Shared energy storage share apportionment calculation method based on power flow tracking and cooperative game

Abstract

The invention relates to a flow tracking and cooperative game-based shared energy storage share allocation calculation method. The method comprises the following steps of: acquiring power data; constructing a shared energy storage cost allocation calculation method model based on a power flow tracking method and a Shapley value, and inputting the collected power data into the model; and outputting the model to obtain each shared share. The invention constructs a shared energy storage cost allocation calculation method based on tidal current tracking and a cooperative game. According to the mechanism, factors such as the use proportion, the use power, the power supply quality improvement benefit and the participation willingness of the rural users on energy storage are comprehensively considered, and a fair, reasonable and transparent payment mechanism among various users is realized.

Description

Technical Field

[0001] This invention belongs to the field of power grid control technology, and in particular to a method for calculating the shared energy storage share allocation based on power flow tracking and cooperative game theory. Background Technology

[0002] Rural power distribution networks, as the final link in the power system, generally suffer from problems such as long power supply radius, low load density, and aging equipment, resulting in large voltage deviations and low power supply reliability. With the rapid popularization of distributed renewable energy in rural areas, its intermittent output and anti-peak-shaving characteristics further exacerbate the pressure on power grid operation, significantly increasing the risk of local overload and voltage exceeding limits.

[0003] Against this backdrop, shared energy storage technology has become an effective solution for improving the carrying capacity and operational efficiency of rural power distribution networks. By configuring shared energy storage systems at key nodes, the spatial and temporal transfer of electricity can be achieved, effectively alleviating line congestion, improving voltage quality, and serving as an emergency power source during faults, significantly enhancing power supply reliability. However, the initial investment and operation and maintenance costs of energy storage facilities are high. How to fairly and reasonably distribute these costs among numerous beneficiary users has become a key bottleneck restricting the large-scale application of this technology in rural areas.

[0004] Traditional cost-sharing methods, such as allocating costs based on electricity consumption or transformer capacity, are ill-suited to the complex electricity usage scenarios in rural areas. Rural users are diverse, with significant differences in their timing, frequency, and reliance on energy storage. A one-size-fits-all approach could discourage user participation and hinder project implementation. Power flow tracing, through reverse flow tracking, traces the flow from load nodes back to energy storage devices, accurately calculating the actual proportion of energy storage discharge used by each user. This provides a transparent and physically based quantitative indicator for cost sharing, laying the foundation for the commercialization of shared energy storage projects in rural areas. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and propose a shared energy storage cost sharing calculation method based on power flow tracking and cooperative game theory. This method comprehensively considers factors such as the proportion of rural users using energy storage, the power consumption, the benefits of power quality improvement, and their willingness to participate, so as to achieve fair, reasonable, and transparent cost sharing among various types of users.

[0006] The technical problem solved by this invention is achieved through the following technical solution: The shared energy storage cost allocation method based on power flow tracking and cooperative game theory includes the following steps: Step 1: Collect power data; Step 2: Construct a cost-sharing calculation model based on power flow tracking and cooperative game theory, and input the collected power data into the model; Step 3: Model output, obtaining each allocation share.

[0007] Furthermore, the cost-sharing calculation model in step 2 is based on the trend tracking method and cooperative game theory: in, To obtain the allocation coefficients through normalization, To obtain the allocation share of node i based on the allocation coefficient, This represents the total cost that needs to be allocated.

[0008] Furthermore, the method for calculating the allocation coefficient obtained by the normalization process is as follows: in, Indicates user The Shapley value, where N is the set of all users, and S is the set of users not included. a subset of It is the payoff function of subset S. For the number of users in subset S, The total number of users. For users Marginal contribution when adding subset S.

[0009] Moreover, the user The method for calculating the marginal contribution when adding subset S is as follows: in, For nodes i Load weight, Represents a node i The improvement in power quality can be calculated based on power quality indicators. Represents a node i Willingness coefficient For the addition of equipment collection, Indicates user i For new equipment k The contribution factor, therefore Represents nodes obtained based on power flow tracing i Contribution factors to the renovation measures Indicates the first i The user in the first j The overall benefits after a user configures the device. For users i Marginal contribution when adding subset S.

[0010] The advantages and positive effects of this invention are: This invention collects power data; constructs a cost-sharing calculation model based on power flow tracing and cooperative game theory; inputs the collected power data into the model; and outputs the cost-sharing share for each user. This invention constructs a cost-sharing calculation method based on power flow tracing and cooperative game theory. This mechanism comprehensively considers factors such as the proportion of rural users using energy storage, the power consumption, the benefits of improved power quality, and their willingness to participate, achieving a fair, reasonable, and transparent cost distribution among various user groups. Attached Figure Description

[0011] Picture 1 This is a diagram of the IEEE 33-node power distribution system used in an embodiment of the present invention. Detailed Implementation

[0012] The present invention will be further described in detail below with reference to the accompanying drawings.

[0013] The shared energy storage cost allocation method based on power flow tracking and cooperative game theory includes the following steps: Step 1: Collect power data.

[0014] Step 2: Construct a cost-sharing model based on power flow tracing and Shapley values, and input the collected power data into the model.

[0015] The cost-sharing model constructed in this invention is based on the fundamental theories of power flow tracing and Shapley value. The core principle of power flow tracing is the proportional sharing principle, using a node connected to four branches. m Explanation: Node m There are two incoming lines, 1 and 2, with power ratings of respectively. P 1 and P 2. There are two outgoing lines, 3 and 4, with outgoing power of respectively. P 3 and P 4. According to the principle of proportional sharing, the power of the output branch is provided by each input branch in proportion to its power, and the power of the input branch is also allocated by each output branch in proportion to its power, i.e., the outgoing line power. P 3. The power supplied by incoming line 1 is The power supplied by incoming line 2 is And the power of the incoming line P The power allocated to branch 3 is 2. The power allocated in branch 4 is .

[0016] Depending on the object being tracked, power flow tracing methods can be divided into downstream tracing and upstream tracing. Downstream tracing follows the power flow direction to determine which generators contribute power to the line, thus determining the contribution factor of each generator to the line. Upstream tracing follows the power flow in the opposite direction to determine which loads ultimately use the power, thus determining the contribution factor of each load to the line. In upstream tracing, because it directly traces the power path in the opposite direction of the power flow, it can clearly identify the actual usage of each load on the line and equipment, making it particularly suitable for cost allocation analysis based on the "user pays" principle. To more specifically calculate the degree of user usage of shared resources in the distribution system, a detailed analysis of the power flow direction within the power grid is required. As a power flow tracing method, upstream tracing starts from the load side and traces the power source layer by layer in the reverse direction of the power flow, thereby clarifying the contribution of each user to the power flowing through the line. Its basic calculation principle is explained below: (1) Reverse tracing method Suppose the system has n If there are 2 nodes, then the total outflow power of any node can be expressed as: (1) in, For any node i The total outflow power is the same as the total injection power; For nodes i Active power under load; For nodes i The set of qualifying teams; branch road im upper node i Inflow node m The power. Assume Substituting into the above equation, we get: (2) Calculate the relationship with the node i Connected lines ij Inflow power: (3) Let be the topology load distribution factor, representing the th . k The power of each load is supplied by the line. ij The provided proportions. By tracing back the power flow, it is possible to determine which loads are specifically using the power of a particular line, thus providing a basis for allocating line costs to the loads. Based on the clear identification of power ownership within the line, the next step is to further quantify the proportion of line resources used by each load in order to establish an allocation indicator linked to costs—that is, a contribution factor.

[0017] (2) Contribution Factor Once the power contribution of each load to the line is determined, the contribution factor of each load to the line can be determined, and the line cost can be allocated based on this factor. k Each load on the line ij The contribution is Then the first k Each load for the line ij The usage share, i.e. the proportion of the cost allocation, is , defined as the first k Each load for the line ij Contribution factor Set up the line. ij The cost is Then the first k The cost of the line needs to be shared by each load. for: (4) Power flow tracing provides a clear and quantifiable basis for allocating equipment costs in distribution networks by quantifying the specific contribution of each load to the line power flow. This is particularly effective in scenarios where multiple users share infrastructure, supporting cost allocation methods based on physical usage relationships. Building upon this allocation basis, a more equitable and flexible cost allocation calculation method can be supported through an allocation model that comprehensively measures the marginal contributions of all parties.

[0018] The Shapley value is a cost or benefit allocation method derived from cooperative game theory. First proposed by Lloyd Shapley in 1953, it measures the marginal contribution of individuals in group cooperation, thereby achieving fair resource allocation. In the power system, especially in the cost allocation problem of distribution network upgrades, different users have different reliability requirements, resulting in different impacts on system upgrades. The Shapley value provides a theoretical basis for solving fair allocation in this multi-agent cooperative context. The core formula of the Shapley value is shown in equation (5).

[0019] (5) in, Indicates user The Shapley value, where N is the set of all users, and S is the set of users not included. a subset of It is the payoff function of subset S. For the number of users in subset S, This represents the total number of users. For users Marginal contribution when adding a subset S. The Shapley value provides a very fair allocation scheme, ensuring the rationality and fairness of resource allocation by taking into account the contribution of each participant in different cooperation sequences.

[0020] When constructing a cost-sharing calculation method, it is first necessary to define the set of "participants" in the cooperation, that is, all users who benefit from a certain power grid transformation measure. For each user, the core of the Shapley value lies in calculating the average of their "marginal contribution" to the system cost or benefit across all possible user joining sequences. Mathematically, for any user... The Shapley value is a weighted average of the additional benefits (or costs) for each user in all possible subsets of the joining sequence. This calculation method fully considers the importance of users in different combinations, thus avoiding the underestimation or overestimation problems caused by simple proportional allocation.

[0021] In scenarios involving shared energy storage configurations in distribution networks, the input to the Shapley value model is typically a cost function defined on a subset of users, such as the minimum retrofit cost C(S) required for all users within subset S to achieve their desired power quality goals. By constructing such a cost function, the additional cost brought by each user when joining the system can be quantified, i.e., their marginal contribution. Based on this, combined with the standard formula for the Shapley value, the cost share that each user should bear in the collaboration can be derived. It is worth noting that this model is applicable not only to retrofit schemes in which users voluntarily participate but also to scenarios where users passively benefit, because it measures the "actual reliability improvement" from a system perspective, rather than the "subjective demands."

[0022] The advantages of applying Shapley values ​​are as follows: First, the model itself possesses fairness and axiom, and can meet basic requirements such as efficiency (no redundancy in total cost allocation) and symmetry (users with the same behavior receive the same allocation); Second, when dealing with the spillover benefits generated by the transformation among multiple users, Shapley values ​​can automatically identify users with a stronger "driving force" on the system and should be given a higher allocation weight; Third, this method naturally supports the promotion of scenarios from single-user to multi-user and from centralized transformation to regional distributed transformation, and has good scalability.

[0023] In practice, to further reflect policy guidance or the social responsibility undertaken by power grid companies, a correction mechanism can be introduced based on the Shapley allocation results. This could involve setting a percentage that power grid companies should bear or imposing an upper limit on the allocation for specific users. In this way, the Shapley value not only becomes a theoretically "ideal allocation" but also transforms into an "executable mechanism" that conforms to regulatory logic and practical operation. This ensures fairness while improving the economic efficiency and user acceptance of power grid companies when implementing reliability upgrades.

[0024] For cost sharing among users, this invention adopts the reverse flow tracing method, which traces along the opposite direction of the power flow to determine which node loads ultimately use the power in the newly added equipment. This determines the power flow contribution factor of a certain load to the newly added equipment. At the same time, it considers the user's willingness to share the cost, the willingness index based on the distance from the demand point, and the benefits of improved power quality, thereby generating a benefit matrix function and calculating the Shapley value. This can effectively measure the contribution of each user in the cooperation and provide a reasonable basis for cost sharing.

[0025] (6) (7) in, For nodes i Load weight, Represents a node i The improvement in power quality can be calculated based on power quality indicators. Represents a node i Willingness coefficient For the addition of equipment collection, Indicates user i For new equipment k The contribution factor, therefore Represents nodes obtained based on power flow tracing i Contribution factors to the renovation measures Indicates the first i The user in the first j The overall benefits after a user configures the device. For users i Marginal contribution when adding subset S.

[0026] (8) (9) Finally, normalization is performed to obtain the allocation coefficients. Nodes are obtained based on the allocation coefficients. i Share of contribution , This represents the total cost that needs to be allocated.

[0027] Step 3: Model output, obtaining each allocation share.

[0028] Based on the above-mentioned method for calculating the cost allocation of shared energy storage configuration in rural power distribution networks, this embodiment uses, for example... Picture 1 Taking the IEEE 33-node power distribution system as an example, a shared energy storage device is configured at node 18, with a total investment cost of 2 million yuan.

[0029] To simplify the calculation, nodes 9, 12, and 16 are selected as representative users, namely ordinary residential users, rural food processing plants, and agricultural irrigation users, respectively.

[0030] (1) Profit sharing in the first phase The stakeholders (representing users) negotiated with the power grid company, with the power grid company sharing 30% (600,000 yuan) and the stakeholders sharing 70% (1,400,000 yuan).

[0031] (2) Profit sharing in the second phase The stakeholder group allocated 1.4 million yuan based on the Shapley value method. The following is the basic user data: Table 1 User Basic Data

[0032] In Table 1, the load weight is the ratio of each user's load to the total load, the power quality improvement effect is the ratio of the reduction in average voltage deviation to the original voltage deviation, the willingness coefficient reflects the degree of users' willingness to invest in shared energy storage to improve power quality, and the power flow contribution factor reflects the user's profit from the new equipment.

[0033] The comprehensive benefits for each user are calculated based on equations (6) and (7). B ij .

[0034] Table 2 Overall Benefits for Each User B ij

[0035] Table 3. Shapley Values ​​and Allocation Ratios for Each User

[0036] Table 4. Allocation Coefficients and Shared Costs for Different User Types

[0037] The results in the table above show that residential users contributed 72,100 yuan, accounting for 5.15% of the total cost shared by stakeholders, reflecting their relatively low contribution and returns. Rural enterprises and agricultural irrigation users contributed 570,900 yuan and 757,000 yuan respectively, accounting for 40.78% and 54.07% respectively, reflecting their higher investment willingness and returns.

[0038] This mechanism comprehensively considers load weight, power quality improvement effect, willingness coefficient and power flow contribution factor, and achieves fair allocation for different types of users.

[0039] It should be emphasized that the embodiments described in this invention are illustrative and not limiting. Therefore, this invention includes, but is not limited to, the embodiments described in the specific implementation. Any other implementations derived by those skilled in the art based on the technical solutions of this invention are also within the scope of protection of this invention.

Claims

1. A method for calculating the shared energy storage share allocation based on power flow tracking and cooperative game theory, characterized in that: Includes the following steps: Step 1: Collect power data; Step 2: Construct a model for calculating the cost sharing of shared energy storage based on power flow tracking and cooperative game theory, and input the collected power data into the model; Step 3: Model output, obtaining each allocation share.

2. The method for calculating shared energy storage cost allocation based on power flow tracking and cooperative game theory as described in claim 1, characterized in that: The sharing model in step 2 is based on the trend tracking method and cooperative game theory: ； in, To obtain the allocation coefficients through normalization, To obtain the allocation share of node i based on the allocation coefficient, This represents the total cost that needs to be allocated.

3. The method for calculating shared energy storage cost allocation based on power flow tracking and cooperative game theory according to claim 2, characterized in that: The method for calculating the allocation coefficients obtained by the normalization process is as follows: ； ； in, Indicates user The Shapley value, where N is the set of all users, and S is the set of users not included. a subset of It is the payoff function of subset S. For the number of users in subset S, The total number of users, For users Marginal contribution when adding subset S.

4. The method for calculating shared energy storage cost allocation based on power flow tracking and cooperative game theory as described in claim 3, characterized in that: The user The method for calculating the marginal contribution when adding subset S is as follows: ； ； in, For nodes i Load weight, Represents a node i The improvement in power quality can be calculated based on power quality indicators. Represents a node i Willingness coefficient For the addition of equipment collection, Indicates user i For new equipment k The contribution factor, therefore Represents nodes obtained based on power flow tracing i Contribution factors to the renovation measures Indicates the first i The user in the first j The overall benefits after a user configures the device. For users i Marginal contribution when adding subset S.

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