A coordinated control system and control method of a megawatt-level optical storage and charging micro-grid

Abstract

This invention discloses a coordinated control system and method for a megawatt-level photovoltaic-storage-charging microgrid, belonging to the field of integrated energy management and microgrid control technology. The system includes a grid interface, a photovoltaic power generation array, a large-scale energy storage system, a charging pile cluster, and a microgrid management system. The method constructs a five-layer efficient control logic system comprising a prediction layer, an energy control layer, a load control layer, an operation layer, and a value-added layer. Its core lies in using the power balance equation as a basis to dynamically adjust the charging and discharging power of the energy storage system, thereby maximizing the absorption of photovoltaic output, accurately managing grid demand, and adaptively adjusting the charging load. This invention introduces the concept of a photovoltaic discharge threshold that matches the physical start-up characteristics of photovoltaics. Based on the dynamic control logic of charging photovoltaics with power ramping, it achieves the operational goal of photovoltaic power utilization exceeding 70%, significantly reducing charging costs and improving the overall economy and reliability of the system.

Description

Technical Field

[0001] This invention relates to the field of energy internet and microgrid control technology, specifically to a collaborative control system and optimized operation method for an integrated microgrid combining photovoltaic, energy storage, and charging piles at the megawatt (MW) scale. Background Technology

[0002] In 2024, China's newly installed photovoltaic power capacity reached 277.57 GW. In 2025, due to the limitations of grid absorption capacity and the impact of policies such as the Management Measures for Distributed Photovoltaic Power Generation and the Market-oriented Reform of New Energy Feed-in Tariffs, the era of full grid connection for distributed photovoltaic power generation has basically come to an end. The profitability of self-consumption projects with surplus electricity fed into the grid is rapidly decreasing and difficult to predict due to irregular price reductions and restrictions on grid connection ratios.

[0003] Meanwhile, affected by the large amount of electricity generated during peak periods of photovoltaic and wind power generation, most provinces have adjusted their original peak and off-peak electricity price periods. Many energy storage projects that could implement 2 charging and 2 discharging have had to be changed to 1 charging and 1 discharging, and some even have no charging and discharging conditions due to flat electricity prices throughout the day. This has also reduced the yield of previously profitable household-side energy storage projects and made it difficult to predict their returns.

[0004] The construction and operation of conventional electric vehicle charging stations currently face many challenges, such as low entry barriers, fierce competition, urban power supply shortages, and unstable investment returns.

[0005] It is evident that user-side energy projects with single operational functions face various risks. Planning for energy sources, grids, loads, and storage on the user side, exploring the potential of individual single-function projects, and promoting the construction of integrated smart energy projects are the inevitable paths for the future development of energy projects.

[0006] The market penetration of electric new energy vehicles in China has already exceeded 50%. Due to the capacity limitations of transformers in residential areas, the charging demand in most regions has overflowed from residential communities to public charging stations. This has created a new scenario for the large-scale integration of photovoltaic, energy storage, and charging technologies. Photovoltaics provide low-cost electricity, while energy storage solves the problem of the spatiotemporal transfer of unstable photovoltaic power output. The integration of photovoltaic, energy storage, and charging technologies will become an inevitable trend.

[0007] Traditional photovoltaic-storage-charging projects typically involve building photovoltaic carports above parking spaces at charging stations, with photovoltaic capacity ranging from tens to hundreds of kilowatts; the energy storage equipment typically generates only tens to hundreds of kilowatt-hours of electricity.

[0008] Existing photovoltaic carports are generally self-generated and self-consumed with surplus electricity fed to the grid. Photovoltaic electricity that cannot be consumed in time is sent back to the grid through the lines and cannot be dynamically stored in energy storage devices. The revenue from the surplus electricity fed to the grid is only obtained according to the local desulfurized coal benchmark on-grid electricity price.

[0009] Energy storage devices generally operate on a peak-valley arbitrage model. Since charging vehicles tend to charge at lower electricity prices, fewer vehicles charge during peak and off-peak hours of the power grid. Therefore, the scale on which energy storage can engage in peak-valley arbitrage is limited, and the installed capacity will not be too large.

[0010] The core objective of photovoltaic and energy storage applications is to reduce the electricity cost of existing charging capacity by using low-priced electricity. However, due to the limited installed capacity, the amount of electricity provided by photovoltaic carports is small and disproportionate to the demand for charging, thus limiting the effect of reducing charging prices. The installed capacity of energy storage is also small, and its role is generally limited to the peak-valley arbitrage model of grid electricity prices, thus having a relatively small effect on reducing overall charging prices.

[0011] In terms of overall architecture, it is merely a simple stacking of photovoltaics, energy storage, and charging stations, and it is difficult to achieve full interaction between light, energy storage, and charging at the technical level.

[0012] This is also because photovoltaics, energy storage, and charging piles operate independently according to their own working logic, and cannot be mutually called upon or coordinated. Under the current technology model, installing more photovoltaic and energy storage means wasting photovoltaic and energy storage resources, that is, the installed capacity of photovoltaic and energy storage cannot reach the megawatt level.

[0013] The core operational objective of large-scale photovoltaic-storage-charging microgrids is to replace grid power with large-scale photovoltaic power, a revolutionary power transformation that significantly reduces customer charging costs. In this microgrid system, photovoltaic power is prioritized and consumed immediately; surplus photovoltaic power that cannot be consumed immediately is transferred to other high-load periods through large-scale energy storage facilities; and the efficient control logic of the microgrid management system intelligently schedules various power sources and loads, tapping into the system's potential and maximizing customer charging costs.

[0014] The efficient operation of this large-scale photovoltaic-storage-charging microgrid relies on the construction of an efficient control logic system and the orderly execution of intelligent logic at each level within the system, thereby enabling large-scale utilization of photovoltaic and energy storage.

[0015] The efficient control logic system for large-scale photovoltaic-storage-charging microgrids comprises five layers, and the logic within these layers includes:

[0016] (1) Forecasting level: weather forecast, load forecast, photovoltaic power generation forecast, etc. These forecasts are further divided into day-ahead forecasts and real-time forecasts.

[0017] (2) Energy control level: load response of energy storage, peak charging ratio, photovoltaic charging ratio, anti-backflow, delayed charging and early withdrawal of photovoltaic charging related to sunrise and sunset time, transformer demand management, distributed energy mutual assistance, maximizing photovoltaic output, prioritizing photovoltaic charging, photovoltaic anti-backflow, and grid connection and off-grid switching, etc.

[0018] (3) Load control level: Adjust the power of charging piles, actively shut down the piles, etc.

[0019] (4) Operational level: dynamically adjust charging prices, use points redemption to attract users, etc.

[0020] (5) Further price reduction / revenue increase: energy storage peak-valley arbitrage, participation in electricity spot trading, participation in virtual power plants, participation in load aggregation, and optimization of power consumption economy at power plants.

[0021] The microgrid management system, through its efficient control logic architecture, coordinates the power supply and consumption of the external power grid, photovoltaic systems, energy storage, and charging piles based on predicted load and photovoltaic power generation.

[0022] (1) The external power grid serves as a supplementary power source for the overall power supply safety and stability of the microgrid.

[0023] (2) Photovoltaic power generation at maximum output is the main source of electricity for this project.

[0024] (3) Energy storage is used for the time and space transfer of surplus photovoltaic power, working in the form of load response and controlling the demand level of the external power grid; unused photovoltaic power during the day is stored through energy storage devices; when the photovoltaic output is insufficient to support the charging power demand, the energy storage devices discharge; when it is predicted that the photovoltaic power generation will be insufficient in the next day, the energy storage system charges the grid in advance during the off-peak period, and discharges during the peak electricity price, peak electricity price and high load periods of the next day.

[0025] (4) When the instantaneous power of the charging pile affects the monthly demand level or has a tendency to exceed the transformer load, if the energy storage power is exhausted and cannot respond, the microgrid system controls the charging pile to reduce the output power or shut down some charging piles.

[0026] Photovoltaic-storage-charging microgrids effectively reduce the power demand of charging stations from the grid by leveraging the dynamic capacity expansion capabilities of photovoltaics and energy storage, overcoming the bottleneck of small-capacity transformers. They also reduce vehicle charging costs through the low-cost electricity generated by photovoltaics, while simultaneously meeting the high-power, fast-charging needs of these vehicles. Summary of the Invention

[0027] To address the shortcomings of the existing technologies, a collaborative control system and method for a megawatt-level photovoltaic-storage-charging microgrid is provided. Through an innovative hierarchical control logic system, and especially a dynamic control strategy that solves the problem of the photovoltaic physical start-up threshold, a high proportion of photovoltaic power generation can be instantly absorbed and transferred in time and space within the microgrid. This significantly reduces the charging cost of electric vehicles and ensures the reliability and economy of large-scale system operation.

[0028] The technical solution adopted in this invention is:

[0029] A coordinated control system for a megawatt-level photovoltaic-storage-charging microgrid includes: a grid connection point, photovoltaic power generation units, an energy storage system, a charging pile load group, and a microgrid central controller; the total installed capacity of the photovoltaic power generation units is in the megawatt range, and the total capacity of the energy storage system matches the photovoltaic installed capacity to realize the spatiotemporal transfer of photovoltaic power; the microgrid central controller is configured to execute a hierarchical control system containing the following core control logic:

[0030] Based on the system power balance equation: P 电网 +P 光伏 +P 储放 =(1+μ)P 桩 +P 储充 For the control basis, where P 电网 P is the power input to the power grid. 光伏 For real-time photovoltaic power output, P 储放 For energy storage discharge power, P 桩 denoted as the total load power of the charging pile, Penergy storage is the energy storage charging power, and μ is the system loss rate.

[0031] The control logic includes at least:

[0032] Load response logic: Real-time monitoring of P 电网 When P 电网 Exceeding the preset maximum AC bus power P 母线max At that time, the energy storage system is controlled to enter the discharge state, and P is dynamically adjusted. 储放 , making P 电网 Stable at P 母线max ;

[0033] P 电网 +P 光 +P 储放 =(1+μ)P 桩

[0034] When P 电网 >P 母线max (P) 电网 Real-time and various time periods P 母线max (Set value comparison), energy storage enters load response state, dynamically adjusting P 储放 , making P 电网 =P 母线max ;

[0035] Photovoltaic charging logic: During the daytime, the P-grid is dynamically adjusted to keep the P-grid above the preset photovoltaic discharge threshold, thereby inducing the photovoltaic unit to reach its maximum power output. The P-discharge threshold is set according to the physical start-up characteristics of the photovoltaic unit.

[0036] Preferably, the execution process of the photovoltaic charging logic includes:

[0037] When the grid voltage P is less than the discharge threshold P, the energy storage system is controlled to gradually increase the charging power ramp rate P.

[0038] For each additional P ramp, monitor whether the output power of the photovoltaic unit increases by the same value.

[0039] When the photovoltaic output power no longer increases with the increase of P-storage charging, it is determined that the photovoltaic has reached its maximum output. At this time, the energy storage system is controlled to adjust the charging power back, so that the P grid returns to near the P discharge threshold.

[0040] The photovoltaic charging logic can only be activated during daytime hours (according to the sunrise and sunset schedules, as well as the time periods for sunrise delays and sunset advances).

[0041] P 电网 +P 光 =(1+μ)P 桩 +P 储充

[0042] Because of the existence of the photovoltaic start-up threshold P discharge threshold, P storage and charging must be dynamically adjusted so that P grid ≥ P discharge threshold before the photovoltaic system will discharge.

[0043] The specific steps are as follows: If the system detects that Pgrid < Pdischarge threshold, it considers that the photovoltaic power output is not at full power. The energy storage system then ramps up its charging at a ramp rate P (the set value is approximately 3% of the total power of the energy storage PCS; in this project, there are 5 energy storage units per group, with a ramp power of 125 * 3% ≈ 4kW per unit, so a group is 5 * 4 = 20kW). The charging power of the energy storage system is increased; for each additional Pdischarge threshold... 爬坡 The photovoltaic output will increase by an equal amount until the photovoltaic power no longer increases (reading photovoltaic Ailogger data), P 放电阈值 ≤P 电网 ≤P 放电阈值 +5*P 爬坡 Afterwards, the energy storage callback power (the callback value is P) 电网 -P 放电阈值 ), ultimately making P 电网 =P 放电阈值 At this point, the photovoltaic system has reached its maximum power output.

[0044] If no rate value is set for the energy storage power reduction, it will default to returning to the set value at the fastest rate of the system.

[0045] Preferably, the control logic further includes off-peak charging logic: during off-peak hours of the grid electricity price, the energy storage system is controlled to charge, and the grid input power P_grid or (P_grid + P_photovoltaic) is stabilized at a preset off-peak charging threshold P_off-peak charging threshold.

[0046] Off-peak electricity pricing period (according to the scheduled period) to activate off-peak charging logic

[0047] P 电网 +P 光 =(1+μ)P 桩 +P 储充

[0048] The above notes are based on sunrise and sunset times:

[0049] Valley period P after sunset 光 =0, dynamically adjust P 储充 , making P 电网 =(1+μ)P 桩 +P 储充 =P 充谷电阈值 .

[0050] Valley period after sunrise during the day (P) 光 >0, dynamically adjust P 储充 , making P 电网 +P 光 =(1+μ)P 桩 +P 储充 , where P 电网 =P 充谷电阈值 .

[0051] P 充谷电阈值 The significance is that the total power of the bus during energy storage charging does not exceed the safe operation limit of the bus or the demand management limit of the transformer.

[0052] Preferably, the microgrid central controller is further configured to execute intelligent operation logic, which is based on the day-ahead load forecast result WLn and the day-ahead photovoltaic power generation forecast result WSn, and the transformer capacity P... 变max Under the constraints, dynamic optimization is used to determine the maximum AC bus power P for each time period of the future day. 母线max and energy storage plan discharge power P 储放n To satisfy the safety constraint: ∑(P 储放n * Tn)≤ WB_remaining + ∑(WSn - (1+μ)WLn) - WB_rated*10%, where WB_remaining is the remaining energy storage capacity and WB_rated is the total rated capacity of energy storage.

[0053] Preferably, the intelligent operation logic determines that the energy storage capacity is insufficient to support the preset P. 母线max At that time, perform at least one of the following operations: initiate a valley charging plan to increase the energy storage capacity WBV; within a safe range, increase the P bus max setting value; generate and execute a power reduction or shutdown plan for some charging piles.

[0054] Preferably, the control system also includes operation layer logic for dynamically adjusting the charging service price for users based on the real-time energy availability of the system.

[0055] A method for coordinated control of a megawatt-level photovoltaic-storage-charging microgrid based on the system includes the following steps:

[0056] Construct and initialize a five-layer control logic framework comprising a day-ahead low-cost energy and load forecasting layer, an energy control layer, a load control layer, an operation layer, and a value-added layer;

[0057] Real-time data collection of grid power, photovoltaic power, energy storage status, and charging load power;

[0058] Based on the power balance equation, and according to the preset threshold and the current time period, the corresponding core control logic is selected and executed. The core control logic includes at least load response logic and photovoltaic charging logic.

[0059] When executing the photovoltaic charging logic, the power of the power grid port is kept above the photovoltaic discharge threshold by dynamically adjusting the energy storage charging power, so as to force the photovoltaic array to reach the maximum power output.

[0060] The day-ahead low-cost energy and load forecasting layer includes: the day-ahead load forecasting layer and the day-ahead photovoltaic forecasting layer;

[0061] The daytime load forecasting layer predicts the load curve of charging piles for each period based on historical data, weather forecasts, and traffic data, and makes judgments in conjunction with the maximum power of transformers and the time-of-use electricity price of the power grid.

[0062] The photovoltaic forecasting layer recently predicted the photovoltaic power generation curves for different time periods based on meteorological sensors and cloud data.

[0063] The energy control layer includes: load response layer, demand management layer, photovoltaic charging layer, energy sharing layer, and microgrid off-grid layer;

[0064] The load response layer determines the charging and discharging output power of independent energy storage and energy storage within the unit at different times;

[0065] The demand management layer monitors the total incoming lines in real time, implements grid power limit management, and strictly prevents transformer overload tripping.

[0066] The photovoltaic layer maximizes the output of local photovoltaic power, prioritizing the charging needs of this unit or station.

[0067] In the energy sharing layer, when the charging and discharging of each unit is unbalanced, cross-unit energy dispatch is carried out through the main bus.

[0068] Microgrid offline layer, supporting both on-grid and off-grid handover;

[0069] The load control layer is used for adjusting the power of charging piles; the operation control layer includes: the energy storage response spot layer, the charging station price management layer, and the peak-valley arbitrage layer.

[0070] Energy storage responds to the spot market: during periods of low prices, electricity is purchased from the grid to charge the energy storage, and during periods of high prices, the discharge peaks.

[0071] The charging station pricing management system implements dynamic electricity pricing to guide car owners to charge in an orderly manner (peak shaving and valley filling).

[0072] Peak-valley arbitrage layer: Calculates and controls the optimal proportion of electricity from the power grid during off-peak periods.

[0073] Value-added control layer: Used for network connectivity. It connects to the electricity spot market, virtual power plants, and load aggregation platforms, and receives grid dispatch instructions to respond to demand-side demands.

[0074] Preferably, the photovoltaic charging logic is activated only during the effective daytime period determined according to the sunrise and sunset schedule, and can be set to activate after a first preset time delay after sunrise and deactivate before sunset by a second preset time advance.

[0075] Preferably, it also includes an intelligent optimization step: based on the current forecast data, under the constraint of transformer capacity, with the goal of optimizing the economic efficiency of system operation or maximizing photovoltaic absorption, the energy storage charging and discharging plan and the upper limit of bus power are continuously optimized in the next 24 hours.

[0076] Preferably, it also includes a load control step: when the system power supply capacity is insufficient, a power reduction or shutdown command is sent to the designated charging pile to ensure system power balance and safety and stability.

[0077] The advantages of this invention over the prior art are:

[0078] This invention discloses a collaborative control system and method for a megawatt-level photovoltaic-storage-charging microgrid, which realizes refined and intelligent collaborative control, and increases the proportion of megawatt-level photovoltaic power generation to more than 70% of the real-time consumption and spatiotemporal transfer within the microgrid, making low-cost photovoltaic power the main power source for charging loads, rather than a simple supplement to grid power.

[0079] This invention discloses a coordinated control system and method for a megawatt-level photovoltaic-storage-charging microgrid. By using dynamic control logic for charging photovoltaic power based on the photovoltaic discharge threshold, it effectively addresses the physical start-up characteristics of photovoltaics, avoids frequent curtailment of solar power due to load fluctuations, and ensures maximum utilization of large-scale photovoltaic power.

[0080] This invention provides a collaborative control system and method for a megawatt-level photovoltaic-storage-charging microgrid, which improves the system's economy and safety: the energy storage working mode changes from a rigid peak-valley arbitrage to a flexible integration of photovoltaic transfer + demand management + peak-valley arbitrage multi-mode, fully realizing its value; strict load response and intelligent load control logic ensure that the system can safely withstand the random impact of high-power fast charging loads under limited transformer capacity.

[0081] This invention presents a collaborative control system and method for a megawatt-level photovoltaic-storage-charging microgrid, forming a complete smart energy solution. The constructed five-layer logic system—prediction, control logic, load execution, operational efficiency improvement, and business value-added—transcends traditional single energy management, achieving comprehensive collaborative optimization in technical, economic, and market dimensions, and providing complete technical support for the commercial and efficient operation of large-scale photovoltaic-storage-charging stations. Attached Figure Description

[0082] Figure 1 This is a five-layer logic architecture diagram of a collaborative control system for a megawatt-level photovoltaic-storage-charging microgrid according to the present invention;

[0083] Figure 2 This is a schematic diagram of a microgrid power system for a megawatt-level photovoltaic-storage-charging microgrid collaborative control system according to the present invention;

[0084] Figure 3 This is a logic diagram of energy storage and photovoltaic charging for a megawatt-level photovoltaic-storage-charging microgrid collaborative control system according to the present invention.

[0085] Figure 4 This is a system data acquisition and logic execution path diagram for a megawatt-level photovoltaic-storage-charging microgrid collaborative control system according to the present invention. Detailed Implementation

[0086] The present invention will now be described in detail with reference to the accompanying drawings and embodiments:

[0087] Appendix Figure 1 It can be seen that the efficient control logic system of large-scale photovoltaic-storage-charging microgrids includes five layers, and the logic within these layers includes:

[0088] The day-ahead low-cost energy and load forecasting layer includes: the day-ahead load forecasting layer and the day-ahead photovoltaic forecasting layer;

[0089] The daytime load forecasting layer predicts the load curve of charging piles for each period based on historical data, weather forecasts, and traffic data, and makes judgments in conjunction with the maximum power of transformers and the time-of-use electricity price of the power grid.

[0090] The photovoltaic forecasting layer recently predicted the photovoltaic power generation curves for different time periods based on meteorological sensors and cloud data.

[0091] The energy control layer includes: load response layer, demand management layer, photovoltaic charging layer, energy sharing layer, and microgrid off-grid layer;

[0092] The load response layer determines the charging and discharging output power of independent energy storage and energy storage within the unit at different times;

[0093] The demand management layer monitors the total incoming lines in real time, implements grid power limit management, and strictly prevents transformer overload tripping.

[0094] The photovoltaic layer maximizes the output of local photovoltaic power, prioritizing the charging needs of this unit or station.

[0095] In the energy sharing layer, when the charging and discharging of each unit is unbalanced, cross-unit energy dispatch is carried out through the main bus.

[0096] Microgrid offline layer, supporting both on-grid and off-grid handover;

[0097] Load control layer: used for adjusting the power of charging piles; when encountering energy bottlenecks, it implements a flexible current-cutting strategy of "reducing power and shutting down fewer charging piles".

[0098] The operation control layer includes: the energy storage response spot layer, the charging station price management layer, and the peak-valley arbitrage layer;

[0099] Energy storage responds to the spot market: during periods of low prices, electricity is purchased from the grid to charge the energy storage, and during periods of high prices, the discharge peaks.

[0100] The charging station pricing management system implements dynamic electricity pricing to guide car owners to charge in an orderly manner (peak shaving and valley filling).

[0101] Peak-valley arbitrage layer: calculates and controls the optimal proportion of electricity from the power grid during off-peak periods.

[0102] Value-added control layer (external interaction): Used for network connection. It connects to the electricity spot market, virtual power plants (VPPs), and load aggregation platforms, receives grid dispatch instructions to respond to demand, and can involve photovoltaic, energy storage, and charging piles to increase revenue.

[0103] The microgrid management system, through its efficient control logic architecture, coordinates the power supply and consumption of the external power grid, photovoltaic systems, energy storage, and charging piles based on predicted load and photovoltaic power generation.

[0104] (1) The external power grid serves as a supplementary power source for the overall power supply safety and stability of the microgrid.

[0105] (2) Photovoltaic power generation at maximum output is the main source of electricity for this project.

[0106] (3) Energy storage is used for the time and space transfer of surplus photovoltaic power, working in the form of load response and controlling the demand level of the external power grid; unused photovoltaic power during the day is stored through energy storage devices; when the photovoltaic output is insufficient to support the charging power demand, the energy storage devices discharge; when it is predicted that the photovoltaic power generation will be insufficient in the next day, the energy storage system charges the grid in advance during the off-peak period, and discharges during the peak electricity price, peak electricity price and high load periods of the next day.

[0107] (4) When the instantaneous power of the charging pile affects the monthly demand level or has a tendency to exceed the transformer load, if the energy storage power is exhausted and cannot respond, the microgrid system controls the charging pile to reduce the output power or shut down some charging piles.

[0108] Photovoltaic-storage-charging microgrids effectively reduce the power demand of charging stations from the grid by leveraging the dynamic capacity expansion capabilities of photovoltaics and energy storage, overcoming the bottleneck of small-capacity transformers. They also reduce vehicle charging costs through the low-cost electricity generated by photovoltaics, while simultaneously meeting the high-power, fast-charging needs of these vehicles.

[0109] The photovoltaic-storage-charging microgrid, centered on a microgrid intelligent control core, constructs a closed-loop control system. This system comprises grid transformers, photovoltaic systems, energy storage systems, and charging stations as its main hardware; current transformers and weather sensors as local data acquisition tools; cloud-based data support including time-of-use pricing, weather forecasts, competitor data, traffic data, electricity spot market data, and grid dispatch instructions; a safety barrier (transformer and interface current limiting) as its boundary; flexible adjustment of energy storage, photovoltaics, and charging piles as its means; and maximizing economic benefits as its goal. Through the effective management of the microgrid intelligent control core, the orderly flow of electricity, information, and customers is achieved, resolving the instability and mismatch between photovoltaics and charging, and enabling large-scale replacement of grid electricity by photovoltaic power.

[0110] The overall operation process of system data acquisition and logic execution is as follows:

[0111] 1. The data acquisition and sensing phase includes: real-time data collection from both physical and network dimensions.

[0112] Hardware-level data (milliseconds / seconds): Real-time collection of actual power, voltage, and current flow of each sub-unit (photovoltaic, energy storage, and charging pile) through voltage / current transformers, photovoltaic bidirectional smart meters, energy storage bidirectional smart meters, and grid connection point smart meters.

[0113] Environmental and external data (minute / hour level): External information such as meteorological sensors (light intensity, temperature), time-of-use electricity pricing interface, weather forecast, traffic flow prediction, and virtual power plant (VPP) dispatch instructions are synchronously imported.

[0114] 2. Intelligent Core Decision-Making Stage (Process)

[0115] All data is aggregated into the microgrid control intelligent core. The core compares the real-time total load with the total power generation, and calculates the current energy allocation scheme by combining time-of-use pricing and transformer capacity limits. The scheme has been compared in terms of safety, flexibility, economy and other aspects, and is the current optimal scheme.

[0116] 3. Logic Execution and Action Phase (Output)

[0117] After the core decision is made, hard action commands are issued to the underlying devices via RS485, TCP / IP, and other relevant communication protocols, including:

[0118] Photovoltaic execution: Adjusting the photovoltaic inverter (reducing power generation command, cutting off reverse current).

[0119] Energy storage function: Regulate the charging and discharging direction and power of the PCS (energy storage converter) to stabilize the current and voltage of the main bus and daughter bus.

[0120] Charging pile execution: Send a "flexible current limiting" command to the main control board of the charging pile to smoothly reduce the output power of the charging vehicle without shutting down the charging pile.

[0121] The main decision-making and execution control processes include:

[0122] Process 1: System-level electrical safety defense (ensuring the safety of busbars and transformers).

[0123] Transformer bidirectional hard constraint control (electricity demand and reverse power management):

[0124] Power extraction defense: Real-time monitoring of total grid current. When (total load) > (total generation + transformer power extraction limit), orderly charging is forcibly triggered. The power of charging piles is reduced according to priority or idle energy storage is forcibly discharged to ensure that the bus current does not exceed the standard.

[0125] Reverse feedback defense line: When (total power generation) > (total load + transformer reverse feedback limit), instruct the photovoltaic inverter to operate at reduced capacity or guide idle energy storage to be forcibly charged to ensure that the reverse feedback grid current does not exceed the limit.

[0126] Main busbar thermal stress counterbalancing control:

[0127] The theoretical peak value of the main busbar is calculated in real time. If the temperature rise of a certain section of the busbar is too fast or the current is close to the physical selection safety margin, the mutual flow of the two sides (voltage drop power of the power supply unit or charging power of the power receiving unit) is immediately limited.

[0128] Process 2: Unit-level energy self-consistency and mutual isolation (protecting the unit bus).

[0129] Local consumption is given absolute priority; the charging load within a sub-unit is primarily provided by the photovoltaic and energy storage systems within the unit; current is only allowed to flow to the unit combiner cabinet for energy mutual assistance at the main bus level when there is a net surplus or net deficit within the sub-unit; interface-level bidirectional current limiting protection; monitoring of the main circuit breaker connected to the main bus of each sub-unit combiner cabinet;

[0130] Power supply current limiting: The current supplied by the sub-unit to the main bus is locked to a limit by the control core; if the internal power generation is excessive, the local photovoltaic power generation is limited or the local energy storage is shut down.

[0131] Current limiting: The current drawn by the sub-unit from the main bus is also locked to a limit; if the charging pile is fully loaded but the local sub-unit does not generate electricity, the interface current must be within the safe threshold, otherwise the charging pile power will be reduced.

[0132] Process 3: Flexible supply of charging piles (ensuring charging experience).

[0133] The strategy of "fewer pile closures and gentle power reduction";

[0134] When the system triggers a power supply limitation (demand alarm), the microgrid intelligent control core does not directly cut off the power supply to a certain charging pile.

[0135] Implement flexible allocation: Based on the SOC (State of Charge) and demand of each vehicle, smoothly reduce the power of all charging vehicles proportionally or according to priority to ensure that all vehicles are powered continuously.

[0136] Millisecond-level voltage / current support for energy storage;

[0137] When photovoltaic power drops suddenly due to cloud cover or when a large number of vehicles plug in at the same time, causing a sudden surge in load, the energy storage equipment (independent energy storage groups and unit energy storage) performs a transient response, filling the gap by instantaneous discharge through the energy storage PCS, and smoothing the voltage and current fluctuations of the unit bus and the main bus.

[0138] Process 4: Multidimensional economic optimization (cost reduction and revenue increase).

[0139] Dynamic load transfer;

[0140] By leveraging price mechanisms (dynamic price dashboards at charging stations), car owners are encouraged to charge their vehicles during peak solar power generation periods or when prices are significantly lower than grid prices.

[0141] Virtual power plant (VPP) aggregate response;

[0142] By receiving grid dispatch instructions (peak shaving / valley filling) and coordinating the charging and discharging directions of multiple independent energy storage systems, combined with the flexible voltage drop of the charging load, the entire microgrid can be presented to the outside world as a dispatchable elastic load / power source, thereby obtaining ancillary service subsidies.

[0143] Process 5: Maximize photovoltaic power output.

[0144] Busbar backfeed current control: When the busbar current does not exceed the transformer backfeed limit, the photovoltaic system continues to maximize its output;

[0145] Energy storage charging photovoltaic power: When the power of the grid-side meter is less than the physical discharge threshold of the photovoltaic system and it is during a period of sunshine, the energy storage system starts charging the photovoltaic system. The charging power of the energy storage system gradually increases from the minimum power, and the inverter power also increases accordingly. When the power of the meter is detected to be greater than the photovoltaic discharge threshold, it means that the inverter has reached its maximum output value. The charging power of the energy storage system is then adjusted back to make the power of the meter equal to the photovoltaic discharge threshold. At this time, the charging and discharging is in a balanced state, that is, the photovoltaic system is at its maximum output and the energy storage system is only charging the photovoltaic system.

[0146] The intelligent core of microgrid control is the physical entity of the microgrid's brain; the five-layer logical architecture is the "operating system and thought logic" running within this brain. The five-layer architecture modularly breaks down the complex work of the intelligent core:

[0147] The first layer is the low-cost energy and load forecasting layer, which is the core "predictive radar". It uses external weather and traffic data to calculate the photovoltaic curve and charging peak for tomorrow in advance, so that the core can "know what to do" in terms of power allocation.

[0148] The second layer, the energy control layer, forms the safety baseline of the intelligent core and the foundation for economical power dispatch and operation. It includes logics such as load response, demand management, energy sharing, and maximizing photovoltaic output.

[0149] The third layer, the load control layer, is the intelligent core's flexible buffer and business strategy. It is responsible for minimizing the power reduction and shutdown of charging piles when extreme conditions arise.

[0150] The fourth layer, the operation and control layer, is responsible for the operation and management of the charging station. Through its own photovoltaic, energy storage and charging equipment capabilities, it executes peak-valley arbitrage, electricity spot arbitrage, and dynamic electricity price adjustments to ensure that the charging station can both serve car owners well and ensure revenue.

[0151] The fifth layer, the value-added control layer, is the core "social interface," responsible for interacting with the power grid, electricity sales companies, virtual power plants, load aggregators, etc., receiving dispatch instructions, and earning additional revenue.

[0152] The five-layer logical architecture is a detailed diagram of the internal algorithms of the intelligent core of microgrid control. It runs through the complete information flow from top to bottom: "advance prediction → external order acceptance → internal accounting (ensuring safety / seeking profit) → flexible allocation → hardware execution". It is this layered mechanism that supports the complex and massive energy hedging system of megawatt-level photovoltaic-storage-charging microgrids.

[0153] Implementation of microgrid control logic:

[0154] The key to managing photovoltaic, energy storage, and charging microgrids lies in controlling the power generation and consumption of each device. By adjusting the real-time power of these devices, the microgrid's power consumption, spatial and temporal transfer of power, and load aggregation are executed according to predetermined logic, ensuring the system's safety and stability.

[0155] Basic formulas and physical conditions:

[0156] (1) Basic formula: P 电网 +P 光 +P 储放 =(1+μ)P 桩 +P 储充 ,in:

[0157] P 电网 P 光 For momentum;

[0158] P 储放 P 储充 It is a controllable active quantity;

[0159] P 桩 An uncontrollable active force;

[0160] μ is the system loss rate from the microgrid bus to the charging pile, taking the state of no energy storage charging and discharging and photovoltaic discharge, and the total power of the charging station > 60kW, the average of 20 measurement points randomly distributed throughout the day, (1 - total power of charging station / power of grid);

[0161] P-light is taken from the photovoltaic grid connection point table. If inverter data is taken, the line loss from the inverter to the bus must also be considered.

[0162] (2) Three important settings for energy storage devices:

[0163] P bus max is the maximum power of the AC bus --- the discharge power setting;

[0164] P-off-peak charging threshold, also known as off-peak charging threshold --- off-peak charging power setting;

[0165] The P discharge threshold is the power control value of the power grid gateway meter that matches the characteristics of photovoltaic power generation. Photovoltaic power generation will only occur when the power of the gateway meter is higher than this value.

[0166] (3) The photovoltaic power of the energy storage device P is not a set value. It is dynamically adjusted after calculation based on factors such as photovoltaic output and load size.

[0167] (4) Energy storage setting P is the power that does not need to be adjusted (default 2kW). When the P grid fluctuation is less than the P power that does not need to be adjusted, P storage charging and P storage discharging will not be adjusted.

[0168] (5) Photovoltaic can only start after the load power reaches a certain threshold (physical characteristic), that is, the power P of the grid collected by the photovoltaic power grid (which is consistent with the data of the energy storage grid meter) (approximately 2%-5% of the inverter's installed power) can only start. After measuring this value, the photovoltaic start-up threshold P discharge threshold is written into the program as the control target of the grid meter power when the energy storage charges the photovoltaic.

[0169] (6) P grid follows the signal without response delay; P optical has a second-level response delay; P energy storage has a millisecond-level response delay for charging / discharging.

[0170] System power response status:

[0171] (1) Load response status;

[0172] At any given time, the load response logic is at the highest level;

[0173] P 电网 +P 光 +P storage = (1+μ)P 桩

[0174] When P 电网 >P 母线max (The P grid is compared with the P bus max setting value in real time and at each time period), the energy storage enters the load response state, and the P storage is dynamically adjusted so that the P grid = P bus max.

[0175] (2) Off-peak charging state;

[0176] Off-peak electricity pricing period (according to the scheduled period) to activate off-peak charging logic

[0177] P 电网 +P 光 =(1+μ)P 桩 +P 储充

[0178] The above notes are based on sunrise and sunset times:

[0179] Valley period P after sunset 光 =0, dynamically adjust P 储充 , making P 电网 =(1+μ)P pile + P storage and charging = P charging valley electricity threshold.

[0180] Valley period after sunrise during the day (P) 光 >0, dynamically adjust Pstorage and Plight to make Pgrid + Plight = (1 + μ)P 桩 +P 储充 , where Pgrid = Pvalley charging threshold.

[0181] P 充谷电阈值The significance is that the total power of the bus during energy storage charging does not exceed the safe operation limit of the bus or the demand management limit of the transformer.

[0182] (3) Photovoltaic charging status;

[0183] The photovoltaic charging logic can only be activated during daytime hours (according to the sunrise and sunset schedules and the time periods for sunrise delays and sunset advance determinations);

[0184] P 电网 +P 光 =(1+μ)P 桩 +P 储充 ;

[0185] Because of the photovoltaic start-up threshold P 放电阈值 The existence of P requires dynamic adjustment of P storage and charging to ensure that P grid ≥ P discharge threshold before photovoltaic discharge occurs.

[0186] The specific steps are as follows: If the system detects that Pgrid < Pdischarge threshold, it considers that the photovoltaic power output is not at full power. The energy storage system then ramps up its charging at a ramp rate P (the set value is approximately 3% of the total power of the energy storage PCS; in this project, there are 5 energy storage units per group, with a ramp power of 125 * 3% ≈ 4kW per unit, so a group is 5 * 4 = 20kW). The charging power of the energy storage system is increased; for each additional Pdischarge threshold... 爬坡 The photovoltaic output will increase by the same value until the photovoltaic power no longer increases (reading photovoltaic Ailogger data). After the P discharge threshold ≤ P grid ≤ P discharge threshold + 5 * P ramp-up, the energy storage power will be adjusted back (the adjustment value is P grid - P discharge threshold), eventually making P grid = P discharge threshold. At this time, the photovoltaic has reached its maximum power output.

[0187] If no rate value is set for the energy storage power reduction, it will default to returning to the set value at the fastest rate of the system.

[0188] (4) Peak-valley (peak-high) arbitrage;

[0189] Peak-valley arbitrage follows the same logic as load response, except that the P bus maximum is reduced during peak and high-price periods to maximize energy storage output. During daytime photovoltaic power generation, the P bus maximum for peak-valley arbitrage must not fall below the P discharge threshold, otherwise it will affect normal photovoltaic discharge.

[0190] Relevant settings parameters:

[0191] (1) Periods during which charging is prohibited;

[0192] By inputting specific time periods, such as 17:00-19:00 (January, July, August, and December), charging can be prohibited during these periods of high electricity prices / no solar power, thus preventing unexpected increases in costs.

[0193] (2) Sunrise is delayed and sunset is earlier;

[0194] Due to the existence of the P discharge threshold, during the periods of low photovoltaic output in the early morning and evening, activating the photovoltaic charging logic will simultaneously charge a large proportion of the mains power, which is uneconomical. Therefore, the photovoltaic charging program should start with a delayed start in the morning and exit earlier in the evening, with testing showing that 25 minutes is ideal for these two times. The start and exit times should be based on the local daily sunrise and sunset schedule throughout the year.

[0195] (3) Adjustment of P-pillars;

[0196] Under normal operating conditions, the P-pile is not controlled to maximize the charging needs of each customer; when the system power supply capacity is insufficient (including insufficient transformer capacity, insufficient energy storage capacity, insufficient photovoltaic output, etc.), the charging pile is subject to system scheduling and performs reduced power operation or shuts down.

[0197] List of main control parameters

[0198]

[0199]

[0200] Intelligent adjustment of microgrid operation control logic:

[0201] Operational logic of photovoltaic-storage-charging microgrid;

[0202] The efficient operation of microgrids relies on the orderly execution of various intelligent logics, including: weather forecasting, load forecasting, and photovoltaic power generation forecasting; load response of energy storage, off-peak charging ratio, photovoltaic charging ratio, backflow prevention, delayed photovoltaic charging and early withdrawal of photovoltaic charging related to sunrise and sunset times, transformer demand management, and distributed energy mutual assistance; maximizing photovoltaic output, prioritizing photovoltaic charging, photovoltaic backflow prevention, and grid-connected / off-grid switching; adjusting charging pile power and actively shutting down charging piles; dynamically adjusting charging prices and using points redemption to attract users; peak-valley arbitrage of energy storage, participation in electricity spot trading, participation in virtual power plants, participation in load aggregation, and optimization of power consumption economics at power plants.

[0203] Among them, the load response logic (AC bus maximum power setting) is the basic logic for the safe operation of the entire energy system, and will be introduced in detail here. Other logics will not be elaborated on.

[0204] A brief introduction to load response logic:

[0205] (1) Based on weather, holidays, large-scale exhibitions, large-scale conferences, road construction, charging station equipment maintenance, promotions, traffic restrictions, etc., build a prediction model to predict the load power value for half an hour in the next day, i.e. WL01→WL48.

[0206] (2) Based on historical data, actual power generation data, irradiance data of the station meteorological instrument, irradiance data of the weather forecast, temperature, cloudy, overcast, rain, snow, dust, haze, photovoltaic equipment maintenance, etc., a prediction model is built to predict the power generation value for half an hour in the next day, i.e. WS01→WS48.

[0207] (3) P in each time period 桩n (WLn / Tn) P can be obtained through load forecasting. 光n (WSn / Tn) can be obtained through photovoltaic power generation prediction.

[0208] (4) When the transformer capacity is sufficient, economic efficiency takes precedence, and the output of photovoltaic and energy storage can be maximized, which is relatively simple. However, when the transformer capacity is insufficient, the safety and stability of power supply take precedence, which is complex. The following is a brief introduction to the intelligent adjustment logic for insufficient transformer capacity.

[0209] Objective: To prevent transformer overload; and to maximize the discharge revenue of photovoltaic and energy storage systems by discharging electricity sequentially during peak, off-peak, and normal periods, provided that the transformer is not overloaded.

[0210] Logical foundation data:

[0211] A. Transformer capacity constraint: Set the maximum allowable power P of the transformer. 变max .

[0212] B. When the microgrid is operating stably and safely, P 电网 +P 光 +P 储放 =(1+μ)P 桩 +P 储充 P here 电网 This is the maximum power value P of the AC bus after energy storage control. max The busbar ensures that the total power of the transformer must meet P. 变max ≥P max母线 .

[0213] C, P max母线 =(1+μ)P 桩 -P 光 -P 储放 +P 储充 P pile changes at any time, P 光 Continuously maximize output, P 储放 Follow-up (with P) 储充 Mutually exclusive), P max The busbar configuration should be set to ensure the safe operation of the microgrid, and the smaller the busbar, the better, under the condition that the remaining daily energy storage capacity is minimized (but not completely used up).

[0214] D. Considering the existence of the photovoltaic discharge threshold, during the photovoltaic power generation period, P max The minimum value of the busbar is P放电 Threshold; during non-photovoltaic power generation periods, P max The minimum value of the busbar can theoretically be taken as 0.

[0215] Determination of the maximum power value of the AC bus:

[0216] A. Accounting Logic:

[0217] P 光n ≥(1+μ)P 桩n At that time, P 电网 =Total inverter power * (-Anti-reverse current setting value);

[0218] (1+μ)P 桩n -P 光n <P 母线max hour;

[0219] P 电网 = (1+μ)P 桩n -P 光n；

[0220] (1+μ)P 桩n -P 光n ≥P 母线max hour,

[0221] P 电网 = P 母线max P 储放n =(1+μ)P 桩n -P 光n -P 母线max ;

[0222] Therefore, when (1+μ)P 桩n -P 光n ≥P 母线max When, 0 must be less than ∑((1+μ)P 桩n -P 光n -P 母线max )*Tn)≤WB 总 ;

[0223] B, P, and bus bar maximum are calculated starting from P becoming maximum and gradually decreasing, based on P. 储放n =(1+μ)P 桩n - P 光n -P 母线max A value greater than 0 forms a list of n values ​​stored in P.

[0224] Accounting in P 母线max =P 变max In the case of ∑(P) 储放n *Tn)-(WB 剩 +∑(WSn-(1+μ)WLn))+WB 额If *10%>0, it means that the remaining energy storage capacity and the unconsumed photovoltaic power for the next day are insufficient to support the safe operation of the system. Therefore, the energy storage needs to be charged with the nighttime electricity WBV, so that ∑(P 储放n *Tn)-(WBV+WB 剩 +∑(WSn-(1+μ)WLn)+WB 额 *10%=0, P on the next day 母线max =P 变max As in the previous formula (WBV+WB) 剩 +∑(WSn-(1+μ)WLn)+WB 额 *10%=WB 额时 P still cannot be satisfied 母线max ≤P 变max The pile closure plan must be implemented to re-form P. 储放n List.

[0225] When energy storage does not require charging and the nighttime power WBV is low, the adjustment step is gradually reduced in increments of 5% of P becoming maximum, and P is refreshed. 储放n A list of values, up to ∑(P) 储放n *Tn) is close to (WB) 剩 +∑(WSn-(1+μ)WLn)- WB 额 *10%), and ∑(P 储放n *Tn)-(WB left +∑(WSn-(1+μ)WLn))+WB 额 *10%<0.

[0226] Then, adjust the value of P by 0.5% of the maximum value as a step. 母线max Continue decreasing until ∑(P) 储放n *Tn) is closest to (WB remainder + ∑(WSn-(1+μ)WLn) - WB amount*10%), and ∑(P 储放n *Tn)-(WB left +∑(WSn-(1+μ)WLn))+WB 额 *10%<0, take the P value formed at this time. 储放n Forecast values ​​and energy storage capacity allocation list and P 母线max The value (this state has a single value throughout the day) is the control target.

[0227] Note: Here, "WB amount * 10%" is the reserved value for energy storage DOD.

[0228] Electricity Price Period Energy storage discharge power (kW) Energy storage power distribution (kWh) AC bus maximum power value (kW) - single value 00:00~00:30 <![CDATA[P 储放01 ]]> <![CDATA[WB 01 ]]> <![CDATA[P max母线 ]]> 00:30~01:00 <![CDATA[P 储放02 ]]> <![CDATA[WB 02 ]]> <![CDATA[P max母线 ]]> …… <![CDATA[P 储放n ]]> WBn <![CDATA[P max母线 ]]> 23:30~00:00 <![CDATA[P 储放 48]]> WB48 <![CDATA[P max母线 ]]>

[0229] C. Day 2 (1+μ)P 桩n -P 光n ≥P 母线max At the same time, the energy storage discharge power is adjusted in real time to stabilize the bus power at P. 母线maxThe control formula is Pstorage = (1 + μ)P 桩 -P 母线max -P 光 .

[0230] D. If the cumulative discharge of the energy storage during the executed period is lower than the actual reserved cumulative amount, it will not affect the execution of subsequent periods. If the total discharge is lower than the actual reserved cumulative amount, other periods that did not occur today will be added as discharge periods, or if it is predicted that the energy storage's rechargeable photovoltaic power will be insufficient on the next day, the discharge will be postponed to the next day. Any discharge not completed within the day will be postponed to the next day. If the discharge of the executed period is higher than the actual reserved cumulative amount, then based on the remaining energy storage power and the remaining expected rechargeable power ∑(WSn-(1+μ)WLn) within the day, steps A to C will be repeated, and P will be updated again. 母线max Value and P 储放n List of predicted values.

[0231] This invention discloses a collaborative control system and method for a megawatt-level photovoltaic-storage-charging microgrid, which realizes refined and intelligent collaborative control, and increases the proportion of megawatt-level photovoltaic power generation to more than 70% of the real-time consumption and spatiotemporal transfer within the microgrid, making low-cost photovoltaic power the main power source for charging loads, rather than a simple supplement to grid power.

[0232] This invention discloses a coordinated control system and method for a megawatt-level photovoltaic-storage-charging microgrid. By using dynamic control logic for charging photovoltaic power based on the photovoltaic discharge threshold, it effectively addresses the physical start-up characteristics of photovoltaics, avoids frequent curtailment of solar power due to load fluctuations, and ensures maximum utilization of large-scale photovoltaic power.

[0233] This invention provides a collaborative control system and method for a megawatt-level photovoltaic-storage-charging microgrid, which improves the system's economy and safety: the energy storage working mode changes from a rigid peak-valley arbitrage to a flexible integration of photovoltaic transfer + demand management + peak-valley arbitrage multi-mode, fully realizing its value; strict load response and intelligent load control logic ensure that the system can safely withstand the random impact of high-power fast charging loads under limited transformer capacity.

[0234] This invention presents a collaborative control system and method for a megawatt-level photovoltaic-storage-charging microgrid, forming a complete smart energy solution. The constructed five-layer logic system of prediction-control-load-operation-value-added surpasses traditional single energy management, achieving comprehensive collaborative optimization in technical, economic, and market dimensions, and providing complete technical support for the commercial and efficient operation of large-scale photovoltaic-storage-charging stations.

[0235] Existing photovoltaic-storage-charging microgrid systems primarily utilize grid electricity, with photovoltaic power typically accounting for no more than 10%, thus limiting their price reduction effect. Once large-scale photovoltaic-storage-charging microgrids are built, the annual photovoltaic power utilization rate can generally exceed 70%, reaching over 85% during peak photovoltaic months. Currently, the total lifecycle cost of photovoltaic power generation is below 0.1 yuan / kWh, far lower than the grid electricity price of 0.5-0.7 yuan / kWh. Therefore, large-scale photovoltaic-storage-charging microgrids, supported by an efficient control logic system, can significantly reduce charging costs for new energy vehicle customers while also generating appropriate returns for investors in photovoltaic-storage-charging microgrid projects.

[0236] The implementation of large-scale photovoltaic-storage-charging microgrid projects has also brought about significant social benefits, mainly including: stimulating new heavy asset (photovoltaic, energy storage, and charging) investment in the local area; creating new industry jobs, such as site construction, site operation, and equipment maintenance; reducing the charging costs of local operating vehicles, correspondingly increasing the profits and tax burden of operating companies; reducing the charging costs of private vehicles, reducing transportation expenses, and improving the happiness index; lowering the charging electricity price during peak hours (16:00-23:00), eliminating the need for vehicles to charge at low prices late at night, which is more in line with human needs; and reducing the concentrated impact of charging stations on the main power grid during peak electricity consumption periods, delaying and reducing the need for grid upgrades caused by the construction of large-scale charging stations, thus making it a grid-friendly project.

Claims

1. A collaborative control system for a megawatt-level photovoltaic-storage-charging microgrid, characterized in that, include: The system comprises a grid connection point, photovoltaic (PV) power generation units, an energy storage system, a charging pile load group, and a microgrid central controller. The total installed capacity of the PV power generation units is in the megawatt range, and the total capacity of the energy storage system matches the PV installed capacity to achieve the spatiotemporal transfer of PV power. The microgrid central controller is configured to execute a hierarchical control system containing the following core control logic: Based on the system power balance equation: P 电网 +P 光伏 +P 储放 =(1+μ)P 桩 +P 储充 For the control basis, where P 电网 P is the power input to the power grid. 光伏 For real-time photovoltaic power output, P 储放 For energy storage discharge power, P 桩 denoted as the total load power of the charging pile, Penergy storage is the energy storage charging power, and μ is the system loss rate. The control logic includes at least: Load response logic: Real-time monitoring of P 电网 When P 电网 Exceeding the preset maximum AC bus power P 母线max At that time, the energy storage system is controlled to enter the discharge state, and P is dynamically adjusted. 储放 , making P 电网 Stable at P 母线max ; P 电网 +P 光 +P 储放 =(1+μ)P 桩 ; When P 电网 >P 母线max Energy storage enters load response mode, dynamically adjusting P 储放 , making P 电网 =P 母线max ; Solar charging logic: During daytime hours, dynamically adjust P 储充 This keeps the P grid at the preset photovoltaic discharge threshold P. 放电 Above the threshold, this induces the photovoltaic unit to reach its maximum power output, where P 放电 The threshold is set based on the physical start-up characteristics of the photovoltaic unit.

2. The coordinated control system for a megawatt-level photovoltaic-storage-charging microgrid according to claim 1, characterized in that, The execution process of the photovoltaic charging logic includes: P was detected 电网 < P 放电 When the threshold is reached, the energy storage system is controlled to ramp up at a preset charging power rate P. 爬坡 Gradually increase P 储充 ; Each additional P 爬坡 Monitor whether the output power of the photovoltaic unit increases by the same amount; When photovoltaic output power no longer varies with P 储充 When the power output of the photovoltaic system increases, it is determined that the photovoltaic system has reached its maximum output. At this point, the energy storage system is controlled to adjust its charging power back to allow P to increase its output. 电网 Callback to P 放电阈值 nearby; The photovoltaic charging logic can only be activated during daytime hours; P 电网 +P 光 =(1+μ)P 桩 +P 储充 ; Because of the photovoltaic start-up threshold P 放电阈值 The existence of P necessitates dynamic adjustment. 储充 , making P 电网 ≥P 放电阈值 Photovoltaics will only discharge electricity when photovoltaics are in operation; The specific steps are: The system detects P 电网 <P 放电阈值 If the photovoltaic system is not operating at full power, then the energy storage system will operate at a charging ramp rate P. 爬坡 Increase energy storage charging power; for every additional P 爬坡 The photovoltaic output will increase by an equal amount until the photovoltaic power no longer increases. P 放电阈值 ≤P 电网 ≤P 放电阈值 +5*P 爬坡 Afterwards, the energy storage power is restored, ultimately making P 电网 =P 放电阈值 At this point, the photovoltaic system has reached its maximum power output; If no rate value is set for the energy storage power reduction, it will default to returning to the set value at the fastest rate of the system.

3. The coordinated control system for a megawatt-level photovoltaic-storage-charging microgrid according to claim 1 or 2, characterized in that, The control logic also includes off-peak charging logic: during off-peak hours when the grid electricity price is low, the energy storage system is controlled to charge, and the grid input power P is increased. 电网 The charging threshold P is stabilized during the preset off-peak period. 充谷电 Threshold.

4. The coordinated control system for a megawatt-level photovoltaic-storage-charging microgrid according to claim 1, characterized in that, The microgrid central controller is also configured to execute intelligent operation logic, which is based on the day-ahead load forecast result WLn and the day-ahead photovoltaic power generation forecast result WSn, and the transformer capacity P... 变max Under the constraints, dynamic optimization is used to determine the maximum AC bus power P for each time period of the future day. 母线max and energy storage plan discharge power P 储放n To satisfy the safety constraint: ∑(P 储放n * Tn)≤ WB 剩 +∑(WSn - (1+μ)WLn) - WB 额 *10%, where WB_remaining is the remaining energy storage capacity, and WB_rated is the total rated capacity of energy storage.

5. The coordinated control system for a megawatt-level photovoltaic-storage-charging microgrid according to claim 4, characterized in that, The intelligent operation logic determines that the energy storage capacity is insufficient to support the preset P. 母线max At that time, perform at least one of the following operations: initiate a valley charging plan to increase the energy storage capacity WBV; lower the P bus max setting value; generate and execute a power reduction or shutdown plan for some charging piles.

6. The coordinated control system for a megawatt-level photovoltaic-storage-charging microgrid according to claim 1, characterized in that, The control system also includes operational layer logic, which dynamically adjusts the charging service price for users based on the system's real-time energy adequacy.

7. A control method for a coordinated control system of a megawatt-level photovoltaic-storage-charging microgrid according to any one of claims 1-6, characterized in that, Includes the following steps: Construct and initialize a five-layer control logic framework comprising a day-ahead load forecasting layer, an energy control layer, a load control layer, an operations layer, and a value-added layer; Real-time data collection of grid power, photovoltaic power, energy storage status, and charging load power; Based on the power balance equation, and according to the preset threshold and the current time period, the corresponding core control logic is selected and executed. The core control logic includes at least load response logic and photovoltaic charging logic. When executing the photovoltaic charging logic, the power of the power grid port is kept above the photovoltaic discharge threshold by dynamically adjusting the energy storage charging power, so as to force the photovoltaic array to reach the maximum power output. The day-ahead load forecasting layer includes: the day-ahead load forecasting layer and the day-ahead photovoltaic forecasting layer; The daytime load forecasting layer predicts the load curve of charging piles for each period based on historical data, weather forecasts, and traffic data, and makes judgments in conjunction with the maximum power of transformers and the time-of-use electricity price of the power grid. The photovoltaic forecasting layer recently predicted the photovoltaic power generation curves for different time periods based on meteorological sensors and cloud data. The energy control layer includes: load response layer, demand management layer, photovoltaic charging layer, energy sharing layer, and microgrid off-grid layer; The load response layer determines the charging and discharging output power of independent energy storage and energy storage within the unit at different times; The demand management layer monitors the total incoming lines in real time, implements grid power limit management, and strictly prevents transformer overload tripping. The photovoltaic layer maximizes the output of local photovoltaic power, prioritizing the charging needs of this unit or station. In the energy sharing layer, when the charging and discharging of each unit is unbalanced, cross-unit energy dispatch is carried out through the main bus. Microgrid offline layer, supporting both on-grid and off-grid handover; The load control layer is used for adjusting the power of charging piles; the operation control layer includes: the energy storage response spot layer, the charging station price management layer, and the peak-valley arbitrage layer. Energy storage responds to the spot market: during periods of low prices, electricity is purchased from the grid to charge the energy storage, and during periods of high prices, the discharge peaks. The charging station pricing management system implements dynamic electricity pricing to guide car owners to charge in an orderly manner. Peak-valley arbitrage layer: calculates and controls the optimal proportion of electricity from the power grid during off-peak periods. The value-added control layer is used for network connectivity. It connects to the electricity spot market, virtual power plants, and load aggregation platforms, and receives grid dispatch instructions to respond to demand-side demands.

8. The control method for the coordinated control system of a megawatt-level photovoltaic-storage-charging microgrid according to claim 7, characterized in that, The photovoltaic charging logic is activated only during the effective daytime period determined according to the sunrise and sunset schedule, and is activated after a first preset time delay after sunrise and is deactivated before a second preset time advance before sunset.

9. The control method for the coordinated control system of a megawatt-level photovoltaic-storage-charging microgrid according to claim 7, characterized in that, It also includes intelligent optimization steps: based on the current forecast data, under the constraint of transformer capacity, with the goal of optimizing the economic efficiency of system operation or maximizing photovoltaic absorption, the energy storage charging and discharging plan and the upper limit of bus power are continuously optimized in the next 24 hours.

10. The control method for the coordinated control system of a megawatt-level photovoltaic-storage-charging microgrid according to claim 7, characterized in that, It also includes load control steps: when the system power supply capacity is insufficient, a power reduction or shutdown command is sent to the designated charging pile to ensure system power balance and safety and stability.

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