. In the claims, means-plus-function clauses are intended to cover the structures described herein as performing the recited function and not only structural equivalents, but also equivalent structures. Moreover, it is the express intention of the applicant not to invoke 35 U.S.C. § 112(f) for any limitations of any of the claims herein, except for those in which the claim expressly uses the word “means” together with an associated function.RELATED APPLICATIONS
FIELD OF DISCLOSURE
BACKGROUND
BRIEF DESCRIPTION OF THE DRAWINGS
DETAILED DESCRIPTION
Example Components of the Portable Microgrid System 100
Example Schematic Diagrams Associated with the Portable Microgrid System
Example Methods of Use
Example Improvements Associated with the Portable Microgrid System