面向多重不确定性的梯级水风光互补系统竞标电量偏差均衡风险决策模型

刘方; 徐韵; 邓艳平; 唐成鹏; 朱丹丹; 卫思明

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面向多重不确定性的梯级水风光互补系统竞标电量偏差均衡风险决策模型

更新时间：2026-02-03

- 面向多重不确定性的梯级水风光互补系统竞标电量偏差均衡风险决策模型
- 面向多重不确定性的梯级水风光互补系统竞标电量偏差均衡风险决策模型
- 华北电力大学学报（自然科学版） 2026年53卷第1期页码：23-35
- 作者机构：
  
  1. 上海电力大学电气工程学院
  2. 国网上海市电力公司
  3. 上海发电设备成套设计研究院有限责任公司
  4. 南方电网公司超高压输电公司
  5. 国网江苏省电力公司电力科学研究院
- 作者简介：
- 基金信息：
  
  上海市科委青年科技英才“扬帆计划”(21YF1414600)
- DOI：
  中图分类号： TM61
- 纸质出版：2026
- 稿件说明：
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[1]刘方,徐韵,邓艳平,等.面向多重不确定性的梯级水风光互补系统竞标电量偏差均衡风险决策模型[J].华北电力大学学报(自然科学版),2026,53(01):23-35.

刘方, 徐韵, 邓艳平, et al. 面向多重不确定性的梯级水风光互补系统竞标电量偏差均衡风险决策模型[J]. 2026, 53(1): 23-35.
[1]刘方,徐韵,邓艳平,等.面向多重不确定性的梯级水风光互补系统竞标电量偏差均衡风险决策模型[J].华北电力大学学报(自然科学版),2026,53(01):23-35. DOI：

刘方, 徐韵, 邓艳平, et al. 面向多重不确定性的梯级水风光互补系统竞标电量偏差均衡风险决策模型[J]. 2026, 53(1): 23-35. DOI：

摘要

梯级水风光多能互补系统(CMCS)中，上、下游子系统独立参与市场竞争，信息共享受阻叠加系统中风光水随机性，传导至下游子系统导致入库流量、可发电量等多重不确定性，易引起中标电量与可发电量不匹配，造成下游子系统无水可发或弃风/光/水问题。为均衡下游子系统日前市场中标电量偏差，提出下游子系统通过日内发电合约转让交易及系统惩罚相结合的偏差电量平衡机制。发电合约交易包括集中合约市场交易及与上游子系统协商交易，系统不平衡惩罚亦作为虚拟交易，从而转换为偏差电量在组合交易中优化分配问题。针对各类交易价格不确定性，基于CVaR框架建立了下游子系统偏差电量组合交易风险决策模型，使下游子系统偏差电量组合交易中满足预置期望损失约束下承担的CVaR风险最小。最后，通过某CMCS系统为例开展仿真分析，验证本文模型和方法在处理多主体CMCS独立参与现货市场面临电量偏差问题的有效性，为下游子系统偏差电量平衡决策和风险评估提供参考。

Abstract

In the cascade multi-energy complementary system(CMCS) where upstream and downstream subsystems independently participate in market competition

information-sharing barriers coupled with inherent stochasticity of wind/solar/hydro resources create multiple uncertainties in inflow volume and available generation capacity. This can easily cause a mismatch between the bidding volumes and actual generation capacity

leading to generation shortfalls or renewable curtailment in wind

solar and hydro. To mitigate bidding deviations in the day-ahead market in the downstream subsystem

we propose an integrated balancing mechanism combining intraday generation contract transfers with system penalty schemes. Power generation contract transactions include centralized contract market transactions and negotiated transactions with upstream subsystems

and virtual transactions representing system imbalance penalties

which transforms deviation balancing into an optimal allocation problem across composite transactions.To address price uncertainties across different trading mechanisms

a CVaR-based risk decision model is developed for composite deviation trading in downstream subsystems. This model minimizes the conditional value-at-risk(CVaR) exposure while satisfying predefined expected-loss constraints during the deviation allocation process. Finally

simulation analysis conducted on a CMCS case study verifies the effectiveness of the proposed model and method in addressing generation deviation challenges when multiple autonomous CMCS participants engage in spot markets. The results provide a reference for deviation balancing decisions and risk assessment of bidding electricity quantity in downstream subsystems.

关键词

Keywords

references

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