针对传统地区电网调度中不同发电主体与负荷之间因火电机组深度调峰成本分摊导致的利益冲突问题,提出一种计及风光消纳与负荷联盟博弈的火电机组深度调峰成本分摊策略。为提高风光消纳和火电企业主动参与深度调峰的积极性,引入基于Shapley值法的成本分摊机制进行策略研究。首先,建立一个含火电厂、风电场、光伏电站和抽水蓄能电站等多供能主体的优化调度模型,该模型以系统总调峰成本最小为优化目标。其次,根据火电机组调峰市场出清结果计算边际调峰成本。仿真实例表明,利用Shapley值法对联盟成员进行调峰成本的分摊,用户侧主体产生的调峰量化成本实际值的占比与按用电量分摊的占比同各自所需分摊的边际调峰成本实际值相比,相对差值分别为-2.97%、-3.25%、-2.38%和-0.78%、-26.85%、7.58%,平均绝对误差（MAE）分别为2.37%和13.88%,下降11.51个百分点;风光侧分别从0.6~1.6倍和0.0~2.0倍参与并网,最后根据调峰效应进行各主体调峰成本分摊,得出更加公平合理的风光消纳同火电机组深度调峰的成本分摊策略。
Abstract
Traditional regional power grid scheduling often faces conflicts of interest between different power generation entities and loads due to the cost allocation of deep peak regulation for thermal power units. To address this issue,this paper proposes a deep peak regulation cost allocation strategy for thermal power units, which incorporates wind and solar power accommodation as well as a load alliance game mechanism. To enhance the participation incentives of wind, solar, and thermal power enterprises for participating in deep peak regulation, a Shapley value-based cost allocation mechanism is introduced for strategic analysis. First, an optimal scheduling model is developed, which incorporates thermal power plants, wind farms, photovoltaic power stations, and pumped storage stations, aiming to minimize the total system peak regulation cost. The model is constructed with the objective of minimizing the system-wide cost incurred by peak regulation operations. Then, the marginal peak regulation cost is calculated based on the thermal power unit market clearing results. Simulation results demonstrate that applying the Shapley value method to allocate peak-shaving costs among alliance members results in actual cost shares for user-side entities that closely align with their respective marginal peak-shaving costs. Compared to the traditional allocation method based on electricity consumption, the relative deviations are -2.97%,-3.25%, and -2.38% versus -0.78%, -26.85%, and 7.58%, respectively. The corresponding mean absolute errors （MAEs） are 2.37% and 13.88%, indicating a reduction of 11.51 percentage points. Furthermore, by varying the grid-connected capacity multiples of wind and solar generation from 0.6 to 1.6 and 0.0 to 2.0, respectively, the corresponding peak shaving effects and the cost allocation for each participating entity in deep peak regulation are analyzed. The results provide insights into developing a more equitable and rational cost-sharing strategy for wind and solar power integration and the deep peak regulation of thermal power units.
关键词
火力发电厂 /
可再生能源 /
博弈论 /
深度调峰 /
成本分析
Key words
power plants /
renewable energy resources /
game theory /
deep peak regulation /
cost benefit analysis
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基金
河南省科技攻关项目（222102240072）
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