Distributed energy management method and system based on double entanglement regulation quantum game

Abstract

This invention provides a distributed energy management method and system based on dual-entanglement controlled quantum game theory. The method includes: collecting real-time data from each distributed unit; initializing the strategy parameters and entanglement strength of each game player; establishing a state mathematical model including power balance, voltage constraints, and energy storage capacity limitations; establishing a quantum game framework; mapping the strategies of each participant to quantum strategy angle parameters; inputting current-moment data into the auxiliary entanglement channel to quickly calculate the optimal output of each device; recalculating the revenue distribution scheme based on historical records and cooperation levels over a long period using the main entanglement channel; dynamically adjusting and updating the entanglement strength based on the results of the two-layer game to form steady-state cooperation; recording scheduling data, transaction results, and entanglement parameters to form a three-layer record system: physical ledger, quantum ledger, and economic ledger; and outputting scheduling instructions and transaction settlement results. This invention achieves synergistic optimization of safe and efficient operation of the power dispatch layer and fair cooperative incentives at the power trading layer.

Description

Technical Field

[0001] This invention relates to the fields of novel power systems and quantum intelligent control technology; in particular, it relates to the fields of energy optimization scheduling and market-based management technology for distributed energy systems; specifically, it relates to a distributed energy management method and system based on dual-entanglement controlled quantum game. Background Technology

[0002] Currently, with the development of distributed energy systems, energy is gradually shifting from centralized supply to a new pattern of multi-point distribution, two-way interaction, and regional self-balancing. Various energy devices, such as photovoltaics, energy storage, and hydrogen energy, have been widely connected to the distribution network, and system operation involves two key business operations:

[0003] First, energy dispatch and operation control, emphasizing the achievement of second-level safe operation under physical constraints such as voltage, frequency, power balance, and energy storage status;

[0004] Second, energy trading and market settlement require different entities to achieve fair returns, long-term cooperation, and decentralized collaboration on time scales ranging from hourly to daily.

[0005] The two types of business have different time response characteristics and optimization goals: the scheduling side pursues "real-time and feasible" while the trading side emphasizes "fairness and incentives". How to take into account both types of needs in the same system has become the core technical challenge of distributed energy management.

[0006] In recent years, quantum game theory has been gradually introduced into the fields of energy management and market optimization due to its unique advantages in expanding the strategy space, improving collaborative efficiency, and stability. Through quantum superposition and entanglement mechanisms, continuous, multi-dimensional game solutions can be generated within a finite strategy space, achieving higher cooperative returns. However, existing quantum game models generally employ a single entanglement protocol, i.e., setting only a fixed entanglement strength parameter ω, whose strategy space and payoff distribution remain unchanged during system operation. This structure has some effectiveness in single-task scenarios (such as market bidding or equipment collaborative control), but it reveals significant limitations in the "schedule-trade integration" scenario of distributed energy systems: when the entanglement strength is high, the system game tends towards a cooperative state, with fair payoff distribution but decreased response speed, making it unsuitable for real-time scheduling; when the entanglement strength is low, the system response is rapid, but the cooperative relationship is fragile, easily leading to payoff deviations and divergent behaviors. Therefore, a single entanglement mechanism cannot simultaneously cover both real-time security and long-term fairness.

[0007] The published patent document CN111062596B, "A Distributed Generation Energy Management Method Based on a Blockchain Dual-Chain Structure," proposed by North China Electric Power University, focuses on constructing a two-layer blockchain structure: a parent chain and a child chain. The parent chain is responsible for cross-regional coordination and transaction settlement, while the child chain is responsible for power dispatching and contract execution within a region. Through a hash anchoring mechanism, data from the child chain is periodically uploaded to the parent chain to form a trusted ledger. The significance of this scheme lies in overcoming the problem of "inability to simultaneously achieve security, decentralization, and dispatching efficiency" in high-concurrency energy management using a single-chain blockchain architecture, enabling parallel operation of dispatching and transactions at different layers. However, its essence remains "layered optimization of the information interaction layer," without addressing the dynamic coordination of decision-making strategies. Although data synchronization is achieved between the dispatching and transaction layers, the lack of strategy evolution and incentive mechanisms prevents adaptive decision-making capabilities.

[0008] The published patent document CN118917690A, "Dynamic Quantum Game Theory Management Method for Low-Carbon Building Decision-Making under the Carbon Trading System," is the first to introduce quantum game theory into the field of dynamic management decision-making. Its method involves: adjusting the strategic coordination of different agents using quantum entanglement parameters; realizing a low-carbon investment and return game through dynamic evolution equations; and capturing the willingness to cooperate at different stages by utilizing changes in the entanglement angle. This participation method demonstrates the potential of quantum game theory in strategy optimization and incentive guidance. However, its model is still a single-entanglement protocol, with the entanglement strength fixed in the same time domain; the system lacks multi-time domain decomposition and does not consider the physical constraints or real-time requirements of the energy system. Therefore, it is suitable for long-term strategy decision-making but not for handling the second-level scheduling problem of distributed energy systems.

[0009] The published patent document CN116385018A, "A Credit Level Evaluation Method Based on Quantum Game Theory Model," achieves multi-factor credit evaluation through quantum superposition and entanglement mechanisms, and improves the decision-making resolution of complex systems by utilizing quantum state superposition. Its core contribution is applying quantum game theory to a multi-agent evaluation mechanism, proving the computational feasibility of quantum policy mapping. However, this scheme is still limited to a single evaluation task and lacks time-domain game regulation or cross-objective dynamic collaboration capabilities.

[0010] The published paper, "Reducing Food Loss and Waste in a Two-Echelon FoodSupply Chain: A Quantum Game Approach" (Journal of Cleaner Production, 2021), introduces quantum game theory into the field of supply chain collaborative governance for the first time. It constructs a two-tier food supply chain model composed of suppliers and retailers to study the interaction mechanism of "effort level—profit distribution—cooperation stability." Its innovations lie in: expanding the strategy space through a non-zero-sum quantum game model; introducing quantum superposition and entanglement parameters to describe the continuous strategy state between "full effort—no effort"; discovering the risk that "the effortr bears the loss of the betrayer" in classical games, while under maximum entanglement conditions, the loss is borne by the non-effortrendering party, thus achieving systematic Pareto optimality; and further proposing an "entanglement contract" to ensure no deviation incentives for either party by adjusting the entanglement angle.

[0011] This research lays the theoretical foundation for the idea that "quantum entanglement can improve cooperative equilibrium," and is inspiring for subsequent quantum game modeling in fields such as energy and construction. However, its model assumes that all participants are on the same time scale and lacks description of multi-time-domain cooperation and physical constraint feedback (such as energy conservation and real-time scheduling). Therefore, it is only applicable to the abstract level of cooperative evolution analysis and is difficult to directly support the dynamic operation decision-making of power and energy systems.

[0012] The published paper, "Reducing Betrayal Behavior in Green Building Construction: A Quantum Game Approach" (Journal of Cleaner Production, 2024), applies quantum game theory to suppress betrayal behavior in the green building construction supply chain. The paper uses developers and contractors as the two main actors, constructing an extended model from classical non-zero-sum games to quantum strategy space. The core idea is to describe the trust strength between developers and contractors using quantum entanglement angles, and to characterize the continuous cooperative state between "full effort" and "no effort" using quantum superposition states. It proves that in classical games, the party making full effort bears all the risk, while under maximum entanglement conditions, the loss is borne by the party not making effort, prompting both parties to favor the full effort strategy. Finally, it proposes an "entanglement treaty" as a constraint mechanism to ensure that neither party has an incentive to betray, thus achieving stable cooperation in the construction supply chain.

[0013] The contribution of this approach lies in extending quantum game theory from economic games to the field of engineering project management, verifying the governance role of quantum entanglement in multi-stakeholder collaboration. However, its research still belongs to a single-time-domain game model, failing to distinguish the strategic differences between the construction and operation phases, and also neglecting the real-time control-market settlement linkage mechanism of energy systems. Therefore, while this achievement has reference value for cooperative incentive mechanisms, it still has structural shortcomings in dealing with the "schedule-trading two-layer collaboration" problem of complex energy systems.

[0014] The aforementioned literature indicates that quantum game theory has gradually expanded from the field of socio-economic decision-making to the fields of engineering management and resource optimization. Its common characteristics include utilizing quantum superposition to achieve continuous strategy expression, employing entanglement mechanisms to enhance cooperative stability, and adjusting the distribution of game payoffs through quantum angle parameters. However, these studies generally suffer from the following two limitations:

[0015] Limited time scale: Game modeling focuses on strategy evolution and lacks multi-time domain decomposition and dynamic control mechanisms;

[0016] Lack of physical constraints: Ignoring engineering constraints such as energy conservation, voltage stability, and real-time response makes it difficult to support the operation of actual energy systems.

[0017] In summary, distributed energy systems simultaneously address the self-balancing consumption of local energy and multi-entity trading in the electricity market. The former emphasizes real-time response to physical constraints such as voltage, power, and energy storage, while the latter focuses on fair trading, stable returns, and long-term cooperation. The two are inherently conflicting in terms of temporal characteristics and goal orientation.

[0018] Quantum game theory, with its advantages of expanding the strategy space and strengthening cooperative incentives, has been applied to collaborative decision-making in distributed energy resources. However, existing quantum game models generally employ a single entanglement protocol with fixed entanglement strength, failing to simultaneously address the different needs of second-level scheduling and hourly-level transactions. In practical operation, increasing entanglement strength to pursue long-term cooperation leads to delayed scheduling response and reduced feasibility; conversely, decreasing entanglement strength to improve real-time performance results in fragile cooperative relationships and unbalanced benefit distribution, creating a technical bottleneck where scheduling and transactions are incompatible. Summary of the Invention

[0019] Therefore, the purpose of this invention is to develop a distributed energy management method and system based on dual-entanglement controlled quantum game theory. The invention proposes a dual-entanglement controlled quantum game mechanism, setting up an auxiliary entanglement channel and a primary entanglement channel. The auxiliary entanglement channel is used for real-time scheduling, controlling the low-latency entanglement strength to ensure rapid system stability under physical boundaries such as power balance, voltage safety, and SoC constraints. The primary entanglement channel is used for market transactions, controlling the high-expression entanglement strength to achieve fair returns and cooperative incentives. The two entanglement channels are dynamically coordinated by an entanglement control manager, automatically adjusting the entanglement strength and strategy angle parameters during system operation to optimize scheduling and transactions within their respective time domains and maintain global consistency. This simultaneously improves the scheduling security, response efficiency, and cooperative fairness of the distributed energy system, solving the core problem in existing quantum game models that cannot simultaneously handle real-time scheduling and market transactions. Achieving temporal separation of entanglement intensity in the scheduling-trading two-layer structure: thereby overcoming the limitation of existing quantum game models that "cooperative incentives and dynamic responses are difficult to balance", and providing a new path for multi-objective coordination in energy systems; for multi-energy coupling scenarios such as photovoltaic, energy storage, and hydrogen energy, achieving coordinated optimization of safe and efficient operation of the power scheduling layer and fair cooperative incentives of the power trading layer.

[0020] This invention provides a distributed energy management method based on dual-entanglement controlled quantum game, comprising the following steps:

[0021] S1. Collect real-time data from each distributed unit, including photovoltaic output, energy storage power, voltage, current and market price, and initialize the strategy parameters and entanglement strength of each game subject (such as power source, energy storage and user).

[0022] S2. Based on voltage, current, and SoC energy storage state information, establish a state mathematical model of system operation that includes power balance, voltage constraints, and energy storage capacity limitations; establish a quantum game framework that includes an auxiliary entangled channel for real-time scheduling control and a main entangled channel for executing market transactions.

[0023] Specifically, the auxiliary entanglement channel (corresponding to real-time scheduling) is responsible for power allocation, frequency support, and voltage control at the second to minute level; the main entanglement channel (corresponding to market trading) is responsible for profit allocation, reputation maintenance, and long-term cooperation at the hour to day level. The two entanglement channels are interconnected but have different functions.

[0024] In distributed energy systems, "real-time scheduling" and "market trading" are considered two different types of decision problems. The former requires rapid response and is subject to physical constraints, while the latter requires fairness and sustainability. To address this, this invention proposes a dual-entanglement control quantum game mechanism, which sets up an auxiliary entanglement channel and a primary entanglement channel. The auxiliary entanglement channel is used for real-time scheduling, controlling the low-latency entanglement strength to ensure rapid system stability under physical boundaries such as power balance, voltage safety, and SoC constraints. The primary entanglement channel is used for market trading, controlling the high-expression entanglement strength to achieve fair returns and cooperative incentives.

[0025] S3. Map the strategies (such as output level, bidding strategy, etc.) of each participant in the game (such as power source, energy storage, users) to quantum strategy angle (μ,β) parameters; the two entangled channels use different quantum operators to represent the entanglement relationship: the auxiliary entanglement operator is used for low-latency calculation and responds to real-time changes; the main entanglement operator is used for high-precision calculation and considers long-term incentives and reputation.

[0026] S4, the auxiliary entanglement channel (scheduling layer) uses the data at the current moment as input to calculate the optimal output of each device; when voltage fluctuations or over-limit risks occur, the entanglement control and management device reduces the auxiliary entanglement strength, reduces the strategy coupling degree, and ensures the independent feasibility of each device and the stability of the system;

[0027] S5. The main entanglement channel (trading layer) recalculates the profit distribution plan based on historical records and cooperation levels over a long period. If a participant is found to deviate from the agreed strategy, the quantum contract mechanism is triggered to automatically adjust the participant's profit weight or reputation coefficient to prevent free-riding or malicious speculation and maintain a long-term cooperative relationship.

[0028] S6. The entanglement control and management device dynamically adjusts and updates the entanglement strength based on the results of the two-layer game. If unstable frequency or voltage operating indicators are detected, the auxiliary entanglement parameters are tightened; if a decrease in cooperative fairness is found, the main entanglement parameters are increased. Through continuous adjustment, a steady-state cooperation is gradually formed during operation.

[0029] S7 records scheduling data, transaction results, and entanglement parameters to form a three-layer recording system of physical ledger, quantum ledger, and economic ledger; it outputs scheduling instructions and transaction settlement results while updating the three-layer recording system.

[0030] Specifically, the physical ledger records real-time scheduling data; the quantum ledger records entanglement parameters and strategy evolution; and the economic ledger records revenue, reputation, and contract execution status.

[0031] Furthermore, the method for establishing a state mathematical model of system operation, including power balance, voltage constraints, and energy storage capacity limitations, in step S2 includes:

[0032] S21. Establish a unified objective function based on minimizing the scheduling cost of output:

[0033] ;

[0034] Where t and T are the time period index and the total number of time periods, respectively;

[0035] Let be the output of the i-th conventional generator during time period t;

[0036] Let i be the operating cost function of generator i; it is usually a quadratic function. ,in , , It is a cost coefficient that reflects the consumption characteristics of the generator;

[0037] Let be the active power of the j-th energy storage system during time period t; a positive value indicates discharging, and a negative value indicates charging.

[0038] The cost of energy storage operation losses; related to charging and discharging power and cycle life, converting physical losses into economic costs;

[0039] This represents the amount of electricity wasted by the k-th renewable energy source (such as photovoltaics) during time period t.

[0040] The penalty cost for curtailing solar / wind power; that is, to encourage the consumption of renewable energy, an economic penalty is imposed on the wasteful portion of it.

[0041] This refers to the total installed power generation capacity.

[0042] The number of energy storage systems;

[0043] This refers to the installed capacity of renewable energy.

[0044] S22. Establish power balance constraints, including active power balance constraints and reactive power balance constraints;

[0045] The expression for the active power balance constraint is:

[0046] ;

[0047] The expression for the reactive power balance constraint is:

[0048] ;

[0049] in, Let k be the maximum available active power of renewable energy source k during time period t;

[0050] Total active power load;

[0051] The total active power loss is implicitly determined by the subsequent power flow equations;

[0052] This refers to the number of reactive power compensation devices;

[0053] Let be the reactive power generated by generator i during time period t;

[0054] The reactive power provided by the m-th reactive power compensation device (such as a capacitor or SVG) during time period t;

[0055] Total reactive load;

[0056] The total reactive power loss is determined by the power flow equations, which are expressed as follows:

[0057] For any node i (participant):

[0058] ,

[0059] ;

[0060] in, , These are the net active power and net reactive power injected into node i, respectively;

[0061] , These are the voltage magnitudes at nodes i and j, respectively;

[0062] The voltage phase angle difference between nodes i and j;

[0063] , Let be the element in the i-th row and j-th column of the nodal admittance matrix. , These are the real part and the imaginary part, representing the topology and parameters of the power grid, respectively.

[0064] S23. Establish the relationship constraints between active power frequency regulation and reactive power voltage regulation. The expression for active power frequency regulation is:

[0065] ;

[0066] in, Frequency deviation (unit: Hz) , 50Hz;

[0067] The load frequency damping coefficient (unit: MW / Hz) represents the degree to which the load power naturally changes with frequency.

[0068] This represents the change in mechanical power, specifically the change in the input power of a prime mover (such as a steam turbine or a water turbine).

[0069] This represents the load power variation, specifically the random fluctuations in the active power of the user load.

[0070] Specifically, the reactive power regulation can be precisely controlled in the second formula of the power flow equation.

[0071] S24. Establish constraints for the energy storage system. The energy storage state equation is:

[0072] ;

[0073] in, The state of charge of energy storage j at the beginning of time period t, ranging from 0 to 1;

[0074] , denoted as the charging and discharging active power of energy storage j during time period t, respectively; both are non-negative values. , and The variable relationships are as follows:

[0075] ;

[0076] in, The rated capacity of energy storage j;

[0077] , These are the charging and discharging efficiencies of energy storage j, respectively, both of which are less than 1;

[0078] The duration of each time period;

[0079] The expression to prevent overcharging and over-discharging is: ;

[0080] The maximum charging power is: ;

[0081] The upper limit of discharge power is: ;

[0082] The expression for mutual exclusion between charge and discharge states is: ;

[0083] S25. Establish safety thresholds, including: frequency threshold and voltage threshold;

[0084] The frequency threshold 0.2Hz;

[0085] The voltage threshold .

[0086] Furthermore, the method for mapping the strategies of each participant in the game to quantum policy angle parameters in step S3 includes:

[0087] The core strategy of the participants is their level of contribution. and market quotes The output level and market quotes The quantization mapping is as follows:

[0088] Output level strategy angle :

[0089] ;

[0090] in, The rated output of the participating party;

[0091] Market pricing strategy angle :

[0092] ;

[0093] in, As the market benchmark price, This is the highest bid.

[0094] Specifically, the output level strategy angle Describe the real-time output adjustment intentions of the distributed units. ∈[0, π / 2]; When the value is 0, the output is 0. When the output reaches the rated value, the output power is equal to π / 2.

[0095] Market pricing strategy angle This reflects the aggressiveness of the bid; the higher the bid is above the benchmark price, the more aggressive the strategy.

[0096] The quantum state of a single participant is represented as:

[0097] Note the difference between the imaginary unit i and the participant / node i in the formula.

[0098] Furthermore, the quantum contract mechanism of step S5 includes:

[0099] S51, Hamiltonian in the main entanglement channel In the design contract items This makes the contract terms part of the game rules:

[0100] ;

[0101] in, It is the Hamiltonian that dominates the game at the transaction layer;

[0102] It is a contractual item, and its inherent meaning is to punish non-cooperative behavior;

[0103] S52. Set the key parameters and automatic execution process of the contract mechanism, wherein the key parameters include:

[0104] Cooperation Benchmark : Represents a conservative, cooperative pricing tendency, and is set as a negative value; for example 0.5;

[0105] Strategy Observation : indicates the final state of the game The expected value of the participants' bidding strategy is obtained through multiple measurements. This value is a positive indicator; the larger the value, the more aggressive the bidding.

[0106] Contract strength : Indicates the severity of the penalty, which is a dynamic parameter; the contract strength. The update rules are as follows:

[0107] ;

[0108] in, This represents the contract strength after the previous iteration; it indicates that if a participant continues to deviate from the cooperation benchmark, the contractual penalty against it will automatically and gradually increase in subsequent games.

[0109] S53. Determine the payoff weights in quantum games by calculating the final payoff weights of the participants based on the measurement results of the final quantum state:

[0110] ,

[0111] ;

[0112] in, It is a revenue weighting operator;

[0113] It is the unit operator;

[0114] This is the baseline weight (e.g., 1);

[0115] It is the contract impact coefficient (negative value, such as -0.3);

[0116] The actual benefit to the participants after settlement through the quantum contract mechanism;

[0117] The theoretical profit that participants should receive according to classic market rules;

[0118] By embedding the calculation of payoff weights into the quantum measurement process, when the measurement results show that a participant's strategy deviates from the cooperation benchmark, the participant's payoff weight will be automatically reduced, thereby directly reducing its actual payoff.

[0119] The contract influence coefficient in the above formula With a reputation coefficient CR based on long-term performance i Binding fusion (e.g.) ∝CR i This allows participants with high credibility to receive higher reward bonuses for their cooperative behavior, thus achieving long-term incentives.

[0120] This invention utilizes quantum contracts to resolve the potential conflict between secure operation and cooperative settlement. When a system issues a warning or relevant parameters exceed a safety threshold, the coupling between participants is reduced by lowering the secondary entanglement strength parameter, allowing for independent operation and ensuring device safety. However, this leads to a decrease in the level of cooperation among participants. Therefore, a "quantum contract" is introduced in the main entanglement channel (transaction layer) to promote cooperation among participants.

[0121] Furthermore, the monitoring index system used in step S6 to dynamically adjust and update the entanglement strength based on the results of the two-layer game includes:

[0122] Based on two types of indicators: quantum game theory indicators and classical operational indicators, the quantum game theory indicators (reflecting the state of cooperation) include:

[0123] Quotation Consistency Index C β This measures the average deviation of each participant's pricing strategy from the cooperation benchmark; the larger the value, the worse the system's cooperation. The expression is:

[0124] ;

[0125] Quotation Coordination Q β This measure the strength of the quantum correlation between the bidding strategies of different participants; the lower the value, the less synergy there is between the strategies, indicating a tendency for each to act independently. The expression is:

[0126] ;

[0127] The number of market participants in the system;

[0128] Cooperation payoff ratio R: This is the ratio of the expected payoffs to the system from a cooperative strategy to a non-cooperative strategy. A lower value indicates a smaller advantage from cooperation. The expression is:

[0129] ;

[0130] The classic operational indicators (reflecting physical security) include:

[0131] Frequency deviation Δf: The deviation between the actual system frequency and the rated value;

[0132] Voltage over-limit severity V violation : Quantify the degree to which the voltage of each node deviates from the safe range.

[0133] Furthermore, the adjustment rules used in step S6 to dynamically adjust and update the entanglement strength based on the results of the two-layer game include: rules for adjusting the secondary entanglement strength. The principle of safety first, used to adjust the main entanglement strength The principle of cooperation and adaptation;

[0134] The triggering condition for the safety priority principle is: when the frequency deviation Δf > 0.1Hz or the voltage over-limit severity V violation A value greater than 0.02 pu indicates that the system faces a safety risk; (These are trigger thresholds set for preventative control strategies, providing sufficient response time and safety margin for the control system to prevent deviations from further expanding into dangerous areas and resulting in insufficient response time.)

[0135] The adjustment action triggered under the safety priority principle is: immediately reduce the secondary entanglement strength. The decrease is proportional to the severity of the safety risk, and the adjusted and updated auxiliary entanglement strength is:

[0136] ;

[0137] in, To adjust the secondary entanglement strength before the update;

[0138] Specifically, adjust the secondary entanglement strength The control logic is: reduce This effectively weakens the coupling between the strategies of each unit in the scheduling game, prompting them to act quickly and independently based on local information, prioritizing system security. Simultaneously, it increases the weight of the physical constraint term in the Hamiltonian of the scheduling layer game, further strengthening the security orientation.

[0139] The trigger condition for the cooperative adaptation principle is: when the quotation consistency index C β Greater than a certain empirical value, and the degree of price coordination Q β When the cooperation benefit ratio R is less than a certain empirical value, it indicates that the cooperativeness of the system is deteriorating.

[0140] The adjustment action triggered by the cooperative adaptation principle is: increase the main entanglement strength. The increase is related to the degree of deterioration in cooperation, and the adjusted and updated main entanglement strength is:

[0141] .

[0142] Specifically, adjust the main entanglement strength The control logic is: increase This effectively strengthens the quantum correlation between the strategies of each participant in the trading game, making cooperative strategies more likely to gain an advantage. Simultaneously, the governance mechanism will enhance the strength of the quantum contract, imposing harsher intrinsic penalties on non-cooperative behavior.

[0143] When security risks and cooperation crises occur simultaneously, the governance mechanism adheres to the principle of absolute security priority:

[0144] Implement adjustments to the auxiliary channel immediately to ensure system stability.

[0145] The adjustments to the main channel will be temporarily suspended, and the duration of cooperation temporarily sacrificed to ensure safety will be recorded.

[0146] Post-event compensation: Once the system has stabilized, if the duration of cooperation sacrifice exceeds a preset threshold, the administrator will automatically trigger a compensation mechanism, such as appropriately lowering the contract strength of the relevant participants and providing the set reputation compensation to maintain their long-term cooperation enthusiasm.

[0147] Furthermore, the trigger thresholds for the security priority principle and the cooperation adaptation principle are dynamically generated by the entanglement strength manager. The method for generating the trigger thresholds includes: the entanglement strength manager continuously collects real-time data of each indicator in the quantum game index and the corresponding system cooperation state, accumulating it into a multi-scenario experience pool. After the sample size reaches the target, the inflection point of the cooperation state transition in the data is analyzed, and the data value of the inflection point is used as the initial threshold. Subsequently, the threshold is iteratively updated in combination with new data so that the threshold always adapts to the actual cooperation characteristics of the current system.

[0148] This invention also provides a distributed energy management system based on dual-entanglement controlled quantum game theory, for executing the distributed energy management method based on dual-entanglement controlled quantum game theory as described above, including:

[0149] Data acquisition module: used to collect real-time data from each distributed unit, including photovoltaic output, energy storage power, voltage and current, and market price, and to initialize the strategy parameters and entanglement strength of each game subject;

[0150] State modeling module: used to establish a mathematical model of system operation based on voltage, current, and SoC energy storage state information, including power balance, voltage constraints, and energy storage capacity limits; and to establish a quantum game framework including an auxiliary entangled channel for real-time scheduling control and a main entangled channel for executing market transactions.

[0151] The quantum strategy mapping module is used to map the strategies of each participant in the game to quantum strategy angle parameters; the two entangled channels use different quantum operators to represent the entanglement relationship: the auxiliary entanglement operator is used for low-latency calculation and responds to real-time changes; the main entanglement operator is used for high-precision calculation and considers long-term incentives and reputation.

[0152] The auxiliary entanglement game module is used to calculate the optimal output of each device by taking the current data as input. When voltage fluctuations or over-limit risks occur, the entanglement control and management module reduces the auxiliary entanglement strength and reduces the strategy coupling.

[0153] Main Entanglement Game Module: Used by the main entanglement channel to recalculate the profit distribution scheme based on historical records and degree of cooperation over a long period; if a participant is found to deviate from the agreed strategy, the quantum contract mechanism is triggered to automatically adjust the participant's profit weight or reputation coefficient.

[0154] Entanglement Control and Governance Module: This module is used by the entanglement control and governance unit to dynamically adjust and update the entanglement strength based on the results of the two-layer game. If unstable frequency or voltage operating indicators are detected, the auxiliary entanglement parameters are tightened; if a decrease in cooperative fairness is detected, the main entanglement parameters are increased. Through continuous adjustment, a steady-state cooperation is gradually formed during operation.

[0155] Ledger Settlement Module: Used to record scheduling data, transaction results, and entanglement parameters, forming a three-layer recording system of physical ledger, quantum ledger, and economic ledger; outputs scheduling instructions and transaction settlement results, and updates the three-layer recording system at the same time.

[0156] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the distributed energy management method based on dual-entanglement controlled quantum game as described above.

[0157] The present invention also provides a computer device, the computer device including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the steps of the distributed energy management method based on dual entanglement-controlled quantum game as described above.

[0158] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0159] The distributed energy management method and system based on dual-entanglement-controlled quantum game theory provided by this invention, compared with existing energy management methods based on blockchain or single quantum entanglement, is no longer limited to hierarchical optimization at the information layer, but directly introduces a dual-entanglement control structure at the decision-making level. Through the time-domain collaboration of the main and auxiliary entangled channels, the system can respond quickly to power fluctuations on a second-level timescale and maintain market cooperation on an hour-level scale, achieving a unity of scheduling security and transaction fairness. This solves the problem that existing methods cannot simultaneously address real-time scheduling and long-term cooperation within the same framework. The introduction of an entanglement control manager gives the system adaptive capabilities, solving the problem that the entanglement strength of traditional quantum game models cannot be adjusted according to the operating state, leading to strategy imbalance in extreme cases. The entanglement control manager can adjust the entanglement strength according to voltage, frequency, and other parameters. The system automatically adjusts the primary and secondary entanglement parameters based on indicators such as rate of return and profit deviation, thereby dynamically balancing security and economy and improving the overall stability and robustness of the system. It proposes a quantum contract mechanism to solve the problems of "cooperation easily collapses and incentives are not sustainable" in existing game theory models. By binding entanglement parameters to profit distribution, when an individual deviates from the cooperation strategy, the profit automatically decreases, protecting the cooperating parties and forming an endogenous constraint and incentive mechanism. This "automatic correction-continuous incentive" characteristic enables the distributed energy system to maintain a high level of coordination and fairness in long-term operation, significantly outperforming existing solutions that rely solely on static game theory. It is suitable for industry applications such as integrated energy microgrids, virtual power plants, and regional energy management platforms, and can achieve synergistic optimization of safe and efficient operation at the power dispatch layer and fair cooperative incentives at the power trading layer. Attached Figure Description

[0160] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0161] In the attached diagram:

[0162] Figure 1 This is a flowchart of a distributed energy management method based on dual-entanglement controlled quantum game, according to an embodiment of the present invention.

[0163] Figure 2This is a schematic diagram of the architecture of a distributed energy management system based on dual-entanglement controlled quantum game according to an embodiment of the present invention;

[0164] Figure 3 This is a schematic diagram of the configuration of a computer device according to an embodiment of the present invention. Detailed Implementation

[0165] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and products consistent with some aspects of this disclosure.

[0166] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used herein are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0167] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this disclosure, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0168] The embodiments of the present invention will be described in further detail below.

[0169] This invention provides a distributed energy management method based on dual-entanglement controlled quantum game theory. (See also...) Figure 1 As shown, it includes the following steps:

[0170] S1. Collect real-time data from each distributed unit, including photovoltaic output, energy storage power, voltage, current and market price, and initialize the strategy parameters and entanglement strength of each game subject;

[0171] S2. Based on voltage, current, and SoC energy storage state information, establish a state mathematical model of system operation that includes power balance, voltage constraints, and energy storage capacity limitations; establish a quantum game framework that includes an auxiliary entangled channel for real-time scheduling control and a main entangled channel for executing market transactions.

[0172] The auxiliary entanglement channel is responsible for power allocation, frequency support, and voltage control at the second to minute level; the main entanglement channel is responsible for revenue allocation, reputation maintenance, and long-term cooperation at the hour to day level.

[0173] This embodiment sets up a primary entanglement channel and a secondary entanglement channel, corresponding to the transaction layer and scheduling layer in the distributed energy system, respectively. The secondary entanglement is used for second-level power allocation and operational safety control, while the primary entanglement is used for hour-level revenue allocation and cooperative incentives. The two are dynamically coordinated under the action of the entanglement control and governance device, thereby taking into account both real-time feasibility and long-term fairness in the same system.

[0174] Methods for establishing state mathematical models of system operation that include power balance, voltage constraints, and energy storage capacity limitations include:

[0175] S21. Establish a unified objective function based on minimizing the scheduling cost of output:

[0176] ;

[0177] Where t and T are the time period index and the total number of time periods, respectively;

[0178] Let be the output of the i-th conventional generator during time period t;

[0179] Let be the operating cost function of generator i; It is a quadratic function ,in , , It is a cost coefficient that reflects the consumption characteristics of the generator;

[0180] Let be the active power of the j-th energy storage system during time period t; a positive value indicates discharging, and a negative value indicates charging.

[0181] The cost of energy storage operation losses; related to charging and discharging power and cycle life, converting physical losses into economic costs;

[0182] This represents the amount of electricity wasted by the k-th renewable energy source (such as photovoltaics) during time period t.

[0183] The penalty cost for curtailing solar / wind power; that is, to encourage the consumption of renewable energy, an economic penalty is imposed on the wasteful portion of it.

[0184] This refers to the total installed power generation capacity.

[0185] The number of energy storage systems;

[0186] This refers to the installed capacity of renewable energy.

[0187] S22. Establish power balance constraints, including active power balance constraints and reactive power balance constraints;

[0188] The expression for the active power balance constraint is:

[0189] ;

[0190] The expression for the reactive power balance constraint is:

[0191] ;

[0192] in, Let k be the maximum available active power of renewable energy source k during time period t;

[0193] Total active power load;

[0194] The total active power loss is implicitly determined by the subsequent power flow equations;

[0195] This refers to the number of reactive power compensation devices;

[0196] Let be the reactive power generated by generator i during time period t;

[0197] The reactive power provided by the m-th reactive power compensation device (capacitor, SVG) during time period t;

[0198] Total reactive load;

[0199] The total reactive power loss is determined by the power flow equations, which are expressed as follows:

[0200] For any node i (participant):

[0201] ,

[0202] ;

[0203] in, , These are the net active power and net reactive power injected into node i, respectively;

[0204] , These are the voltage magnitudes at nodes i and j, respectively;

[0205] The voltage phase angle difference between nodes i and j;

[0206] , Let be the element in the i-th row and j-th column of the nodal admittance matrix. , These are the real part and the imaginary part, representing the topology and parameters of the power grid, respectively.

[0207] S23. Establish the relationship constraints between active power frequency regulation and reactive power voltage regulation. The expression for active power frequency regulation is:

[0208] ;

[0209] in, Frequency deviation (unit: Hz) , 50Hz;

[0210] The load frequency damping coefficient (unit: MW / Hz) represents the degree to which the load power naturally changes with frequency.

[0211] This represents the change in mechanical power, specifically the change in the input power of a prime mover (such as a steam turbine or a water turbine).

[0212] This represents the load power variation, specifically the random fluctuations in the active power of the user load.

[0213] S24. Establish constraints for the energy storage system. The energy storage state equation is:

[0214] ;

[0215] in, The state of charge of energy storage j at the beginning of time period t, ranging from 0 to 1;

[0216] , denoted as the charging and discharging active power of energy storage j during time period t, respectively; both are non-negative values. , and The variable relationships are as follows:

[0217] ;

[0218] in, The rated capacity of energy storage j;

[0219] , These are the charging and discharging efficiencies of energy storage j, respectively, both of which are less than 1;

[0220] The duration of each time period;

[0221] The expression to prevent overcharging and over-discharging is: ;

[0222] The maximum charging power is: ;

[0223] The upper limit of discharge power is: ;

[0224] The expression for mutual exclusion between charge and discharge states is: ;

[0225] S25. Establish safety thresholds, including: frequency threshold and voltage threshold;

[0226] The frequency threshold 0.2Hz;

[0227] The voltage threshold .

[0228] S3. Map the strategies (output levels, bidding strategies, etc.) of each participant in the game (power source, energy storage, users, etc.) to quantum strategy angle (μ, β) parameters; the two entangled channels use different quantum operators to represent the entanglement relationship: the auxiliary entanglement operator is used for low-latency calculation and responds to real-time changes; the main entanglement operator is used for high-precision calculation and considers long-term incentives and reputation.

[0229] Methods for mapping the strategies of each player in a game to quantum policy angle parameters include:

[0230] The core strategy of the participants is their level of contribution. and market quotes The output level and market quotes The quantization mapping is as follows:

[0231] Output level strategy angle :

[0232] ;

[0233] in, The rated output of the participating party;

[0234] Market pricing strategy angle :

[0235] ;

[0236] in, As the market benchmark price, This is the highest bid.

[0237] Output level strategy angle Describe the real-time output adjustment intentions of the distributed units. ∈[0, π / 2]; When the value is 0, the output is 0. When the output reaches the rated value, the output power is equal to π / 2.

[0238] Market pricing strategy angle This reflects the aggressiveness of the bid; the higher the bid is above the benchmark price, the more aggressive the strategy.

[0239] S4, the auxiliary entanglement channel (scheduling layer) uses the data at the current moment as input to calculate the optimal output of each device; when voltage fluctuations or over-limit risks occur, the entanglement control and management unit reduces the auxiliary entanglement strength and reduces the strategy coupling degree;

[0240] S5. The main entanglement channel (trading layer) recalculates the profit distribution plan based on historical records and cooperation levels over a long period. If a participant is found to deviate from the agreed strategy, the quantum contract mechanism is triggered to automatically adjust the participant's profit weight or reputation coefficient to prevent free-riding or malicious speculation and maintain a long-term cooperative relationship.

[0241] Quantum contract mechanisms include:

[0242] S51, Hamiltonian in the main entanglement channel In the design contract items This makes the contract terms part of the game rules:

[0243] ;

[0244] in, It is the Hamiltonian that dominates the game at the transaction layer;

[0245] It is a contractual item, and its inherent meaning is to punish non-cooperative behavior;

[0246] S52. Set the key parameters and automatic execution process of the contract mechanism, wherein the key parameters include:

[0247] Cooperation Benchmark : Represents a conservative, cooperative pricing tendency, and is set as a negative value; for example 0.5;

[0248] Strategy Observation : indicates the final state of the game The expected value of the participant's bidding strategy is obtained through multiple measurements. The more positive the value, the more aggressive the bidding.

[0249] Contract strength : Indicates the severity of the penalty, which is a dynamic parameter; the contract strength. The update rules are as follows:

[0250] ;

[0251] in, The contract strength is the value after the previous iteration. The learning rate (e.g., 0.1) indicates that if a participant continues to deviate from the cooperation benchmark, the contractual penalty against it will automatically and gradually increase in subsequent games.

[0252] S53. Determine the payoff weights in quantum games by calculating the final payoff weights of the participants based on the measurement results of the final quantum state:

[0253]

[0254]

[0255] in, It is a revenue weighting operator;

[0256] It is the unit operator;

[0257] This is the baseline weight (value is 1);

[0258] It is the contract impact coefficient (negative value, value is -0.3);

[0259] The actual benefit to the participants after settlement through the quantum contract mechanism;

[0260] The theoretical profit that participants should receive according to classic market rules;

[0261] By embedding the calculation of payoff weights into the quantum measurement process, when the measurement results show that a participant's strategy deviates from the cooperation benchmark, the participant's payoff weight will be automatically reduced, thereby directly reducing its actual payoff.

[0262] The contract influence coefficient in the above formula With a reputation coefficient CR based on long-term performance i Binding Fusion ( ∝CR i This allows participants with high credibility to receive higher reward bonuses for their cooperative behavior, thus achieving long-term incentives.

[0263] This embodiment uses quantum contracts to resolve potential conflicts between secure operation and cooperative acceptance. When the system issues a warning or relevant parameters exceed the safety threshold, the coupling between the participants is reduced by lowering the secondary entanglement strength parameter, allowing them to operate independently to ensure device safety. However, this can lead to a decrease in the degree of cooperation among the participants. Therefore, a "quantum contract" is introduced in the main entanglement channel (transaction layer) to promote cooperation among the participants.

[0264] This embodiment designs a quantum strategy mapping and quantum contract mechanism. The decisions of each player are parameterized by quantum strategy angle and input into a dual-channel entangled operator. In the main channel, automatic incentives and deviation penalties are implemented through quantum contracts. If a player deviates from the optimal strategy, its payoff is automatically reduced, while the payoff of cooperating parties remains unaffected, thereby encouraging all parties to adhere to the cooperative strategy in the long term.

[0265] S6. The entanglement control and management device dynamically adjusts and updates the entanglement strength based on the results of the two-layer game. If unstable frequency or voltage operating indicators are detected, the auxiliary entanglement parameters are tightened; if a decrease in cooperative fairness is found, the main entanglement parameters are increased. Through continuous adjustment, a steady-state cooperation is gradually formed during operation.

[0266] Based on the outcome of the two-layer game, the monitoring indicator system used to dynamically adjust and update the entanglement strength includes:

[0267] Based on two types of indicators: quantum game theory indicators and classical operational indicators, the quantum game theory indicators (reflecting the state of cooperation) include:

[0268] Quotation Consistency Index C β This measures the average deviation of each participant's pricing strategy from the cooperation benchmark; the larger the value, the worse the system's cooperation. The expression is:

[0269] ;

[0270] Quotation Coordination Q β This measure the strength of the quantum correlation between the bidding strategies of different participants; the lower the value, the less synergy there is between the strategies, indicating a tendency for each to act independently. The expression is:

[0271] ;

[0272] The number of market participants in the system;

[0273] Cooperation payoff ratio R: This is the ratio of the expected payoffs to the system from a cooperative strategy to a non-cooperative strategy. A lower value indicates a smaller advantage from cooperation. The expression is:

[0274] ;

[0275] The classic operational indicators (reflecting physical security) include:

[0276] Frequency deviation Δf: The deviation between the actual system frequency and the rated value;

[0277] Voltage over-limit severity V violation : Quantify the degree to which the voltage of each node deviates from the safe range.

[0278] Based on the outcome of the two-layer game, the adjustment rules used to dynamically adjust and update the entanglement strength include: rules for adjusting the secondary entanglement strength. The principle of safety first, used to adjust the main entanglement strength The principle of cooperation and adaptation;

[0279] The triggering condition for the safety priority principle is: when the frequency deviation Δf > 0.1Hz or the voltage over-limit severity V violation A value greater than 0.02 pu indicates that the system faces a safety risk; (These are trigger thresholds set for preventative control strategies, providing sufficient response time and safety margin for the control system to prevent deviations from further expanding into dangerous areas and resulting in insufficient response time.)

[0280] The adjustment action triggered under the safety priority principle is: immediately reduce the secondary entanglement strength. The decrease is proportional to the severity of the safety risk, and the adjusted and updated auxiliary entanglement strength is:

[0281] ;

[0282] in, To adjust the secondary entanglement strength before the update;

[0283] Adjusting the strength of secondary entanglement The control logic is: reduce This effectively weakens the coupling between the strategies of each unit in the scheduling game, prompting them to act quickly and independently based on local information, prioritizing system security. Simultaneously, it increases the weight of the physical constraint term in the Hamiltonian of the scheduling layer game, further strengthening the security orientation.

[0284] The trigger condition for the cooperative adaptation principle is: when the quotation consistency index C β Greater than a certain empirical value, and the degree of price coordination Q β When the cooperation benefit ratio R is less than a certain empirical value, it indicates that the cooperativeness of the system is deteriorating.

[0285] The adjustment action triggered by the cooperative adaptation principle is: increase the main entanglement strength. The increase is related to the degree of deterioration in cooperation, and the adjusted and updated main entanglement strength is:

[0286] .

[0287] Adjusting the main entanglement strength The control logic is: increase This effectively strengthens the quantum correlation between the strategies of each participant in the trading game, making cooperative strategies more likely to gain an advantage. Simultaneously, the governance mechanism will enhance the strength of the quantum contract, imposing harsher intrinsic penalties on non-cooperative behavior.

[0288] When security risks and cooperation crises occur simultaneously, the governance mechanism adheres to the principle of absolute security priority:

[0289] Implement adjustments to the auxiliary channel immediately to ensure system stability.

[0290] The adjustments to the main channel will be temporarily suspended, and the duration of cooperation temporarily sacrificed to ensure safety will be recorded.

[0291] Post-event compensation: Once the system has stabilized, if the duration of cooperation sacrifice exceeds a preset threshold, the administrator will automatically trigger a compensation mechanism, such as appropriately lowering the contract strength of the relevant participants and providing the set reputation compensation to maintain their long-term cooperation enthusiasm.

[0292] The trigger thresholds for the security priority principle and the cooperation adaptation principle are dynamically generated by the entanglement strength manager. The method for generating the trigger thresholds includes: the entanglement strength manager continuously collects real-time data of each indicator in the quantum game index and the corresponding system cooperation state, accumulating it into a multi-scenario experience pool. After the sample size reaches the standard, the inflection point of the cooperation state transition in the data is analyzed, and the data value of the inflection point is used as the initial threshold. Subsequently, the threshold is iteratively updated in combination with new data so that the threshold always adapts to the actual cooperation characteristics of the current system.

[0293] S7 records scheduling data, transaction results, and entanglement parameters to form a three-layer recording system of physical ledger, quantum ledger, and economic ledger; it outputs scheduling instructions and transaction settlement results while updating the three-layer recording system.

[0294] The physical ledger records real-time scheduling data; the quantum ledger records entanglement parameters and strategy evolution; and the economic ledger records revenue, reputation, and contract execution status.

[0295] This embodiment achieves quantum-based management of the integrated scheduling and trading of distributed energy systems through the synergistic effect of three designs: "dual entanglement structure", "entanglement control and governance device" and "quantum contract mechanism", enabling the system to simultaneously achieve an optimized state in terms of operational safety, fair benefits and cooperative stability.

[0296] This invention also provides a distributed energy management system based on dual-entanglement controlled quantum game theory (such as...). Figure 2 As shown), the method for implementing the distributed energy management method based on dual-entanglement controlled quantum game as described above includes:

[0297] Data acquisition module: used to collect real-time data from each distributed unit, including photovoltaic output, energy storage power, voltage and current, and market price, and to initialize the strategy parameters and entanglement strength of each game subject;

[0298] State modeling module: used to establish a mathematical model of system operation based on voltage, current, and SoC energy storage state information, including power balance, voltage constraints, and energy storage capacity limits; and to establish a quantum game framework including an auxiliary entangled channel for real-time scheduling control and a main entangled channel for executing market transactions.

[0299] The quantum strategy mapping module is used to map the strategies of each participant in the game to quantum strategy angle parameters; the two entangled channels use different quantum operators to represent the entanglement relationship: the auxiliary entanglement operator is used for low-latency calculation and responds to real-time changes; the main entanglement operator is used for high-precision calculation and considers long-term incentives and reputation.

[0300] The auxiliary entanglement game module is used to calculate the optimal output of each device by taking the current data as input. When voltage fluctuations or over-limit risks occur, the entanglement control and management module reduces the auxiliary entanglement strength and reduces the strategy coupling.

[0301] Main Entanglement Game Module: Used by the main entanglement channel to recalculate the profit distribution scheme based on historical records and degree of cooperation over a long period; if a participant is found to deviate from the agreed strategy, the quantum contract mechanism is triggered to automatically adjust the participant's profit weight or reputation coefficient.

[0302] Entanglement Control and Governance Module: This module is used by the entanglement control and governance unit to dynamically adjust and update the entanglement strength based on the results of the two-layer game. If unstable frequency or voltage operating indicators are detected, the auxiliary entanglement parameters are tightened; if a decrease in cooperative fairness is detected, the main entanglement parameters are increased. Through continuous adjustment, a steady-state cooperation is gradually formed during operation.

[0303] In this embodiment, an entanglement governor is used, which can automatically adjust the strength of the primary and secondary entanglements according to the system's operating status: when the system experiences risks such as voltage fluctuations or frequency anomalies, the governor reduces the strength of the secondary entanglement to prioritize operational safety; when market cooperation decreases or revenue distribution becomes unbalanced, the primary entanglement strength is increased to strengthen cooperation incentives, enabling the system to have adaptive adjustment capabilities and maintain stability and coordination under different operating conditions.

[0304] Ledger Settlement Module: Used to record scheduling data, transaction results, and entanglement parameters, forming a three-layer recording system of physical ledger, quantum ledger, and economic ledger; outputs scheduling instructions and transaction settlement results, and updates the three-layer recording system at the same time.

[0305] Application examples

[0306] In a typical regional microgrid application, this invention includes 1MW of photovoltaic power, 500kWh of energy storage, 300kW of fuel cells, and three market-ready energy-consuming units.

[0307] System settings include: initial value of secondary entanglement strength =0.3, initial value of principal entanglement strength =0.8.

[0308] During operation, the auxiliary entanglement channel achieves second-level scheduling control to ensure power balance and voltage stability; the main entanglement channel performs transaction settlement once per hour to adjust the profit distribution ratio.

[0309] When the energy storage SOC approaches the lower limit, the system automatically tightens the secondary entanglement to prioritize scheduling safety; when some users' transactions deviate, the primary entanglement parameter is increased to strengthen cooperation constraints.

[0310] After a week of operation, the system's voltage over-limit duration decreased by about 35%, the difference in revenue among users decreased by about 40%, and the cooperation stability index increased to over 0.9.

[0311] The results show that the method of the present invention can achieve fair cooperation and improved overall benefits without sacrificing operational safety.

[0312] This application example takes "fairness of the main entanglement tube and security of the auxiliary entanglement tube" as its core logic, and achieves a dynamic balance between the two through the entanglement control and governance device, forming a distributed energy quantum energy management system that has both real-time responsiveness and long-term incentive.

[0313] This invention also provides a computer device. Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention; see the accompanying drawings. Figure 3 As shown, the computer device includes: an input device 23, an output device 24, a memory 22, and a processor 21; the memory 22 is used to store one or more programs; when the one or more programs are executed by the one or more processors 21, the one or more processors 21 implement the distributed energy management method based on dual-entanglement controlled quantum game as provided in the above embodiment; wherein the input device 23, the output device 24, the memory 22, and the processor 21 can be connected via a bus or other means. Figure 3 Taking the example of a connection between China and Israel via a bus.

[0314] The memory 22, as a read / write storage medium for a computing device, can be used to store software programs and computer-executable programs, such as the program instructions corresponding to the distributed energy management method based on dual-entanglement controlled quantum game as described in this embodiment of the invention. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device. Furthermore, the memory 22 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 22 may further include memory remotely located relative to the processor 21, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0315] Input device 23 can be used to receive input digital or character information, and generate key signal inputs related to user settings and function control of the device; output device 24 may include display devices such as a display screen.

[0316] The processor 21 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 22, thereby realizing the above-mentioned distributed energy management method based on dual entanglement control quantum game.

[0317] The computer equipment provided above can be used to execute the distributed energy management method based on dual entanglement-controlled quantum game provided in the above embodiments, and has corresponding functions and beneficial effects.

[0318] This invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to execute the distributed energy management method based on dual-entanglement controlled quantum game as provided in the above embodiments. The storage medium can be any type of memory device or storage device, including: mounting media such as CD-ROM, floppy disk, or magnetic tape; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements; the storage medium may also include other types of memory or combinations thereof; furthermore, the storage medium may reside in a first computer system in which the program is executed, or it may reside in a different second computer system connected to the first computer system via a network (such as the Internet); the second computer system can provide program instructions to the first computer for execution. The storage medium includes two or more storage media that can reside in different locations (e.g., in different computer systems connected via a network). The storage medium can store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0319] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the distributed energy management method based on dual entanglement-controlled quantum game as described in the above embodiments, but can also execute related operations in the distributed energy management method based on dual entanglement-controlled quantum game provided in any embodiment of the present invention.

[0320] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0321] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A distributed energy management method based on double entanglement regulation quantum game, characterized in that, Includes the following steps: S1. Collect real-time data from each distributed unit, including photovoltaic output, energy storage power, voltage, current and market price, and initialize the strategy parameters and entanglement strength of each game subject; S2. Based on voltage, current, and SoC energy storage state information, establish a state mathematical model of system operation that includes power balance, voltage constraints, and energy storage capacity limitations; establish a quantum game framework that includes an auxiliary entangled channel for real-time scheduling control and a main entangled channel for executing market transactions. S3. Map the strategies of each participant in the game to quantum strategy angle parameters; use different quantum operators to represent the entanglement relationship in the two entangled channels: the auxiliary entanglement operator is used for low-latency calculation and responds to real-time changes; the main entanglement operator is used for high-precision calculation and considers long-term incentives and reputation. S4, the auxiliary entanglement channel uses the current data as input to calculate the optimal output of each device; when voltage fluctuations or over-limit risks occur, the entanglement control and management device reduces the auxiliary entanglement strength and reduces the strategy coupling degree; S5. The main entanglement channel recalculates the profit distribution plan based on historical records and the degree of cooperation over a long period. If a participant is found to deviate from the agreed strategy, the quantum contract mechanism is triggered, and the participant's reward weight or reputation coefficient is automatically adjusted. S6. The entanglement control and management device dynamically adjusts and updates the entanglement strength based on the results of the two-layer game. If unstable frequency or voltage operating indicators are detected, the auxiliary entanglement parameters are tightened. If a decline in the fairness of cooperation is found, the main entanglement parameter is increased; through continuous adjustment, a steady-state cooperation is gradually formed during operation. S7. Record scheduling data, transaction results, and entanglement parameters to form a three-layer recording system of physical ledger, quantum ledger, and economic ledger; Output scheduling instructions and transaction settlement results, and update the three-layer record system at the same time; The quantum contract mechanism in step S5 includes: S51. Hamiltonian of the main entanglement channel In the design of the contract item Make the contract item part of the game rules: ； wherein, is the Hamiltonian of the dominant transaction layer game; is a contractual term, which inherently implies punishment for non-cooperation; S52. Set the key parameters of the contract mechanism, wherein the key parameters include: Cooperation Benchmark This represents a conservative, cooperative pricing tendency and is set to a negative value. Policy Observation : indicates the final state of the game The expected value of the participants' bidding strategy is obtained through multiple measurements. This value is a positive indicator; the larger the value, the more aggressive the bidding. Contract strength : Indicates the severity of the penalty, which is a dynamic parameter; the contract strength. The update rules are as follows: ； in, The contract strength is the value after the previous iteration. The learning rate indicates that if a participant continues to deviate from the cooperation benchmark, the contractual penalty imposed on it in subsequent games will automatically and gradually increase. S53. Determine the payoff weights in quantum games by calculating the final payoff weights of the participants based on the measurement results of the final quantum state: in, It is a revenue weighting operator; It is the unit operator; It is the benchmark weight; It is the contract impact coefficient; The actual benefit to the participants after settlement through the quantum contract mechanism; The theoretical profit that participants should receive according to classic market rules; By embedding the calculation of payoff weights into the quantum measurement process, when the measurement results show that a participant's strategy deviates from the cooperation benchmark, the participant's payoff weight will be automatically reduced, thereby directly reducing its actual payoff. The contract influence coefficient in the above formula With a reputation coefficient CR based on long-term performance i Binding and integration enable high-reputation participants to receive higher reward bonuses for their collaborative behavior, thus achieving long-term incentives.

2. The distributed energy management method based on dual-entanglement controlled quantum game as described in claim 1, characterized in that, The method for establishing the state mathematical model of system operation, which includes power balance, voltage constraints, and energy storage capacity limitations, in step S2 includes: S21. Establish a unified objective function based on minimizing the scheduling cost of output: ； Where t and T are the time period index and the total number of time periods, respectively; Let be the output of the i-th conventional generator during time period t; Let be the operating cost function of generator i; Let be the active power of the j-th energy storage system during time period t; Costs associated with energy storage operation losses; Let be the amount of electricity wasted by the k-th renewable energy source during time period t; The penalty cost for curtailing solar / wind power; This refers to the total installed power generation capacity. The number of energy storage systems; For the installed capacity of renewable energy; S22. Establish power balance constraints, including active power balance constraints and reactive power balance constraints; The expression for the active power balance constraint is: ； The expression for the reactive power balance constraint is: ； in, Let k be the maximum available active power of renewable energy source k during time period t; Total active power load; Total active power loss; This refers to the number of reactive power compensation devices; Let be the reactive power generated by generator i during time period t; The reactive power provided by the m-th reactive power compensation device during time period t; Total reactive load; The total reactive power loss is determined by the power flow equations, which are expressed as follows: For any participating node i: ， ； in, , These are the net active power and net reactive power injected into node i, respectively; , These are the voltage magnitudes at nodes i and j, respectively; The voltage phase angle difference between nodes i and j; , Let be the element in the i-th row and j-th column of the nodal admittance matrix. , These are the real part and the imaginary part, representing the topology and parameters of the power grid, respectively. S23. Establish the relationship constraints between active power frequency regulation and reactive power voltage regulation. The expression for active power frequency regulation is: ； in, For frequency deviation, , 50Hz; The load frequency damping coefficient represents the degree to which the load power naturally varies with frequency. This represents the change in mechanical power, specifically the change in the input power of the prime mover. This represents the load power variation, specifically the random fluctuations in the active power of the user load. S24. Establish constraints for the energy storage system. The energy storage state equation is: ； in, The state of charge of energy storage j at the beginning of time period t, ranging from 0 to 1; , denoted as the charging and discharging active power of energy storage j during time period t, respectively; both are non-negative values. , and The variable relationships are as follows: ； in, The rated capacity of energy storage j; , These are the charging and discharging efficiencies of energy storage j, respectively, both of which are less than 1; The duration of each time period; The expression to prevent overcharging and over-discharging is: ; The maximum charging power is: ; The upper limit of discharge power is: ; The expression for mutual exclusion between charge and discharge states is: ; S25. Establish safety thresholds, including: frequency threshold and voltage threshold; The frequency threshold 0.2Hz; The voltage threshold .

3. The distributed energy management method based on dual-entanglement controlled quantum game as described in claim 2, characterized in that, The method for mapping the strategies of each participant in the game to quantum policy angle parameters in step S3 includes: The core strategy of the participants is their level of contribution. and market quotes The output level and market quotes The quantization mapping is as follows: Output level strategy angle : in, The rated output of the participating parties; Market pricing strategy angle : in, As the market benchmark price, This is the highest bid.

4. The distributed energy management method based on dual-entanglement controlled quantum game as described in claim 1, characterized in that, The monitoring index system used in step S6 to dynamically adjust and update the entanglement strength based on the results of the two-layer game includes: Based on two types of indicators: quantum game theory indicators and classical performance indicators, the quantum game theory indicators include: Offer consistency index C β : measures the average deviation of each participant's offer strategy from the cooperative benchmark; the larger the value, the worse the system's cooperativeness, expressed as: ； Quote synergy Q β : measures the strength of quantum correlation between the quote strategies of different participants; the lower the value, the less synergy between the strategies, the more likely they are to be competitive, expressed as: ； The number of market participants in the system; Cooperation payoff ratio R: This is the ratio of the expected payoffs to the system from a cooperative strategy to a non-cooperative strategy. A lower value indicates a smaller advantage from cooperation. The expression is: ； The classic operating indicators include: Frequency deviation Δf: The deviation between the actual system frequency and the rated value; Voltage excursion severity V violation quantifies the degree to which each node voltage deviates from a safe range.

5. The distributed energy management method based on dual-entanglement controlled quantum game as described in claim 4, characterized in that, The adjustment rules used in step S6 to dynamically adjust and update the entanglement strength based on the results of the two-layer game include: rules for adjusting the secondary entanglement strength. The principle of safety first, used to adjust the main entanglement strength The principle of cooperation and adaptation; Wherein, the trigger condition of the safety priority principle is: when the frequency deviation Δf > 0.1 Hz or the voltage out-of-limit severity V violation > 0.02 p.u., it indicates that the system is facing a safety risk; The adjustment action triggered under the safety priority principle is: immediately reduce the secondary entanglement strength. The decrease is proportional to the severity of the safety risk, and the adjusted and updated auxiliary entanglement strength is: ； in, To adjust the secondary entanglement strength before the update; The trigger condition of the cooperation adaptation principle is: when the offer consistency index C β is greater than a certain empirical value, and the offer synergy Q β , the cooperation benefit ratio R is less than a certain empirical value, indicating that the cooperation of the system is deteriorating. The adjustment action triggered by the cooperative adaptation principle is: increase the main entanglement strength. The increase is related to the degree of deterioration in cooperation, and the adjusted and updated main entanglement strength is: 。 6. The distributed energy management method based on dual-entanglement controlled quantum game as described in claim 5, characterized in that, The trigger thresholds for the security priority principle and the cooperation adaptation principle are dynamically generated by the entanglement strength manager. The method for generating the trigger thresholds includes: the entanglement strength manager continuously collects real-time data of each indicator in the quantum game index and the corresponding system cooperation state, accumulating it into a multi-scenario experience pool. After the sample size reaches the standard, the inflection point of the cooperation state transition in the data is analyzed, and the data value of the inflection point is used as the initial threshold. Subsequently, the threshold is iteratively updated in combination with new data so that the threshold always adapts to the actual cooperation characteristics of the current system.

7. A distributed energy management system based on entangled quantum game theory, used to execute the distributed energy management method based on entangled quantum game theory as described in any one of claims 1-6, characterized in that, include: Data acquisition module: used to collect real-time data from each distributed unit, including photovoltaic output, energy storage power, voltage and current, and market price, and to initialize the strategy parameters and entanglement strength of each game subject; State modeling module: used to establish a mathematical model of system operation based on voltage, current, and SoC energy storage state information, including power balance, voltage constraints, and energy storage capacity limits; and to establish a quantum game framework including an auxiliary entangled channel for real-time scheduling control and a main entangled channel for executing market transactions. The quantum strategy mapping module is used to map the strategies of each participant in the game to quantum strategy angle parameters; the two entangled channels use different quantum operators to represent the entanglement relationship: the auxiliary entanglement operator is used for low-latency calculation and responds to real-time changes; the main entanglement operator is used for high-precision calculation and considers long-term incentives and reputation. The auxiliary entanglement game module is used to calculate the optimal output of each device by taking the current data as input. When voltage fluctuations or over-limit risks occur, the entanglement control and management module reduces the auxiliary entanglement strength and reduces the strategy coupling. Main Entanglement Game Theory Module: Used by the main entanglement channel to recalculate the profit distribution scheme based on historical records and the degree of cooperation over a long period of time; If a participant is found to deviate from the agreed strategy, the quantum contract mechanism is triggered to automatically adjust the participant's profit weight or reputation coefficient to prevent free-riding or malicious speculation and maintain a long-term cooperative relationship. Quantum contract mechanisms include: S51, Hamiltonian in the main entanglement channel In the design contract items This makes the contract terms part of the game rules: ； in, It is the Hamiltonian that dominates the game at the transaction layer; It is a contractual item, and its inherent meaning is to punish non-cooperative behavior; S52. Set the key parameters of the contract mechanism, wherein the key parameters include: Cooperation Benchmark This represents a conservative, cooperative pricing tendency and is set to a negative value. Policy Observation : indicates the final state of the game The expected value of the participants' bidding strategy is obtained through multiple measurements. This value is a positive indicator; the larger the value, the more aggressive the bidding. Contract strength : Indicates the severity of the penalty, which is a dynamic parameter; the contract strength. The update rules are as follows: ； in, The contract strength is the value after the previous iteration. The learning rate indicates that if a participant continues to deviate from the cooperation benchmark, the contractual penalty imposed on it in subsequent games will automatically and gradually increase. S53. Determine the payoff weights in quantum games by calculating the final payoff weights of the participants based on the measurement results of the final quantum state: ； ； in, It is a revenue weighting operator; It is the unit operator; It is the benchmark weight; It is the contract impact coefficient; The actual benefit to the participants after settlement through the quantum contract mechanism; The theoretical profit that participants should receive according to classic market rules; By embedding the calculation of payoff weights into the quantum measurement process, when the measurement results show that a participant's strategy deviates from the cooperation benchmark, the participant's payoff weight will be automatically reduced, thereby directly reducing its actual payoff. The contract influence coefficient in the above formula With a reputation coefficient CR based on long-term performance i Binding and integration enable high-reputation participants to receive higher reward bonuses for their cooperative behavior, thus achieving long-term incentives; Entanglement Control and Governance Module: This module is used by the entanglement control and governance unit to dynamically adjust and update the entanglement strength based on the results of the two-layer game. If unstable frequency or voltage operating indicators are detected, the auxiliary entanglement parameters are tightened; if a decrease in cooperative fairness is detected, the main entanglement parameters are increased. Through continuous adjustment, a steady-state cooperation is gradually formed during operation. Ledger Settlement Module: Used to record scheduling data, transaction results, and entanglement parameters, forming a three-layer recording system of physical ledger, quantum ledger, and economic ledger; outputs scheduling instructions and transaction settlement results, and updates the three-layer recording system at the same time.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the distributed energy management method based on dual entanglement-controlled quantum game as described in any one of claims 1-6.

9. A computer device, the computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the distributed energy management method based on dual-entanglement controlled quantum game as described in any one of claims 1-6.

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