Economic Optimal Coordinated Dispatch of Power for Community Users Considering Shared Energy Storage and Demand Response under Blockchain

Abstract

In recent years, user-side energy storage has begun to develop. At the same time, independent energy storage stations are gradually being commercialized. The user side puts shared energy storage under coordinated operation, which becomes a new energy utilization scheme. To solve the many challenges that arise from this scenario, this paper proposes a community power coordinated dispatching model based on blockchain technology that considers shared energy storage and demand response. First of all, this paper analyzes the operating architecture of a community coordinated dispatching system under blockchain. Combined with the electricity consumption mode of communities using a shared energy storage station service, the interactive operation mechanism and system framework of block chain for coordinated dispatching are designed. Secondly, with the goal of minimizing the total cost of coordinated operation of the community alliance, an optimal dispatching model is established according to the relevant constraints, such as the community demand response, shared energy storage system operation and so on. Thirdly, the blockchain application scheme of community coordinated dispatching is designed, including the incentive mechanism based on the improved Shapley value allocation coordination cost, and the consensus algorithm based on the change rate of users’ electricity utilization utility function. Finally, the simulation results show that the proposed community coordinated dispatching strategy in this paper can effectively reduce the economic cost, reduce the pressure on the power grid, and promote the consumption of clean energy. The combination of the designed cost allocation and other methods with blockchain technology solves the trust problem and promotes the innovation of the power dispatching mode. This study can provide some references for the application of blockchain technology in user-side energy storage and shared energy storage.

A Two-Stage Robust Optimization Microgrid Model Considering Carbon Trading and Demand Response

“…In this paper, an optimal scheduling model is established with the aim of minimizing the comprehensive cost of microgrid operations during the scheduling period, as shown in Equation (32). The day-ahead scheduling plan includes the start-stop plan of gas turbines, energy storage equipment, photovoltaic units, unit output plan, carbon quota and electricity purchase and sale, and the load of demand-response adjustment.…”

“…The uncertainty set U is substituted into the Equation (32), and the variable product part is changed to obtain the modified subproblem Equation (41). T ; and M is a positive number of any size (not infinity).…”

“…AlDavood et al [31] proposed a robust scheduling model for islanded microgrids considering demand response, which is solved using a hybrid method combining genetic algorithms and mixed-integer programming. Yu et al [32] formulated an optimal scheduling model centred on DR, cooperative energy storage system operation, and relevant constraints.…”

A Power Evolution Game Model and Its Application Contained in Virtual Power Plants

“…The current flexibility of the power system is flawed, mainly because there are more wind and solar units on the power generation side of the general power system, and their power generation (output) is random, leading to difficulties in peak regulation (power regulation) by power companies, and the use of power users in grid regulation can improve power companies' ability to consume new energy [15,16]. Demand response is a way to guide users to actively adjust load demand by regulating energy prices or economic incentives, to achieve the effect of energy saving and load shaping and to improve the efficiency of electricity use through the comprehensive and optimal allocation of load resources [17,18]. Relying on modern advanced information and communication technology widely used in the power system, demand response has played an increasingly important role in improving the reliability of power, promoting the consumption of renewable energy and reducing energy costs [19,20].…”