Dual-layer scheduling coordination algorithm for power supply guarantee using multi-objective optimization in spot market environment

Q2 Energy
Xuanyuan Wang, Xu Gao, Zhen Ji, Wei Sun, Bo Yan, Bohao Sun
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引用次数: 0

Abstract

As the global electricity market continues to evolve, power dispatch in the spot market environment faces unprecedented challenges. Price fluctuations, the intermittency and uncertainty of renewable energy sources, and stringent environmental constraints make traditional dispatch methods inadequate. To address this, this work proposes a two-layer scheduling strategy based on a multi-objective enhanced genetic algorithm. This strategy aims at balancing multiple objectives such as cost efficiency, environmental impact, and system stability to optimize power dispatch in the spot market. The upper-layer scheduling of this strategy focuses on strategic decisions at the macro level, including generation planning and electricity market transactions. Its lower-layer scheduling concentrates on operational execution at the micro level, specifically power transmission and distribution. To validate the model’s effectiveness, this work designs a regional grid model that includes wind, solar, and several conventional generation units. The experimental results show that, compared to the benchmark strategy, the proposed algorithm achieves a cost savings of 8.33% while ensuring a reliable power supply. Additionally, the algorithm reduces carbon dioxide emissions by approximately 15.1% and significantly increases the average utilization rate of renewable energy to 93.4%. The algorithm is iterated 100 times, each simulating a 24-hour scheduling cycle. The experiment demonstrates its excellent performance in high-dimensional decision spaces and multi-objective optimization problems. This work not only provides an innovative multi-objective optimization solution for power dispatch in the spot market environment but also achieves significant improvements in terms of economic efficiency, environmental sustainability, and long-term viability. Through this two-layer scheduling strategy, the dispatch efficiency of the power system is significantly enhanced, and this provides strong support for the development of a green, low-carbon power supply system.

现货市场环境下多目标优化供电保障的双层调度协调算法
随着全球电力市场的不断发展,现货市场环境下的电力调度面临着前所未有的挑战。价格波动、可再生能源的间歇性和不确定性以及严格的环境约束使得传统的调度方法不足。为了解决这一问题,本文提出了一种基于多目标增强型遗传算法的双层调度策略。该策略旨在平衡成本效益、环境影响和系统稳定性等多个目标,以优化现货市场的电力调度。该策略的上层调度侧重于宏观层面的战略决策,包括发电规划和电力市场交易。其底层调度集中于微观层面的运行执行,特别是输配电。为了验证模型的有效性,本工作设计了一个区域电网模型,其中包括风能、太阳能和几个传统发电单元。实验结果表明,与基准策略相比,该算法在保证可靠供电的同时,节省了8.33%的成本。此外,该算法减少了约15.1%的二氧化碳排放量,并显著提高了可再生能源的平均利用率,达到93.4%。算法迭代100次,每次模拟24小时调度周期。实验证明了该算法在高维决策空间和多目标优化问题上的优异性能。该工作不仅为现货市场环境下的电力调度提供了一种创新的多目标优化解决方案,而且在经济效益、环境可持续性和长期可行性方面取得了显著的进步。通过这种双层调度策略,电力系统的调度效率显著提高,为绿色低碳供电系统的发展提供了有力支撑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
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