从优化视角剖析电力市场的定价问题

doi:10.19595/j.cnki.1000-6753.tces.221083

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摘要在电力市场中,电价通常由市场出清或优化调度等原问题的对偶解构成,具有良好的经济学意义。然而,当原问题面临退化、约束越限等问题时,基于原问题对偶解的定价方法难以保证理想的定价性质。为此,该文提出一种计及定价性质要求的通用性优化定价框架与几种不同形式的优化定价模型,以满足市场运营机构对定价性质的调控需求。首先,从优化视角剖析定价问题,总结提炼了一种通用性优化定价框架,构建通用形式的基础优化定价模型;其次,分析基础优化定价模型的典型目标函数与约束设置,基于最优化理论与对偶理论,分别构建与双层规划定价模型等价的线性规划定价模型,解析其与现有定价方法的区别与联系;再次,以特定市场出清模型及定价问题场景为例,说明所提方法的实用性;最后,基于IEEE 30节点系统和Polish 2 383节点系统进行仿真分析,结果表明所提方法可灵活优化定价性质,满足市场定价的多重需求。

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关键词 ：电力市场, 定价机制, 双层规划, 线性规划, 对偶理论

Abstract：In the electricity market, electricity prices usually consist of dual solutions to the primal problem such as market clearing or dispatch problem, which has nice economic significance. However, when the primal problem is faced with problems such as degeneracy and constraint violation, the pricing method based on the dual solutions cannot guarantee the ideal pricing properties. Recently, some methods were presented to solve these pricing problems, but they can hardly balance the diverse market requirements for pricing properties. Therefore, this paper proposes a general optimization pricing framework considering the pricing property requirements, and several different forms of optimization pricing models, to satisfy the regulatory requirements on the pricing properties of the market operator.
First, from an optimization perspective, a general optimization pricing framework is developed, and the universal-form basic optimization pricing model which can analytically characterize cost recovery, incentive compatibility, revenue adequacy, fairness, and other pricing requirements is analyzed in detail. Secondly, typical objective function and constraint settings of the basic optimization pricing model are analyzed, based on the optimization theory and duality theory, linear programming models equivalent to the bi-level programming models are constructed, and the differences and connections between the proposed pricing methods and the existing pricing methods are interpreted. Third, taking a multi-period economic dispatch model and price spiking problem in the electricity market as an example, the practicality of the proposed method is illustrated. A suitable basic pricing optimization model and a model transformation method are selected, and a linear programming pricing optimization model considering multiple pricing property constraints is established. Finally, the proposed optimal pricing method can achieve flexible trade-offs between different properties. By reasonably regulating the prices' optimization space, the proposed method is comparable to the locational marginal pricing (LMP) method in terms of calculation time.
The numerical simulation is developed in IEEE 30 bus system and Polish 2 383 bus system. We compared pricing methods M1~M8, where M1 and M2 are respectively corresponding to the LMP based on the original dispatch model and modified dispatch model, and M3~M8 are based on the proposed pricing model with different objectives and constraint settings. The results show that M1, M3, and M4 can ensure zero lost opportunity cost (LOC) for all market participants; M2 leads to an unambiguous LOCs for market participants because the real dispatch space is not considered; M5~M8 lead to LOCs for market participants as it attempts to balance the properties of the price cap, product revenue shortfall, market surplus, and total consumer payments.
The following conclusions can be drawn from the simulation analysis: the optimal pricing method proposed in this paper can be adapted to market requirements by reasonably setting the model objective function and constraints. In terms of method selection, M3 or M4 can be used to ensure incentive compatibility and not to introduce non-scarce resources into the pricing, where price spikes and multiple solutions of price are mitigated according to the corresponding objective settings; M5 can be used to minimize LOC under the price limit and not to introduce non-scarce resources into the pricing; M6 can be used to minimize LOC and revenue shortfall under the price limit; M7 or M8 is used to further integrate the market surplus and total consumer payment.

Key words： Electricity market pricing mechanism bi-level programming linear programming duality theory

收稿日期: 2022-06-10

PACS:

TM9

基金资助:国家自然科学基金资助项目（52177072）

通讯作者: 杨知方男,1992年生,博士,教授,博士生导师,研究方向为电力系统优化、电力市场等。E-mail：zfyang@cqu.edu.cn

作者简介: 王怡女,1998年生,博士研究生,研究方向为电力市场、电力系统规划等。E-mail：20153529@cqu.edu.cn

引用本文:

王怡, 杨知方, 余娟, 文旭. 从优化视角剖析电力市场的定价问题[J]. 电工技术学报, 2023, 38(17): 4729-4745. Wang Yi, Yang Zhifang, Yu Juan, Wen Xu. Analyzing Pricing Problem in Electricity Market from an Optimization Perspective. Transactions of China Electrotechnical Society, 2023, 38(17): 4729-4745.

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