Decomposition Algorithm of Source-grid-load Contribution for Promoting Renewable Energy Accommodation

Zhe MI; Jinfang ZHANG; Jun LIU; Qiuli ZHAO; Fuqiang ZHANG

doi:10.12096/j.2096-4528.pgt.19124

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Decomposition Algorithm of Source-grid-load Contribution for Promoting Renewable Energy Accommodation

Energy Internet | 更新时间：2025-07-04

- Decomposition Algorithm of Source-grid-load Contribution for Promoting Renewable Energy Accommodation
- Power Generation Technology Vol. 40, Issue 6, Pages: 509-515(2019)
- 作者机构：
  
  国网能源研究院有限公司, 北京市昌平区 102209
- 作者简介：
- 基金信息：
  
  National Key Research and Development Program(2016YFB0900100);Science and Technology Program of Sate Grade Company(SGNY0000NGJS1900255)
- DOI：10.12096/j.2096-4528.pgt.19124
  CLC：
- Received：12 August 2019，
  
  Published：30 December 2019
- 稿件说明：
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Zhe MI, Jinfang ZHANG, Jun LIU, et al. Decomposition Algorithm of Source-grid-load Contribution for Promoting Renewable Energy Accommodation[J]. Power Generation Technology, 2019, 40(6): 509-515.
DOI：

Zhe MI, Jinfang ZHANG, Jun LIU, et al. Decomposition Algorithm of Source-grid-load Contribution for Promoting Renewable Energy Accommodation[J]. Power Generation Technology, 2019, 40(6): 509-515. DOI： 10.12096/j.2096-4528.pgt.19124.

摘要

解决我国新能源消纳矛盾，需要从电源、电网、负荷等环节因素入手，综合施策、系统优化，有效提升新能源消纳能力，但因侧重研究源网荷因素共同作用效果，缺乏对促进新能源消纳时每种因素的实际贡献度分析。为此，从规划角度，基于电力系统生产模拟构建不同的源网荷因素发展情景，分别根据灵敏度法和Shapley值法对各因素在促进新能源消纳能力中的贡献度进行分解，并结合算例充分比较两种方法差异。分析结果表明，灵敏度法针对特定情景判断某因素的消纳贡献度，适合针对既定发展阶段给出措施清单；Shapley值法基于全部发展情景对各因素贡献度进行综合加权，更适合考察从现状到规划水平年的发展全过程。

Abstract

Continuous optimization of source

grid and load factors is needed to solve the renewable energy curtailment problem. This article focuse d on the decomposition algorithm of contribution to renewable energy accommodation under the combined effect of source-grid-load. From the point of view of the planning

development scenarios were established under different source-grid-load factors

based on production simulation. Source-grid-load contributions to renewable energy accommodation were calculated by sensitivity analysis method and Shapley value method

respectively. The sensitivity analysis calculate contribution by judgment factors according to a specific scenario. It is suitable to give a list of measures for an established stage of development. The Shapley value method is a comprehensive weighting for the contribution of all development scenarios. It is more suitable for examining the whole process of development from the present situation to the level of planning.

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