摘要
由于电力系统能源的多样性,包括传统电力、可再生能源和储能系统,使得协同管理成为确保电力供应可靠性、经济性和可持续性的关键因素.为应对现代电力系统中复杂的能源管理挑战,提出了一种基于CPSO算法的区域电力综合能源协同优化调度方法.首先建立了电力系统的数学模型,包括各种能源的生产、储能、输电和负荷消耗.目标函数包括最小化总成本、最小化碳排放或最大化系统可靠性等不同情景.同时,考虑了多种约束条件,如电力供应的稳定性、储能容量限制以及可再生能源的波动性.CPSO算法作为优化工具,通过在实验中调整CPSO算法的参数和初始条件,对各种情景下的优化结果进行了分析和比较.实验结果表明,基于CPSO算法的区域电力综合能源协同优化调度方法能够有效地降低总成本、减少碳排放,并提高系统的可靠性.此外,该方法还展现了对不稳定可再生能源的灵活适应能力.
Abstract
Due to the diversity of energy sources in the power system,including traditional electricity,renewable energy,and energy storage systems,collaborative management has become a crucial factor in ensuring the reliability,economy,and sustainability of power supply.To address the complex energy management challenges in modern power systems,this study proposes a collaborative optimization scheduling method for regional power integrated energy based on the CPSO algorithm.Firstly,a mathematical model of the power system is established,incorporating the production,storage,transmission,and load consumption of various energy sources.The objective functions cover different scenarios such as minimizing total cost,minimizing carbon emissions,or maximizing system reliability.Meanwhile,various constraint conditions are considered,including the stability of power supply,energy storage capacity limitations,and the volatility of renewable energy.The CPSO algorithm serves as an optimization tool.By adjusting the parameters and initial conditions of the CPSO algorithm in experiments,the optimization results under various scenarios are analyzed and compared.Experimental results demonstrate that the proposed collaborative optimization scheduling method for regional power integrated energy based on the CPSO algorithm can effectively reduce total cost,decrease carbon emissions,and improve system reliability.Furthermore,this method exhibits flexible adaptability to unstable renewable energy sources.
维普
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