基于粒子群算法的新能源消纳策略在电力交易市场的优化

doi:10.3969/j.issn.2097-0706.2025.05.009

摘要/Abstract

摘要：

在电力交易市场环境下，优化新能源消纳策略是提升新能源利用效率的重要课题。以光伏发电和火力发电的综合调度为研究对象，构建了电力交易系统模型，并基于粒子群优化算法（PSO）对调度策略进行优化。通过模拟光伏发电数据和电力负荷数据集，设定了目标函数和约束条件，分析了优化策略的实际效果。结果表明，合理的火力发电和光伏发电协调调度不仅能显著提高新能源发电的消纳效率，还提升了电力系统的稳定性和经济性，并验证了PSO在优化新能源消纳策略中的有效性，为电力市场改革和新能源利用提供了理论依据与实践指导。

关键词: 粒子群优化算法, 新能源消纳, 电力市场, 交易策略, 现货交易

Abstract:

In the context of the electricity trading market， optimizing renewable energy consumption strategies is an important approach for improving the efficiency of renewable energy utilization. The integrated scheduling of photovoltaic （PV） and thermal power generation was taken as the research subject. An electricity trading system model was established， and the scheduling strategy was optimized using the particle swarm optimization（PSO）algorithm. Through simulation of PV power generation data and electrical load datasets， the objective functions and constraints were set， and the practical effects of the optimized strategy were analyzed. The results showed that reasonable coordinated scheduling of PV and thermal power generation not only significantly improved consumption efficiency of renewable energy generation but also enhanced the stability and economic efficiency of the power system. The effectiveness of the PSO algorithm in optimizing renewable energy consumption strategies was validated. It provides a theoretical basis and practical guidance for electricity market reform and renewable energy utilization.

Key words: particle swarm optimization algorithm, renewable energy consumption, electricity market, trading strategy, spot trading

中图分类号:

TK01：TM614

张忠明, 易炳星, 赵海岭, 赵晓晔, 李长峰, 孙江, 赵麒贺. 基于粒子群算法的新能源消纳策略在电力交易市场的优化[J]. 综合智慧能源, 2025, 47(5): 84-90.

ZHANG Zhongming, YI Bingxing, ZHAO Hailing, ZHAO Xiaoye, LI Changfeng, SUN Jiang, ZHAO Qihe. Optimization of renewable energy consumption strategies in electricity trading market based on particle swarm optimization algorithm[J]. Integrated Intelligent Energy, 2025, 47(5): 84-90.

图/表 9

图1

图2

图3

图4

图5

表1

模拟参数设置

参数	设置值
光伏阵列总容量/MW	200
光伏面板太阳追踪模式	单轴追踪
光伏面板倾角/（°）	44
$a t, h$	0.001
$a t, m$	0.000 4
$σ 1$ , $σ 2$	1 000,1 000
实际输出与预测之间的偏差	±20%

表1

表2

图6

图7

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参数	值
x_m	10^-9
y_m	0.31
x_h	10^-9
y_h	0.29
w	0.83
p^t/[元·（MW·h）^-1]	1