为科学、准确地确定光储项目的经济性和平准化度电成本（LCOE）,考虑技术进步、政策调控等因素的影响建立光储项目成本效益模型、LCOE模型以及系统动力学仿真模型。以河北省光储开发项目为案例,分别在有无补贴的情况下应用模型,对光储项目LCOE、内部收益率和综合效益等指标进行仿真分析。选取青海省、云南省光储开发项目做对比研究,测算出光储项目在上述3省中实现平价上网的不同临界点。所建模型可用于分析光储项目成本效益、测算LCOE值、预测光储发电实现平价上网的初始年份。

It is especially urgent to calculate the cost and benefit of photovoltaic energy storage power project accurately. In order to scientifically and accurately determine the economic and levelized cost of energy（LCOE） of photovoltaic energy storage power project, in this paper, the cost benefit model, LCOE model and system dynamics simulation model of photovoltaic energy storage power project are established considering the influence of technological progress and policy regulation. Taking the photovoltaic energy storage power project in Hebei province as an example, the LCOE, internal rate of return and comprehensive benefit of the photovoltaic energy storage power project are simulated and analyzed by using the model with or without subsidies. It also selects the photovoltaic energy storage power projects in Qinghai province and Yunnan province for comparative study, and calculates the different critical points for photovoltaic energy storage power projects to achieve grid parity in the above three provinces. The model can be used to analyze the cost benefit of photovoltaic energy storage power project, to measure LCOE, and to predict the initial year when photovoltaic energy storage power project will realize grid parity in the future.

风光储多能互补能源系统可充分利用可再生能源提高供能的经济性和环保性。本文提出了一种风光储多能互补能源系统，建立了系统的能量模型；综合考虑系统运行的经济性和环保性，提出了系统综合成本和碳排放量最低的目标；开发了改进型非支配遗传算法求解仿真模型，得到了多目标问题的帕累托最优解集，并通过逼近理想解排序法获得了系统的最优容量配置运行方案；利用线性规划软件CPLEX求解器开展了系统的运行调度优化，验证了该系统框架和优化调度模型的有效性和正确性。研究结果表明，本文所提出的风光储多能互补能源系统容量配置优化方法有效提高了可再生能源利用率，实现了经济成本和碳排放量最低，提高了系统的经济性和环保性。本文为可再生能源系统实现持续稳定可靠的供能和园区的低碳化转型提供了参考。

The multi-energy complementary system integrating wind, solar, and energy storage technologies optimizes the use of renewable energy resources, enhancing both economic and environmental benefits. This study proposes a multi-energy complementary system model that incorporates wind, solar, and energy storage. The objective is to minimize the system's overall cost and carbon emissions, addressing both economic and environmental concerns. An improved non-dominated genetic algorithm is developed to obtain the Pareto optimal solution set for the multi-objective optimization problem. The optimal capacity configuration and operation scheme are determined using the technique for order preference by similarity to ideal solution. The system's operation scheduling is optimized using the CPLEX solver, a linear programming software, to validate the effectiveness and accuracy of the proposed system framework and scheduling model. Results demonstrate that the proposed optimization method significantly enhances renewable energy utilization, minimizes economic costs and carbon emissions, and improves the system's economic and environmental performance. This research offers valuable insights for the sustainable, stable, and reliable energy supply of renewable energy systems and supports the low-carbon transition of industrial parks.