含分布式新能源和需求响应负荷的虚拟电厂定价机制及优化调度

doi:10.3969/j.issn.2097-0706.2024.10.002

摘要/Abstract

摘要：

面对电网中分布式风电、光伏发电以及柔性负荷的广泛接入，将这些资源通过虚拟电厂（VPP）进行聚合，采用合理的电价机制来引导用户参与需求响应，可以有效提升新能源的消纳能力并降低整体运营成本。传统的分时电价机制往往难以实现需求响应负荷与新能源出力的良好匹配，可能会导致需求响应的不合理或过度反应。为此，针对包括分布式风电、分布式光伏发电和柔性负荷的VPP，提出了一种基于新能源出力的VPP内部定价机制，并设置电力交易优先级来引导VPP内部各资源优化运行，以VPP的整体运营成本最小化为目标，构建了一个VPP优化调度的混合整数线性规划模型。基于内蒙古某地区的实际数据进行仿真计算，结果表明，与基于传统分时电价的优化结果相比，该方法能显著提高新能源的利用率并降低VPP的运行费用。

关键词: 分布式新能源, 虚拟电厂, 柔性负荷, 需求响应, 定价机制, 混合整数线性规划模型

Abstract:

Faced with the widespread integration of distributed wind power， photovoltaic power generation， and flexible loads into the grid， aggregating these resources through virtual power plants （VPPs） and adopting a reasonable pricing mechanism to guide users to participate in demand response can effectively enhance the absorption capacity of renewable energy and reduce overall operating costs. Traditional time-of-use pricing mechanisms often struggle to achieve a good match between demand response loads and renewable energy output， which may result in irrational or excessive demand response. To address this， a VPP internal pricing mechanism based on renewable energy output was proposed for VPPs containing distributed wind power， distributed photovoltaic power generation， and flexible loads. Power trading priorities were set to guide the optimal operation of internal VPP resources， with the goal of minimizing the overall operating costs of the VPP. A mixed integer linear programming （MILP） model was constructed for optimal VPP scheduling. Simulation results based on real data from a region in Inner Mongolia show that， compared to optimization results based on traditional time-of-use pricing， this method significantly improves renewable energy utilization and reduces VPP operating costs.

Key words: distributed renewable energy resource, virtual power plant, flexible load, demand response, pricing mechanism, mixed integer linear programming model

中图分类号:

TK01：TM732

李明扬, 董哲. 含分布式新能源和需求响应负荷的虚拟电厂定价机制及优化调度[J]. 综合智慧能源, 2024, 46(10): 12-17.

LI Mingyang, DONG Zhe. Pricing mechanism and optimal scheduling of virtual power plants containing distributed renewable energy and demand response loads[J]. Integrated Intelligent Energy, 2024, 46(10): 12-17.

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时段		p_b(t)	p_s(t)
平时段	12:00—17:00，21:00—24:00	0.64	0.32
峰时段	08:00—12:00，17:00—21:00	1.00	0.53
谷时段	00:00—08:00	0.31	0.15

场景	VPP运行费用/元	新能源消纳率/%
1	381.59	97.02
2	393.60	92.99
3	270.35	99.00