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1.山东大学电气工程学院,山东省济南市 250061
2.国网电力科学研究院有限公司(南瑞集团有限公司),江苏省南京市 211106
刘昊(1981—),男,通信作者,正高级工程师,主要研究方向:电力系统优化调度。E-mail:ys199510@163.com
张恒旭(1975—),男,教授,博士生导师,主要研究方向:电力系统稳定性分析与控制。
收稿:2024-03-31,
修回:2024-12-10,
网络出版:2025-01-21,
纸质出版:2025-06-10
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刘昊,张恒旭.考虑风光储碳协同和用户满意度的分层优化调度策略[J].电力系统自动化,2025,49(11):48-58.
LIU Hao,ZHANG Hengxu.Hierarchical Optimal Dispatch Strategy Considering Wind-Solar-Storage-Carbon Synergy and User Satisfaction[J].Automation of Electric Power Systems,2025,49(11):48-58.
刘昊,张恒旭.考虑风光储碳协同和用户满意度的分层优化调度策略[J].电力系统自动化,2025,49(11):48-58. DOI: 10.7500/AEPS20240331011.
LIU Hao,ZHANG Hengxu.Hierarchical Optimal Dispatch Strategy Considering Wind-Solar-Storage-Carbon Synergy and User Satisfaction[J].Automation of Electric Power Systems,2025,49(11):48-58. DOI: 10.7500/AEPS20240331011.
随着“碳达峰∙碳中和”目标的推进及用户满意度需求不断增加,电源和负荷供需矛盾日益增加,以低碳排放为基础实现电力系统供需互动优化运行至关重要。为实现系统低碳排放及提升用户满意度,提出了电源侧考虑风光储碳协同和负荷侧计及用户满意度的分层优化调度模型。首先,电源侧以经济性最优为目标,采用动态约束碳排放模型对火电机组进行优化约束;其次,负荷侧考虑实时电价,将用户满意度水平最大作为目标函数;然后,采用基于改进樽海鞘群算法和算术优化算法的混合优化运算和粒子群算法对分层模型进行迭代运算,实现调度结果综合水平最优。最后,以改进的IEEE 33节点系统为例对所提模型进行验证。结果表明,所建立的模型不仅可以提高风光新能源利用率、增强储能对新能源消纳能力、限制高碳排放机组发电,还能实现用户满意度水平最大化,为实现低碳目标提供理论支撑。
With the advancement of the goal of “carbon emission peak and carbon neutrality” and the increase of demand for user satisfaction
the contradiction between power-side and load-side supply and demand is intensifying. It is crucial to achieve optimal operation of the supply and demand interaction in the power system based on low-carbon emissions. In order to achieve low-carbon emissions in the system and improve the user satisfaction
a hierarchical optimal dispatch model considering wind-solar-storage-carbon synergy on the power side and user satisfaction on the load side is proposed. Firstly
the power side takes the optimal economy as the objective and uses the dynamically constrained carbon emission model to optimize the constraints of thermal power units. Secondly
the load side considers the time-of-use tariffs
and takes the maximum user satisfaction level as the objective function. Then
the hybrid optimization operation based on improved salp swarm algorithm and arithmetic optimization algorithm
as well as particle swarm algorithm are used to perform iterative operations on the hierarchical model
thus achieving the optimal integrated level of dispatch results. Finally
the proposed model is verified through an improved IEEE 33-bus system. Results demonstrate that the established model can not only improve the utilization rate of wind-solar renewable energy
enhance the accommodation ability of energy storage to renewable energy
and limit the power generation of high-carbon-emission units
but also maximize the user satisfaction level
which provides theoretical support for the realization of low-carbon goal.
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