Abstract

This paper aims to study the problems of surplus interaction, poor real-time performance, and excessive processing of information in the micro-grid scheduling and decision-making process. Firstly, the micro-grid dual-loop mobile topology structure is designed by using the method of block-chain and multi-agent fusion, realizing the real-time update of the decision-making body. Secondly, on the basis of optimizing the decision-making body, a two-layer model of intelligent decision-making under the decentralized mechanism is established. Aiming at the upper model, based on the theory of block-chain consensus mechanism, this paper proposes an improved evolutionary game algorithm. The maximum risk-benefit in the decision-making process is the objective function, which realizes the evaluation and optimization of decision tasks. For the lower layer model, based on the block-chain distributed ledger theory, this paper proposes an improved hybrid game reinforcement learning algorithm, with the maximum controllable load participation as the objective function, and realizes the optimal configuration of distributed energy in the micro-grid. This paper reveals the rules of group intelligent decision making in micro-grid under multi-task. Finally, the effectiveness of the proposed algorithm is verified by using Beijing Jin-feng Energy Internet Park data.

Highlights

  • In 2015, the European Union-funded Intelligent Grid Integrated Research Project ELECTRA IRP (European Liaison on Electricity Committed Towards long-term Research Activity Integrated ResearchProgramme) proposed the concept of “Web-of-Cells (WoC)”

  • This paper proposes the mechanism of evolutionary game algorithms based on the block-chain consensus mechanism (CM-EGA), and introduces the key technology in the distributed ledger based on the traditional agent evolutionary game algorithm: consensus mechanism, and smoothing imitate the way to update the strategy and solve the upper layer model to improve the real-time performance of the cluster

  • This paper aims to improve the efficiency of supply and demand interactive communication within the micro-grid, optimize decision-making bodies, and reduce energy consumption

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Summary

Introduction

In 2015, the European Union-funded Intelligent Grid Integrated Research Project ELECTRA IRP (European Liaison on Electricity Committed Towards long-term Research Activity Integrated ResearchProgramme) proposed the concept of “Web-of-Cells (WoC)”. This paper focuses on the direction of multi-cooperative evolutionary game between distributed energy sources and group intelligent decision-making theory in micro-grid. Aiming at this problem, the current common solution is to use a multi-agent system (MAS) with good autonomy to solve the problem of collaborative optimization of distributed systems by using its independent and parallel computing features. When there is a delivery line, the number of deferred tasks is greatly reduced, and time delay can be effectively avoided [3] This solution only solves the problem of time delay in a specific scenario and is not universal. The amount of sampled data that needs to be processed in the early stage is large, which is not conducive to improving the execution efficiency of the algorithm. (e) By using the relative coupling control structure to improve the cooperative performance of the MAS, the network predictive control scheme is adopted to actively deal with network delay and data loss, and the flexibility of the MAS is improved [6]

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