基于优化计算型区块链系统的虚拟电厂模型与调度策略

doi:10.19595/j.cnki.1000-6753.tces.220881

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Abstract At present, there are four problems in the actual operation of the virtual power plant(VPP): (1) The centralized, centralized-decentralized and fully decentralized control modes of the VPP currently used cannot achieve common optimization in flexibility, compatibility and scalability, which will affect the overall operation effect of the VPP. (2) Because the VPP uses the network for two-way communication, the power generation and load data of each unit in the system are vulnerable to malicious attacks and tampering by hackers, which makes the operation process of the VPP wrong, resulting in increased system costs or equipment failures. (3) Wind, solar and other renewable energy power generation has uncertainty and randomness. If the VPP cannot quickly adjust the operation state when the power generation situation changes dramatically, it will lead to the increase of penalty costs and affect the overall benefits of the system. (4) The distributed characteristics of VPP make it difficult to integrate and coordinate the internal units. In the existing research, intelligent optimization algorithm is usually used to calculate the scheduling strategy of VPP, but such algorithm does not adapt to the distributed characteristics of VPP, and there are still deficiencies in calculation time and accuracy, which will lead to the rise of system operation cost and the decline of operation efficiency. To solve these problems, this paper proposes a VPP model and scheduling strategy based on optimized computing block-chain system to improve the information security level and operation efficiency of VPP.
Firstly, the basic structure of the block-chain system and the feasibility of the combination of block-chain technology and VPP are studied, and then on this basis, block-chain based distributed particle swarm optimization algorithm (BD-PSO) and proof of optimization calculation workload (POCW) consensus algorithm suitable for VPP operation environment are proposed, improve the computing speed of scheduling optimization problems. Thirdly, the improved BD-PSO algorithm and POCW algorithm are used to improve the traditional block-chain, and an optimized computational block-chains (OCB) system is proposed to improve the adaptability of the combination of block-chain and VPP and improve the operation efficiency of the system. Finally, the OCB virtual power plant (OCB-VPP) structure model and scheduling strategy are established based on OCB. Through the actual data of a certain region, the differences between OCB-VPP and traditional VPP in coping with the fluctuation of renewable energy output, economic benefits of the system and carbon emissions are compared and analyzed. The advantages of BD-PSO algorithm in calculation speed and accuracy are analyzed, and the effectiveness and economy of the proposed model are verified.
The simulation results of actual data in a certain area show that: (1) BD-PSO algorithm produces more calculation results based on Lin-WPSO algorithm, which are compared in a larger range, optimizes the disadvantage that the Lin-WPSO algorithm is easy to fall into local optimization, and improves the calculation speed and accuracy by 50.19% and 9.86% respectively. (2) Compared with the traditional VPP system, OCB-VPP system benefits from the improvement of system architecture and algorithm performance, and has advantages in scheduling efficiency and accuracy, which significantly reduces the operation cost of the system. The typical daily cost of each season is reduced by 13.29%, the carbon emission is reduced by 14.53%, the wind / light consumption of the system is increased by 9.95%, and the economic benefits and energy utilization of the system have been significantly improved.
Finally, the following conclusions are drawn through analysis: (1) compared with Lin-wPSO, WOA and LRO algorithms, the improved BD-PSO optimization algorithm in this paper has significant advantages in calculation speed and accuracy. Therefore, BD-PSO optimization algorithm is very suitable for the VPP environment with complex and changeable operating conditions. (2) OCB-VPP structure is more suitable for VPP, which can improve the information security level and operation efficiency of VPP. (3) Compared with traditional centralized VPP, OCB-VPP structure can reduce system operation costs, reduce carbon emissions and improve renewable energy utilization.

Key words： Virtual power plant block-chain distributed consensus algorithm particle swarm optimization algorithm

Received: 23 May 2022

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	Liu Yujia
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Cite this article:

Liu Yujia,Fan Yanfang,Bai Xueyan等. Virtual Power Plant Model and Scheduling Strategy Based on Optimized Computing Block-Chain System[J]. Transactions of China Electrotechnical Society, 2023, 38(15): 4178-4191.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.220881 OR https://dgjsxb.ces-transaction.com/EN/Y2023/V38/I15/4178

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