An energy storage arbitrage, adjustable device electricity optimization and peak shaving auxiliary method based on a power system settlement subject

Abstract

This invention discloses a method for energy storage arbitrage, adjustable equipment power consumption optimization, and peak-shaving assistance based on the power system settlement entity, belonging to the field of distributed power resource dispatching technology. This invention uses the power system settlement entity as the aggregation unit, integrating energy storage devices and adjustable devices to form an adjustable resource pool. Through multi-mode adaptive pricing, data traceability verification, energy storage status protection, continuous smooth power control, and tiered peak-shaving response strategies, it achieves coordinated operation of peak-shaving priority, price arbitrage, and power consumption structure optimization. This invention is based entirely on published objective electricity prices for execution control, without involving price prediction, and ensures revenue certainty through multi-mode guaranteed price difference calculation, while providing full life-cycle protection for energy storage batteries. This invention is applicable to the compliant aggregation and market-oriented operation of small distributed power equipment of 50kW and below, is compatible with various electricity market pricing rules, responds to grid peak-shaving needs, and improves user revenue and system operational stability.

Description

Technical Field

[0001] This invention relates to the field of distributed power resource dispatching technology, specifically to a method for energy storage arbitrage, adjustable equipment power consumption optimization, and peak shaving assistance based on the main body of power system settlement. It is adapted to the multi-mode electricity price rules of the electricity market and achieves the triple objectives of grid peak shaving response, electricity price arbitrage, and power consumption structure optimization for energy storage and adjustable equipment. It is particularly suitable for the large-scale aggregation and market-oriented operation scenarios of small distributed power equipment below 50kW, and corresponds completely to the technical solution protected by the claims. Background Technology

[0002] With the continuous advancement of the construction of new power systems, energy storage technologies and adjustable equipment (such as cold storage, air conditioners, charging piles, water heaters, and industrial flexible loads) are being promoted and applied on a large scale. Small distributed power equipment below 50kW has long been difficult to directly participate in grid peak-shaving and electricity market transactions due to its dispersed layout and small individual capacity.

[0003] Meanwhile, my country's power market reform continues to deepen, and the electricity pricing system exhibits a coexistence of multiple models, including post-trade settlement, day-ahead planning, and real-time rolling clearing. The settlement cycle (T+1, T+2, T+3, etc.) and time granularity (1 minute, 3 minutes, 5 minutes, 15 minutes, etc.) can be dynamically adjusted according to market rules, leading to the following common industry pain points in existing technical solutions: 1. Poor compatibility with compliant access: Small distributed devices struggle to achieve compliant, low-cost aggregated access; 2. Insufficient compatibility with multiple electricity pricing models: Existing solutions are mostly designed for a single electricity pricing model and cannot be compatible with dynamic switching between multiple electricity pricing models; 3. Conflict between peak shaving and arbitrage strategies: The lack of clear priority rules leads to conflicts between the grid's peak shaving needs and users' arbitrage and electricity consumption optimization goals; 4. Lack of a power consumption optimization system: Focusing only on energy storage arbitrage or single equipment dispatch, without incorporating adjustable equipment into the power consumption structure optimization system; 5. High uncertainty of returns: Some schemes rely on electricity price forecasts, resulting in large fluctuations in returns and uncontrollable risks.

[0004] The applicant's earlier patent application (application number: 2026102194396, invention title: A comprehensive demand response control system based on the power system settlement entity) was the first to propose a bottom-level architecture for constructing compliant aggregation and large-scale dispatch of distributed power resources with the power system settlement entity (formerly the power grid electricity bill settlement account number) as the core aggregation unit. This architecture solved the key problems of compliant access and aggregation management of small distributed devices, providing a solid technical foundation for this application.

[0005] This application, as a concretization, practical extension, and optimization of the prior patent, adds collaborative control logic for energy storage devices and adjustable devices, a grid-level peak-shaving response strategy, and integrates multi-mode electricity price adaptation and non-predictive electricity price arbitrage mechanisms under its core framework of "aggregation of power system settlement entities." This forms a complete technical closed loop of "energy storage arbitrage - adjustable device electricity consumption optimization - aggregated peak shaving - market rule adaptation," which is consistent with the technical solution defined in the claims and fills the technical gaps in the prior patent in load coordination, market-based electricity price adaptation, grid peak shaving implementation, and adjustable device electricity consumption optimization.

[0006] Existing technologies still cannot simultaneously solve core issues such as the market-oriented adaptation of energy storage and adjustable resource aggregation and peak shaving, the clear priority of peak shaving and arbitrage, and the protection of equipment lifespan and maximization of revenue. They are difficult to balance grid security, user benefits and sustainable equipment operation, and are fundamentally different from the technical solutions protected by the claims of this application. Summary of the Invention

[0007] The purpose of this invention is to provide a method for energy storage arbitrage, adjustable equipment power consumption optimization, and peak shaving assistance based on the power system settlement entity. This method uses the power system settlement entity as the aggregation unit to achieve all the technical objectives defined in the claims, specifically including: 1. Multi-mode electricity pricing adaptive compatibility (settlement price, day-ahead planned price, real-time price), adapting to dynamic rules of the electricity market; 2. Precise response to tiered peak shaving in the power grid, clearly defining the highest priority of peak shaving instructions, and matching the tiered peak shaving rules in the claims; 3. Coordinated scheduling of energy storage devices and adjustable devices to achieve linkage between energy storage arbitrage and power consumption optimization of adjustable devices; 4. The entire process is based on published objective electricity price data and does not involve electricity price forecasts, ensuring the certainty of revenue, which is consistent with the core limitation of the claims that there is no predictive capability; 5. Balancing user-specific needs with the full lifecycle protection of energy storage equipment, and implementing the multi-level protection strategy outlined in the claims; 6. It addresses industry pain points such as poor adaptability, uncertain returns, and conflicts between peak shaving and arbitrage, forming a compliant, efficient, and sustainable distributed power resource dispatch solution that fully covers the technical scope protected by the claims. Technical solution

[0008] This method uses the power system settlement entity as the basic aggregation unit, integrates energy storage devices and adjustable devices within the unit to form an adjustable resource pool, and performs control based on published objective electricity price signals. It does not involve the prediction, fitting, or extrapolation of future electricity prices, and is compatible with multi-mode electricity prices and dynamic electricity market rules. The specific technical solution corresponds completely to claims 1-14 of the claims, and the steps are as follows:

[0009] Electricity pricing model selection and parameter configuration a. Select an electricity price adaptation mode, wherein the electricity price adaptation mode includes one or more combinations of the following: a settlement price mode with a preset settlement period after the transaction, a day-ahead planned price mode, and a real-time price mode with a preset future time granularity, which is completely consistent with the definition of the electricity price adaptation mode in claim 1; b. The settlement period can be dynamically adjusted according to the electricity market rules, including but not limited to T+1, T+2, and T+3; the time granularity can be dynamically adjusted according to the electricity market rules, including but not limited to 1 minute, 3 minutes, 5 minutes, and 15 minutes, matching the parameter adaptation rules in claims 1 and 5; c. Receive user-preset preference parameters, including: energy storage device parameters (upper limit of charging range, lower limit of discharging range, guaranteed price difference, maximum number of charge / discharge cycles per day, SOC protection threshold); adjustable device parameters (power adjustment threshold, electricity price trigger threshold, device operating condition parameters), which completely correspond to the user-preset parameters in claims 1 and 5; d. Supports users to indirectly configure parameters through standardized package models, reducing operational complexity; e. Adapt parameters according to market rules: the longer the settlement cycle, the larger the historical data sample size; the finer the time granularity, the higher the threshold for the change rate of charging and discharging power, thus implementing the parameter adaptation logic in claims 1 and 5.

[0010] Multi-source data acquisition and traceability verification a. Based on the selected electricity price adaptation mode, obtain the corresponding published electricity price data through the API of a compliant aggregator; b. Verify the qualifications of the entity publishing the electricity price data, the timestamp, and the data signature to ensure the validity of the data, consistent with the data traceability verification requirements in claim 1; c. Real-time acquisition of energy storage device status parameters (SOC, SOH, temperature, DOD, cumulative cycle count), adjustable device consumption data, and grid peak shaving command signals, matching the data acquisition range in claims 1, 7, and 10; d. If the electricity price data is abnormal or interrupted, automatically switch to the locally cached historical electricity price data, implement the network outage self-governance strategy, and implement the boundary processing rules in claim 9.

[0011] Energy storage equipment condition monitoring and protection Real-time monitoring of the energy storage device's state of charge (SOC), temperature, and cumulative cycle count; setting multi-level protection thresholds, which fully correspond to the protection strategies in claims 7 and 12: - Minimum SOC protection threshold: 20%–30%; - Maximum SOC protection threshold: 85%–90%; - SOC upper limit thresholds are adopted for batteries used in secondary applications; Always maintain a 5%–10% reserve capacity; - Dynamically limit the rate of power change based on time granularity to avoid polarization damage; - Dynamically tighten the depth of charge and discharge based on the cumulative number of cycles to extend battery life.

[0012] Establishment of continuous control function Combining electricity price data, energy storage-adjustable device data, grid peak-shaving instructions, and user preference parameters, three types of continuous control functions are established (charging power-electricity price, discharging power-electricity price, and adjustable device operating power-electricity price), which are completely consistent with the control function definitions in claims 1 and 8: The function is a monotonically smooth function (linear / exponential / piecewise smooth), and the power changes smoothly with the electricity price without any abrupt changes. The specific rules are as follows: a. Energy storage devices: Real-time electricity price < charging upper limit → charging power increases smoothly as electricity price decreases; Real-time electricity price > discharging lower limit → discharging power increases smoothly as electricity price increases; Electricity price is between the ranges → energy storage is in standby mode; b. Adjustable equipment: Real-time electricity price < trigger lower limit → high power / full load operation to complete energy / cold / heat storage; Real-time electricity price > trigger upper limit → low power / standby to meet basic needs using stored energy; Electricity price between the range → normal power operation to implement the power optimization logic of the adjustable equipment in claim 8.

[0013] Energy storage and adjustable equipment work together for peak shaving, and arbitrage and power optimization are executed in tandem. Based on the continuous control function and the priority of peak-shaving commands, coordinated control is performed, which is completely aligned with the linkage rules in claims 1, 3, and 4: a. No peak-shaving instructions: Energy storage autonomously executes electricity price arbitrage; adjustable equipment autonomously optimizes electricity consumption structure to generate revenue for users; b. Peak shaving order: The peak shaving order has the highest priority. Energy storage arbitrage and power optimization of adjustable equipment should be suspended immediately, and priority should be given to responding to the grid's peak shaving needs. c. Peak shaving graded response: Level 1 emergency peak shaving (response time ≤ 10s), energy storage discharges at the maximum allowable power, and adjustable equipment operates at the minimum power; Level 2 regular peak shaving (response time ≤ 3min), priority is given to adjusting the load of adjustable equipment, and energy storage is only activated when the adjustment is insufficient, matching the graded peak shaving requirements in claim 3. d. After peak shaving ends: automatically restore energy storage arbitrage and power optimization of adjustable equipment, and implement the priority rules in claim 4.

[0014] Calculation of Guaranteed Price Difference by Model The guaranteed price difference is calculated according to different electricity pricing models to ensure that the arbitrage income of energy storage is positive, which is completely consistent with the calculation rules in claim 6: a. Settlement price model: Guaranteed price difference = Historical average charge-discharge price difference − Energy storage battery single cycle loss cost − Capital occupation cost within the preset settlement period, with the capital occupation cost dynamically calculated based on the settlement period length and current market interest rate; b. Day-ahead planned price model: Minimum price difference = Planned price difference × (1 + Deviation coefficient), the deviation coefficient is dynamically adjusted according to the correction range of the real-time electricity price and the planned electricity price within the day; c. Real-time price mode: The guaranteed price difference is a user-defined value. Discharge arbitrage is only executed when the difference between the current discharge price and the most recent charging price is greater than or equal to the guaranteed price difference.

[0015] Boundary case handling and rule adaptation The boundary handling and rule adaptation logic in claims 1 and 9 is implemented as follows: a. If no charge / discharge / adjustable device energy storage operation is triggered for three consecutive preset time granularity cycles, execute the rollback strategy according to the selected mode, or execute minimum power charge / discharge to avoid long-term battery idleness; b. When communication is interrupted, perform network outage self-governance based on local cached data, and automatically synchronize data and correct the strategy after communication is restored; c. When the preset settlement cycle or preset time granularity of the electricity market is adjusted, the system automatically synchronizes the new rules and updates the parameter adaptation rules, while the core control logic remains unchanged.

[0016] Supporting system description (corresponding to the system limitations in claims 2-14) The execution system corresponding to this method includes six core modules and one extension module, which completely correspond to the system modules and functional limitations in claims 2-14: 1. Aggregation Unit Module: Taking the main body of power system settlement as the unit, it integrates energy storage equipment and adjustable equipment, and uniquely binds them to the power grid electricity bill settlement account number to form an integrated adjustable resource pool of "energy storage-adjustable equipment", which matches the aggregation unit definition in claim 2; 2. Data acquisition and verification module: acquisition frequency ≥ 1 time / second, supports 4G / 5G / Ethernet communication, acquires multi-mode electricity price data and performs traceability verification, automatically switches to local cache when data is abnormal, and implements the module functions in claims 2 and 11; 3. Market rule adaptive module: Automatically identifies and synchronizes the preset settlement cycle and preset time granularity of the electricity market. When the rules are adjusted, only the parameter adaptation rules are updated, while the core logic remains unchanged, corresponding to the rule adaptive requirements in claims 1 and 2. 4. Strategy Calculation Module: Constructs a mode-specific continuous control function, generates energy storage arbitrage, adjustable equipment power consumption optimization and peak shaving collaborative control strategies, clarifies the highest priority of peak shaving commands, supports real-time strategy correction, and matches the strategy calculation logic in claims 2 and 8; 5. Command Issuance Module: Issues smooth charging and discharging power commands to energy storage devices and power adjustment commands to adjustable devices. The command issuance delay is ≤100ms. It supports common communication protocols such as Modbus and CAN bus. It can adjust the slope of the power curve in real time according to the priority of peak shaving commands, thus fulfilling the command issuance requirements in claims 2 and 14. 6. Status monitoring and protection module: Real-time monitoring of the energy storage device's SOC, temperature, and cumulative cycle count; preset multi-level protection thresholds; dynamically adjust the power change rate and SOC protection range to achieve full life cycle protection of the battery, corresponding to the protection functions in claims 2, 7, and 12; 7. Extension Module: Log storage and visualization module, which records operation logs according to the electricity price adaptation mode, and associates them with market rule parameters, peak shaving execution data, energy storage arbitrage income and adjustable equipment power consumption optimization income data to display relevant information to users. It supports users to switch the electricity price adaptation mode with one click, matching the extension module limitation in claim 13. Beneficial effects

[0017] Compared with the prior art, the beneficial effects of the present invention fully correspond to the technical solutions protected by the claims, as follows: 1. Strong compliance and inheritance: It adopts the aggregation logic of the main body of power system settlement, adapts to the standard of exemption from approval and filing for small distributed equipment below 50kW, is consistent with the prior main body patent, forms a complete technical system, and meets the compliance access requirements in claims 1 and 10; 2. Multi-market rule adaptive: compatible with any electricity price mode such as settlement price, day-ahead planned price, and real-time price, and supports dynamic adjustment of settlement cycle (T+1 / T+2 / T+3) and time granularity (1-15 minutes). When the market rules are adjusted, only the parameters are updated, and the core logic remains unchanged, matching the rule adaptation requirements in claims 1 and 9. 3. High efficiency in peak shaving, arbitrage, and power optimization: Clearly define the highest priority of peak shaving instructions, respond to grid peak shaving needs in a tiered manner, and automatically execute energy storage arbitrage and power optimization of adjustable equipment when there is no peak shaving, so as to achieve "peak shaving priority, arbitrage as a backup, and load efficiency improvement", taking into account grid demand and user benefits, and implementing the core logic in claims 1, 3, and 4. 4. High certainty of returns: The entire process is based on published objective electricity price data, without involving electricity price forecasting. The guaranteed price difference is calculated according to different modes, and the battery loss and capital occupation costs are deducted to ensure that the return of each arbitrage operation is positive, which is consistent with the return control limits in claims 1 and 6. 5. Precise Equipment Protection: Through multi-level protection strategies and smooth control functions, the SOC protection range, power change rate and charge / discharge depth of the energy storage equipment are dynamically adjusted, extending the life of the energy storage equipment by more than 20% and implementing the equipment protection rules in claims 7 and 12. 6. Highly adaptable: No additional hardware investment is required; it can be directly deployed on existing smart gateways. It features low command issuance latency, adaptability to real-time control with fine time granularity, extremely simple user operation, support for one-click switching of electricity pricing modes, and complies with the implementation-related limitations in claims 2, 13, and 14. 7. Excellent robustness: It has boundary handling capabilities such as network outage autonomy, data anomaly switching, no operation rollback, and rule self-adaptation, and can still operate stably under complex power grid environment and market rules, corresponding to the boundary handling logic in claim 9. Attached Figure Description

[0018] This invention has the following 8 figures.

[0019] Figure 1 The overall flowchart of the method of this invention is as follows: electricity price mode selection → parameter configuration → data acquisition and traceability verification → equipment status monitoring → continuous control function establishment → peak shaving-arbitrage-electricity optimization linkage execution → sub-mode guaranteed price difference calculation → boundary processing and rule adaptation, including peak shaving instruction priority branch and market rule change adaptation branch, corresponding to the method steps in claim 1. Figure 2 The system architecture diagram of this invention shows the connection relationship and data transmission direction of the aggregation unit module, data acquisition and verification module, market rule adaptive module, strategy calculation module, instruction issuance module, status monitoring and protection module, and extended log storage and visualization module, corresponding to the system architecture in claim 2. Figure 3 : Execution logic diagram of energy storage-adjustable equipment collaborative peak shaving; clarify the triggering conditions, response strategies and switching rules with arbitrage strategies for primary emergency peak shaving and secondary conventional peak shaving, and focus on demonstrating the cost reduction logic of prioritizing the adjustment of adjustable equipment for secondary peak shaving, corresponding to the peak shaving linkage rules in claims 3 and 4; Figure 4 : Comparison chart of continuous control function curves under different modes; showing the charging / discharging power-electricity price smoothing curves under three modes: settlement price, day-ahead planned price, and real-time price, including the curve differences at different time granularities, and also showing the three-segment electricity price response curve of the adjustable device, corresponding to the control function limitation in claim 8; Figure 5 : Multi-level protection logic diagram of energy storage equipment; showing the correlation and adjustment relationship between SOC protection threshold, power change rate limit, reserve capacity retention and cumulative cycle count, corresponding to the equipment protection strategies in claims 7 and 12; Figure 6 : Logic diagram for calculating the minimum price difference in multi-mode electricity pricing; the calculation factors and dynamic adjustment rules for the minimum price difference are shown for each mode, corresponding to the calculation rules in claim 6; Figure 7 The system's visual interface is shown in the diagram. It includes four main sections: mode selection, real-time data, revenue statistics, and equipment status. It supports one-click switching of the electricity price adaptation mode, corresponding to the extended module function in claim 13. Detailed Implementation

[0020] The technical solution of the present invention will be described in detail below in conjunction with specific application scenarios. The embodiments are only used to explain the present invention and are not intended to limit the scope of protection of the present invention. All minor adjustments based on the core logic of the present invention are within the scope of protection of the present invention, and all embodiments strictly match the technical limitations of claims 1-14.

[0021] All embodiments satisfy the core limitations of the claims: the power system settlement entity (grid electricity bill settlement account number) is the aggregation unit, the single capacity of the energy storage device is ≤50kW, it complies with the national and local standards for exemption from approval and filing of distributed energy storage, the entire process is based on published objective electricity price data, does not involve future electricity price prediction, and the peak shaving command is the highest execution priority. Example 1: Practical application of distributed energy storage for daily peak shaving and electricity price arbitrage (pure energy storage)

[0022] This embodiment corresponds to the energy storage arbitrage, peak shaving response, and equipment protection logic in claims 1, 3, 4, 6, 7, and 8. It uses independent energy storage as a typical application scenario, covering all scenarios including off-peak charging, peak discharging, and sudden peak shaving, fully realizing the core demand of "energy storage collaborative control creating value." The daily operation and benefits are as follows:

[0023] Scenario 1: Charging during off-peak hours (2:00 AM - 5:00 AM) When the real-time electricity price of the grid is consistently below 0.3 yuan / kWh (≤ charging limit of 0.35 yuan), the system executes a charging strategy, with the power gradually increasing from 2kW to 5kW as the electricity price decreases, and the SOC increasing from 25% to 65%, storing approximately 15kWh of off-peak electricity, which complies with the smooth control rules in claim 8 and the SOC protection threshold in claim 7.

[0024] Scenario 2: Discharge during peak power hours (8:00-11:00 AM) When the real-time electricity price of the grid rises to above 0.85 yuan / kWh (≥ the lower limit of discharge), the system executes a discharge strategy. The power gradually increases from 2kW to 5kW as the electricity price rises, and the SOC decreases from 65% to 30%, releasing about 17.5kWh of off-peak electricity to achieve peak-valley arbitrage, matching the arbitrage logic in claims 1 and 6.

[0025] Scenario 3: Emergency Level 1 Peak Shift Adjustment (10:15 AM) During the discharge process, the power grid issues a first-level emergency peak-shaving command. The system responds within 8 seconds and immediately increases the discharge power to the maximum allowable power of 5kW until the power grid frequency returns to normal at 10:25. The peak-shaving command ends and the system automatically restores the original discharge strategy. During this period, the system receives power grid peak-shaving subsidies, implementing the tiered peak-shaving and priority rules in claims 3 and 4.

[0026] Scenario 4: Standby during periods of stable electricity prices (12:00-13:00) The real-time electricity price is stable at 0.6 yuan / kWh (between the upper limit of charging of 0.35 and the lower limit of discharging of 0.85), the system remains in standby mode, the energy storage SOC is stable at 30%, and invalid operations are avoided, which complies with the energy storage standby rules in claim 8.

[0027] In this embodiment, the power adjustment is a gradual change in the form of a progress bar, and the SOC is controlled within the protection range of 25%-90% without any step jumps. This achieves the synergistic effect of "peak shaving priority and arbitrage as a backup", which fully matches the core technology limitation of the claims. Example 2: Practical Operation of Power Optimization and Peak Shaving Synergy for Adjustable Equipment (Cold Storage)

[0028] This embodiment corresponds to the adjustable equipment power consumption optimization and peak shaving coordination logic in claims 1, 3, 4, and 8. It takes cold storage as a typical application scenario for adjustable equipment, covering all scenarios of pre-cooling energy storage when electricity prices are low, shutdown for cooling when electricity prices are high, and emergency peak shaving coordination, and fully implements the core requirements of "adjustable equipment power consumption optimization + peak shaving coordination".

[0029] Basic configuration A cold storage facility for cold chain logistics (power system settlement account number: XXX) is equipped with a 50kW refrigeration unit, with an adjustable temperature setting from -18℃ to -22℃. The cold storage walls and goods have a cold storage capacity of 4-6 hours. User preset: • Electricity price trigger threshold: 0.35 yuan / kWh (full-load pre-cooling will occur if the price is below this). • Electricity price trigger threshold: 0.85 yuan / kWh (if the electricity price exceeds this threshold, the unit will be shut down and existing cooling capacity will be utilized). • Normal operating range: 0.35-0.85 yuan / kWh (operating under normal temperature control), matching the adjustable equipment parameters and control rules in claims 1 and 8.

[0030] Pre-cooling energy storage during periods of low electricity prices (2:00 AM - 5:00 AM) With the real-time electricity price consistently below 0.35 yuan / kWh, the system controls the cold storage unit to operate at full load of 50kW, pre-cooling the storage temperature from -18℃ to -22℃. Simultaneously, it utilizes the walls and goods to store approximately 200kWh of cold energy, thus implementing the adjustable equipment power optimization logic in claim 8.

[0031] Electricity prices are operating stably and normally (8:00 AM - 10:00 AM) The real-time electricity price is 0.5-0.6 yuan / kWh (within the normal range). The system controls the cold storage to operate according to the normal temperature control logic. The unit starts and stops intermittently to maintain the storage temperature. The average power is about 20kW, which meets the normal operation rules of the adjustable equipment in claim 8.

[0032] High electricity prices lead to power outages for cooling purposes (3:00 PM - 5:00 PM). When the real-time electricity price rises to 0.9 yuan / kWh (≥ the upper limit threshold of electricity price trigger), the system controls the cold storage unit to shut down and uses the existing cold storage pre-cooled in the early morning to maintain the storage temperature. The storage temperature slowly rises from -22℃ to -18℃. There is no need to start the compressor within 4 hours, saving peak electricity costs and realizing the power optimization of adjustable equipment, matching the core logic in claims 1 and 8.

[0033] Emergency Level II routine peak shaving (3:30 PM) During the shutdown and cooling process, the power grid issues a level-two routine peak-shaving command, and the system responds within 2 minutes. It prioritizes adjusting the cold storage operation strategy—temporarily widening the allowable temperature range of the cold storage to -16℃ to -22℃, extending the usage time of the existing cold storage, while suspending other non-essential loads, smoothing power fluctuations of the aggregation unit, meeting the power grid's peak-shaving needs, and without consuming additional energy storage, thus implementing the level-two peak-shaving rules in claims 3 and 4.

[0034] In this embodiment, the operation of the cold storage unit is highly coordinated with the electricity price throughout the process, realizing the dual value of "adjustable equipment power consumption optimization + peak shaving coordination", which fully complies with the claims' requirements for adjustable equipment control and peak shaving coordination. Example 3: Industry mainstream model – T2 settlement + guidance price + real-time price hybrid pricing model

[0035] This embodiment corresponds to the multi-mode electricity price adaptation, smoothing control, and minimum price difference calculation logic in claims 1, 5, 6, and 8, and is adapted to the mainstream hybrid pricing scenarios in the industry, as detailed below:

[0036] Basic configuration A small industrial and commercial user (electricity system settlement entity account number: XXX) has configured a 50kWh cascaded energy storage battery with a SOC protection range of 25%-90% and always retains 5% reserve capacity. It is compatible with the current mainstream hybrid pricing rules of the power grid, adopts the T2 settlement cycle, uses the grid guidance price as the charging and discharging benchmark, and the 5-minute real-time price as the basis for smooth adjustment. The user has preset a minimum price difference of ≥0.5 yuan / kWh and a power change rate threshold of ≤0.2P credit / 5 minutes (to ensure smoothness without step jumps), which completely corresponds to the parameters, protection, and accounting rules in claims 1, 5, 6, 7, and 8.

[0037] Core pricing and smoothing control rules The grid-guided price sets the upper limit for charging at 0.35 yuan / kWh and the lower limit for discharging at 0.85 yuan / kWh. When the real-time price is consistently lower than or higher than the guided price for 5 minutes, the system gradually adjusts the charging and discharging power every 5 minutes according to the power change rate threshold. When the real-time price fluctuates within ±10% of the guided price, the system maintains stable operation at the current power. All operational revenue is calculated on a T2 settlement cycle, deducting the battery's single-cycle loss cost and capital occupation cost, thus implementing the logic in claims 1, 5, 6, and 8.

[0038] Practical process of pure energy storage granular smoothing in 5 minutes • Low-cost progressive charging (12:00-12:45): Real-time electricity price drops from 0.32 yuan to 0.25 yuan, charging power gradually increases from 2kW to 4kW, and SOC increases from 30% to 56%; • Gradual discharge at higher prices (18:00-18:20): Real-time electricity price increases from 0.88 yuan to 1.0 yuan, discharge power gradually increases from 2kW to 4kW, and SOC decreases from 56% to 45%; • Peak shaving priority interruption and recovery: At 18:20, the power grid issues a level-two routine peak shaving command. The system responds within 3 minutes, increasing the discharge power to 5kW to perform peak shaving. Peak shaving ends 20 minutes later, and the system automatically and smoothly returns to the original discharge strategy. The above processes all comply with the smoothing control and peak-shaving priority rules in claims 3, 4, and 8.

[0039] Implementation effect During the T2 settlement period, pure energy storage achieves a gross arbitrage profit of 32.6 yuan through 5-minute granular gradual charging and discharging. After deducting losses and capital occupation costs, the net profit is 29.8 yuan. With the addition of a peak-shaving subsidy of 25 yuan, the total profit is 54.8 yuan. The power adjustment throughout the process is a gradual change in a progress bar manner, and the SOC rises and falls smoothly, which is fully adapted to the dual needs of grid dispatch and market arbitrage, and matches the core technical objectives of the claims. Example 4: The core strategy pattern of this patent - real-time price pattern (5-minute time granularity)

[0040] This embodiment corresponds to the real-time price mode, smoothing control, and boundary handling logic in claims 1, 6, 8, and 9. It is the practical implementation of the core strategy of this patent, as detailed below:

[0041] Basic configuration A residential user (electricity system settlement entity account number: YYY) has a 50kWh energy storage battery with a SOC protection range of 25%-90% and always retains 5% reserve capacity. The user selects the core real-time price mode of this patent, adapting to the grid's 5-minute real-time electricity price clearing granularity, and adopts a T1 settlement cycle. The user can preset the charging upper limit of 0.33 yuan / kWh, the discharging lower limit of 0.83 yuan / kWh, the guaranteed price difference ≥ 0.5 yuan / kWh, and the power change rate threshold ≤ 0.3P / 5 minutes, ensuring that power adjustments are synchronized and gradual with electricity price fluctuations, consistent with the limitations in claims 1, 5, 6, 7, and 8.

[0042] Core smooth control rules The charging and discharging operations are performed entirely based on the real-time electricity price updated by the power grid every 5 minutes, without a guiding price benchmark; when the real-time electricity price is continuously lower than the upper limit of charging / higher than the lower limit of discharging, the charging / discharging power is increased every 5 minutes according to the power change rate threshold; when the electricity price is stable, the current power is maintained, and when the electricity price falls / declines, the power is gradually reduced according to the threshold; the discharging arbitrage operation is only performed when the price difference between the real-time electricity price and the most recent charging price is greater than or equal to the guaranteed price difference, thus implementing the core rules in claims 1, 6, and 8.

[0043] Practical process of pure energy storage granular smoothing in 5 minutes • Off-peak electricity gradual charging (2:00-2:30 AM): Electricity price drops from 0.3 yuan to 0.22 yuan, charging power gradually increases from 1kW to 4kW, and SOC increases from 30% to 44%; • Peak-gradual discharge (8:00-8:30 AM): Electricity price increases from 0.85 yuan to 1.05 yuan, discharge power gradually increases from 1kW to 4kW, and SOC decreases from 44% to 30%; • No-arbitrage standby phase (14:00-14:15): Electricity price remains stable at 0.6 yuan (between the upper limit of charging and the lower limit of discharging), and the system remains in standby mode; The above process conforms to the smooth control and standby rules in claim 8, without step jumps, thus protecting the energy storage device.

[0044] Implementation effect Under the daily 5-minute real-time price mode, pure energy storage completes one full arbitrage through gradual charging and discharging, achieving a net profit of 12.6 yuan; the power adjustment is smooth and stepless throughout, which is highly consistent with the trend of electricity price fluctuations, fully implementing the core real-time price smoothing strategy of this patent, with certain returns and strong robustness, matching the technical limitations in claims 1, 6, 8, and 9. Supplementary Explanation of Photovoltaic Supporting Energy Storage

[0045] It should be noted that distributed photovoltaic (PV) is one of the typical application scenarios of this invention. PV devices can be coordinated with energy storage devices and adjustable devices to achieve higher returns. When the aggregation unit includes distributed PV, the system can execute various coordinated strategies such as "PV fully connected to the grid via energy storage," "PV fully stored in energy storage," and "PV + energy storage coordinated discharge," which have been fully verified in Example 1. However, PV devices are not a necessary component of this invention. Regardless of whether the unit includes PV, the core control logic of this invention can operate independently, consistent with the limitation of "with energy storage devices and adjustable devices as the core" in claim 1, neither expanding nor narrowing the scope of protection.

Claims

1. A method for energy storage arbitrage, adjustable equipment power consumption optimization, and peak-shaving assistance based on the main body of power system settlement, characterized in that, Using the power system settlement entity as the basic aggregation unit, the method integrates energy storage devices and adjustable devices within the unit to form an adjustable resource pool. The method executes control based on published objective electricity price signals, without involving the prediction, fitting, or extrapolation of future electricity prices, and is compatible with multi-mode electricity pricing and dynamic electricity market rules, including: (1) Select an electricity price adaptation mode, which includes one or more combinations of settlement price mode, day-ahead planned price mode, and real-time price mode; the settlement price mode corresponds to a preset settlement period after the transaction, and the real-time price mode corresponds to a preset time granularity. The settlement period and time granularity can be adaptively adjusted according to the rules of the electricity market; at the same time, for adjustable devices in the aggregation unit, preset power adjustment threshold and electricity price trigger threshold are set to support adaptive adjustment of the power consumption structure optimization strategy of adjustable devices based on electricity price signals. (2) Obtain the corresponding published electricity price data through the API of compliant aggregator, and at the same time collect the status of energy storage equipment, the consumption data of adjustable equipment and the grid peak shaving command signal, and perform source verification on the publishing entity, timestamp and data signature of the electricity price data; (3) Based on the user-preset parameters, combined with electricity price data, equipment operation data and grid peak shaving instructions, establish continuous control functions for charging power-electricity price, discharging power-electricity price, and adjustable equipment operating power-electricity price; the continuous control functions change smoothly with the electricity price without step jumps; (4) Based on continuous control function and priority of peak shaving command, the coordinated control is performed: when there is no peak shaving command, the energy storage device executes the electricity price difference arbitrage strategy, and the adjustable device executes the power consumption structure optimization strategy to provide benefits to customers; when there is a peak shaving command, priority is given to responding to the grid peak shaving demand, so as to realize the linkage execution of peak shaving response, energy storage arbitrage and adjustable device power consumption optimization. (5) When the settlement cycle or time granularity rules of the electricity market are adjusted, the new rules are automatically synchronized and the parameter adaptation strategy is updated, while the core control logic remains unchanged.

2. A power system settlement entity-based energy storage arbitrage, adjustable equipment power consumption optimization, and peak-shaving auxiliary system, characterized in that, For performing the method of claim 1, comprising: (1) Aggregation Unit Module: Taking the main body of power system settlement as the unit, it integrates energy storage equipment and adjustable equipment, and uniquely binds them to the power grid electricity bill settlement account number; (2) Data acquisition and verification module: Collects data on energy storage, adjustable equipment and peak shaving instructions, obtains multi-mode electricity price data through compliant aggregator API, and performs data traceability and legality verification; (3) Market rule adaptive module: automatically identifies and synchronizes the settlement cycle and time granularity rules of the electricity market, and only updates the parameter adaptation strategy when the rules change; (4) Strategy calculation module: Construct sub-mode continuous control functions, generate energy storage arbitrage, adjustable equipment power consumption optimization and peak shaving collaborative control strategies, and set the highest priority of peak shaving instructions; (5) Command issuance module: issues smooth power commands to energy storage devices and adjustable devices, with a command delay of ≤100ms, to adapt to refined real-time control; (6) Status monitoring and protection module: Real-time monitoring of the energy storage device's state of charge (SOC), temperature, and cycle count; preset multi-level protection thresholds; and dynamically adjust the power change rate and SOC protection range.

3. The method according to claim 1, characterized in that, The power grid peak shaving instructions are divided into two priority levels: Level 1 emergency peak shaving and Level 2 routine peak shaving. Level 1 emergency peak shaving response time is ≤10s, and when triggered, it controls the energy storage to discharge at the maximum allowable power. Level 2 routine peak shaving response time is ≤3min, and when triggered, it smooths out the power fluctuations of adjustable equipment and simultaneously adjusts the operating power of adjustable equipment to reduce peak shaving costs.

4. The method according to claim 1, characterized in that, The control priority rule is as follows: the power grid peak shaving command has the highest priority, and the pure energy storage arbitrage and adjustable equipment power consumption optimization strategy are suspended during the execution period; the energy storage arbitrage and adjustable equipment power consumption structure optimization operation are automatically restored after the peak shaving command ends.

5. The method according to claim 1, characterized in that, User-preset parameters include the upper limit of the charging range, the lower limit of the discharging range, the minimum price difference, the maximum number of charge / discharge cycles per day, and the SOC protection threshold. The parameter adaptation rules are: the longer the settlement period, the larger the sample size of historical data analysis; the finer the time granularity, the higher the threshold for the change rate of charging and discharging power.

6. The method according to claim 1, characterized in that, The guaranteed price difference for arbitrage between electricity pricing modes is calculated according to the following rules: (1) Settlement price model: Guaranteed price difference = historical average charge and discharge price difference − energy storage battery single cycle loss cost − capital occupation cost within the settlement period, wherein the capital occupation cost is dynamically calculated based on the preset settlement period length and the current market interest rate; (2) Day-ahead planned price model: guaranteed price difference = planned price difference × (1 + deviation coefficient), the deviation coefficient is dynamically adjusted according to the correction range of the real-time electricity price and the planned electricity price during the day; (3) Real-time price mode: The guaranteed price difference is a user-defined value. Discharge arbitrage operation is only performed when the difference between the current discharge price and the most recent charging price is greater than or equal to the guaranteed price difference.

7. The method according to claim 1, characterized in that, The state parameters of energy storage equipment include state of charge (SOC), state of health (SOH), temperature (T), and depth of discharge (DOD). The preset multi-level protection thresholds are: minimum SOC protection threshold of 20%-30%, maximum protection threshold of 85%-90%, always maintaining 5%-10% of reserve capacity, and using the upper limit of the SOC protection threshold for the secondary use of energy storage batteries.

8. The method according to claim 1, characterized in that, The continuous control function is a monotonic smoothing function, including linear functions, exponential functions, or piecewise smoothing functions: When the real-time electricity price is lower than the upper limit of the charging range, the charging power increases smoothly as the electricity price decreases; When the real-time electricity price is higher than the lower limit of the discharge range, the discharge power increases smoothly as the electricity price increases; When the real-time electricity price is between the upper limit of the charging range and the lower limit of the discharging range, the energy storage device remains in standby mode. For adjustable devices, when the real-time electricity price is lower than the preset lower threshold, the adjustable devices are controlled to operate at high power / full load to complete energy storage; when the real-time electricity price is higher than the preset upper threshold, the adjustable devices are controlled to operate at low power / standby, prioritizing the use of stored energy to meet the basic needs of the devices, thereby optimizing the power consumption structure of the adjustable devices and generating revenue for customers; when the electricity price is within the threshold range, the adjustable devices operate at normal power.

9. The method according to claim 1, characterized in that, It also includes boundary case handling steps: (1) If no charge / discharge operation is triggered for three consecutive preset time granularity cycles, the rollback strategy is executed according to the selected electricity price adaptation mode, or the minimum power charge / discharge is executed to avoid the battery being idle for a long time. (2) When communication is interrupted, the system performs autonomous control based on the local cached historical electricity price data and equipment parameters. After communication is restored, the system automatically synchronizes the data and corrects the control strategy.

10. The method according to claim 1, characterized in that, The energy storage device includes one or more of the following: cascaded lithium batteries, brand-new lithium batteries, and lead-acid batteries. The charging and discharging data of the energy storage device are linked with the electricity consumption data of the power system settlement entity for calculation. The adjustable device is an electrical device with power regulation and energy storage capabilities. Its operating data are linked with the charging and discharging data of the energy storage device and the electricity consumption data of the power system settlement entity for calculation, ensuring accurate calculation of electricity consumption optimization benefits.

11. The system according to claim 2, characterized in that, The data acquisition and verification module acquires data once per second and supports 4G / 5G / Ethernet communication. When the electricity price data is abnormal or interrupted, it automatically switches to the locally cached historical electricity price data to ensure the continuous operation of energy storage arbitrage and power optimization of adjustable equipment.

12. The system according to claim 2, characterized in that, The state monitoring and protection module dynamically adjusts the SOC protection range based on the cumulative number of cycles of the energy storage device. When the number of cycles reaches a preset threshold, the depth of charge and discharge is tightened. At the same time, the power change rate is dynamically limited according to a preset time granularity to avoid battery polarization damage and ensure the stable operation of the energy storage device to continuously realize arbitrage profits.

13. The system according to claim 2, characterized in that, It also includes a log storage and visualization module, which records operation logs according to the electricity price adaptation mode, and associates them with market rule parameters, peak shaving execution data, energy storage arbitrage income and adjustable equipment power consumption optimization income data. It displays peak shaving income, arbitrage income, equipment status and market rule information to users, and supports users to switch the electricity price adaptation mode with one click.

14. The system according to claim 2, characterized in that, The command issuing module supports common communication protocols such as Modbus and CAN bus. It can adjust the slope of the charging and discharging power curve of the energy storage device in real time according to the priority of the grid peak shaving command to ensure the accuracy and smoothness of the response. At the same time, it can issue power adjustment commands to the adjustable device to realize the coordinated control of energy storage arbitrage and power consumption optimization of the adjustable device.

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