考虑电价和碳价间Copula风险依赖的虚拟电厂竞标策略

doi:10.3969/j.issn.1000-7229.2019.11.013

摘要/Abstract

摘要： 作为促进温室气体减排的新兴市场，碳交易市场逐渐成为影响发电公司收益的重要因素。碳市场中的碳排放配额具有典型的金融产品特征，碳价波动及其与电价的交互作用会给参与电力市场运营的发电公司竞标决策带来风险。在此背景下，针对由同一区域的火电机组、分布式发电单元、电动汽车和需求侧资源所集成的虚拟电厂（virtual power plant， VPP），首先利用条件风险价值（conditional-value-at-risk， CVaR）理论度量VPP所面临的不确定性因素。然后，采用Copula函数对电价与碳价的联合概率分布进行建模，并以CVaR最小化为目标，针对虚拟电厂构建了计及电价和碳价间风险依赖的Copula-CVaR竞标优化模型。最后，采用YALMIP/CPLEX对所建立的竞标优化模型进行求解，并用一个算例系统的4个场景说明了采用所提方法刻画VPP竞标风险的可行性与有效性。

关键词: 碳排放市场, 虚拟电厂（VPP）, 条件风险价值（CVaR）, Copula理论, 风险依赖, 碳价, 电价

Abstract: As an emerging market to promote greenhouse gas emission reduction， carbon emissions trading has gradually become a significant factor affecting the profits of generation companies. Carbon emission quotas in the carbon market have typical characteristics of financial products. The fluctuation of carbon price and its interaction with electricity price will inevitably bring risk to the bidding decision of a generation company. Given this background， a virtual power plant (VPP) with thermal power units， distributed generation units， electric vehicles and demand-side resources integrated in the same region is addressed first， and the uncertainties faced by the VPP are measured by the conditional-value-at-risk (CVaR). Then， according to the Copula-CVaR theory， the Copula function is employed to model the joint probability distribution of electricity price and carbon price. With the objective of minimizing the CVaR， a bidding strategy for a virtual power plant considering the risk dependence on the electricity and carbon prices is presented. Finally， a sample system with four scenarios is employed to demonstrate the feasibility and efficiency of the proposed method for characterizing the bidding risk of the VPP.

中图分类号:

TM 73

闫园，林鸿基，文福拴，龚建荣，李道强，陈成. 考虑电价和碳价间Copula风险依赖的虚拟电厂竞标策略[J]. 电力建设, 2019, 40(11): 106-115.

YAN Yuan1， LIN Hongji1， WEN Fushuan1， GONG Jianrong2， LI Daoqiang2， CHEN Cheng2. Bidding Strategy of A Virtual Power Plant Considering Copula Risk Dependence of Electricity and Carbon Prices[J]. Electric Power Construction, 2019, 40(11): 106-115.

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