基于数据驱动机会约束的发电企业电煤采购及库存优化模型

doi:10.11930/j.issn.1004-9649.202210036

中国电力 ›› 2023, Vol. 56 ›› Issue (6): 176-184.DOI: 10.11930/j.issn.1004-9649.202210036

基于数据驱动机会约束的发电企业电煤采购及库存优化模型

姚力, 郑海峰, 单葆国, 谭显东, 许传龙, 徐志成

国网能源研究院有限公司，北京 102209

收稿日期:2022-10-10 修回日期:2023-01-30 发布日期:2023-07-04
作者简介:姚力（1991—），男，博士，高级工程师，从事电力供需分析、电力需求侧管理等研究，E-mail：yaoli@sgeri.sgcc.com.cn;郑海峰（1981—），男，硕士，高级工程师，从事能源电力规划、电力需求侧管理等研究，E-mail：zhenghaifeng@sgeri.sgcc.com.cn;单葆国（1971—），男，通信作者，硕士，高级工程师（教授级），从事能源经济模型、电力市场分析预测、电力需求与经济发展关系、电力需求侧管理等研究，E-mail：shanbaoguo@sgeri.sgcc.com.cn
基金资助:
国家电网有限公司科技项目（面向碳达峰、碳中和目标的一二次能源综合平衡分析决策技术研究，5100-202155294A-0-0-00）；国家自然科学基金资助项目（51907036）。

An Optimization Coal Procurement and Inventory Model for Power Generation Enterprises Based on Data-driven Chance Constraints

YAO Li, ZHENG Haifeng, SHAN Baoguo, TAN Xiandong, XU Chuanlong, XU Zhicheng

State Grid Energy Research Institute Co., Ltd., Beijing 102209, China

Received:2022-10-10 Revised:2023-01-30 Published:2023-07-04
Supported by:
This work is supported by Science & Technology Project of SGCC (Comprehensive Balance Analysis and Decision-Making Technology of Primary and Secondary Energy for Carbon Peaking and Carbon Neutralization, No.5100-202155294A-0-0-00) and National Natural Science Foundation of China (No.51907036).

摘要/Abstract

摘要： 发电企业电煤采购及库存优化对于电力保供、保障发电收益具有重要意义。国家能源主管部门已经对电厂安全存煤水平提出了明确要求。但尚未有研究对因发电量和运力不确定性导致的库存越限风险进行概率建模并提出相应的优化模型。针对这一问题，构建基于数据驱动机会约束的发电企业电煤采购及库存优化模型，提出相应的求解方法。首先，考虑发电量和运力不确定性，建立数据驱动的库存机会约束，将其转化为可被求解的条件风险价值约束；然后，利用条件风险价值对决策变量的凸性，提出了一种条件风险价值约束的分段线性化近似方法；最后，采用一个包含10个燃煤电厂的发电企业进行算例测试。优化结果表明：考虑机会约束后，电煤库存越限风险被约束在允许范围内；提出的条件风险价值约束分段线性近似方法能够使模型具有可扩展性，在降低模型规模的同时还能保证较高的精度。

关键词: 电力保供, 电煤库存, 数据驱动, 机会约束规划, 条件风险价值

Abstract: Optimization of coal procurement and inventory for power generation enterprises are of great significance for guaranteeing power supply and ensuring generation income. The requirements for safe coal inventory level have been clearly put forward by the energy administrative authority of our country. However, no existing research has ever focused on the probabilistic model and corresponding optimization strategy for the violation risk of inventory caused by the uncertainties of power generation and transportation capacity. Aiming at this problem, this paper presents an optimization coal procurement and inventory model for power generation enterprises based on data-driven chance constraints and proposes a corresponding solution method. Firstly, with consideration of the uncertainty of power generation and transportation capacity, the data-driven chance constraints for inventory are established and converted to soluble constraints of conditional value at risk (CVaR). Furthermore, based on the convexity of CVaR to decision variables, a piecewise linear approximation method for CVaR constraints is proposed. A power generation enterprise which owns 10 coal power plants is selected for case study. The optimization results show that with consideration of the chance constraints, the violation risk of power coal inventory is restricted within the allowable range; the proposed piecewise linear approximation method for CVaR constraints can make the model scalable and reduce the model’s scale with a high accuracy.

Key words: power supply guarantee, electric coal inventory, data-driven, chance-constrained programming, conditional value at risk (CVaR)

姚力, 郑海峰, 单葆国, 谭显东, 许传龙, 徐志成. 基于数据驱动机会约束的发电企业电煤采购及库存优化模型[J]. 中国电力, 2023, 56(6): 176-184.

YAO Li, ZHENG Haifeng, SHAN Baoguo, TAN Xiandong, XU Chuanlong, XU Zhicheng. An Optimization Coal Procurement and Inventory Model for Power Generation Enterprises Based on Data-driven Chance Constraints[J]. Electric Power, 2023, 56(6): 176-184.

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基于数据驱动机会约束的发电企业电煤采购及库存优化模型

An Optimization Coal Procurement and Inventory Model for Power Generation Enterprises Based on Data-driven Chance Constraints

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基于数据驱动机会约束的发电企业电煤采购及库存优化模型

An Optimization Coal Procurement and Inventory Model for Power Generation Enterprises Based on Data-driven Chance Constraints

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