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基于并行分子微分進(jìn)化算法的虛擬電廠多目標(biāo)優(yōu)化調(diào)度

來(lái)源：電工電氣發(fā)布時(shí)間：2025-10-29 09:29瀏覽次數(shù)：3

基于并行分子微分進(jìn)化算法的虛擬電廠多目標(biāo)優(yōu)化調(diào)度

姜磊¹，龐亞亞²，姜雨宏³

(1 國(guó)網(wǎng)山東省電力公司超高壓公司，山東濟(jì)南 250118；

2 國(guó)網(wǎng)山東省電力公司臨沂供電公司，山東臨沂 276000；

3 山東理工職業(yè)學(xué)院能源與材料工程學(xué)院，山東濟(jì)寧 272067)

摘要：針對(duì)大規(guī)模風(fēng)電、光伏等清潔能源出力隨機(jī)性與熱電聯(lián)產(chǎn)機(jī)組“以熱定電”運(yùn)行約束帶來(lái)的調(diào)度挑戰(zhàn)，構(gòu)建了集成高比例可再生能源、熱電聯(lián)產(chǎn)系統(tǒng)、電熱儲(chǔ)能及需求響應(yīng)機(jī)制的虛擬電廠熱電聯(lián)合經(jīng)濟(jì)調(diào)度模型。提出基于分子動(dòng)力學(xué)“近相斥”原理改進(jìn)的多目標(biāo)并行分子微分進(jìn)化算法，構(gòu)建全異步并行架構(gòu)、精英個(gè)體動(dòng)態(tài)遷移的雙層并行計(jì)算策略，有效克服了傳統(tǒng)群智能算法存在的早熟收斂與計(jì)算效率不足問(wèn)題。仿真結(jié)果顯示：與傳統(tǒng)的微分進(jìn)化算法相比，能夠?qū)崿F(xiàn)92.3%的全局收斂成功率，計(jì)算時(shí)間大幅縮短；所構(gòu)建的調(diào)度模型在將風(fēng)電、光電全部消納的同時(shí)滿足合同供熱需求，實(shí)現(xiàn)煤耗量降低及凈收益提升，充分驗(yàn)證了模型與算法的實(shí)用價(jià)值。

關(guān)鍵詞： 虛擬電廠；分子微分進(jìn)化算法；風(fēng)光發(fā)電模擬；熱電聯(lián)合調(diào)度；電熱儲(chǔ)能；雙層并行計(jì)算

中圖分類號(hào)：TM715 ；TM731 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：1007-3175(2025)10-0024-07

Multi-Objective Optimization Scheduling of Virtual Power Plants Based on

Parallel Molecular Differential Evolution Algorithm

JIANG Lei¹, PANG Ya-ya², JIANG Yu-hong³

（1 Ultra-High Voltage Company of State Grid Shandong Electric Power Company, Jinan 250118, China;

2 Linyi Power Supply Company of State Grid Shandong Electric Power Company, Linyi 276000, China;

3 School of Energy and Materials Engineering, Shandong Polytechnic College, Jining 272067, China）

Abstract: In response to the dispatching challenges brought about by the randomness of the output of large-scale clean energy such as wind power and photovoltaic power and the operation constraints of cogeneration units based on heat to determine power generation, a virtual power plant combined heat and power economic dispatching model integrating a high proportion of renewable energy, cogeneration systems, electric-thermal energy storage and demand response mechanisms has been constructed. An improved multi-objective parallel molecular differential evolution algorithm based on the“proximity repulsion”principle of molecular dynamics is proposed, a double-layer parallel computing strategy with a fully asynchronous parallel architecture and dynamic migration of elite individuals is constructed, effectively overcoming the problems of premature convergence and insufficient computational efficiency existing in traditional swarm intelligence algorithms. The simulation results show that compared with the traditional differential evolution algorithm, it can achieve a global convergence success rate of 92.3%, and the computing time is significantly shortened. The constructed dispatching model not only fully consumes wind power and photovoltaic power but also meets the contracted heating demand,achieving a reduction in coal consumption and an increase in net income, which fully validates the practical value of the model and algorithm.

Key words: virtual power plant (VPP); molecular differential evolution algorithm; wind/photovoltaic power generation simulation; combined thermo-electric dispatch; electric-thermal energy storage; dual-layer parallel computing

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基于并行分子微分進(jìn)化算法的虛擬電廠多目標(biāo)優(yōu)化調(diào)度