Trading risk control model of electricity retailers in multi‐level power market of China
Abstract The decision‐making and risk assessment of electricity purchase and sales is the key to adapt to the electricity market for independent electricity retailers in China. This research carried out the purchase and sales risks of electricity for electricity retailers and constructed the multi‐l...
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2019-12-01
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Online Access: | https://doi.org/10.1002/ese3.457 |
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doaj-caeb8835f0c94b57bbd180bb93be03912020-11-25T01:37:20ZengWileyEnergy Science & Engineering2050-05052019-12-01762756276710.1002/ese3.457Trading risk control model of electricity retailers in multi‐level power market of ChinaXiaobao Yu0Yixin Sun1Shanghai University of Electric Power Shanghai ChinaState Grid Energy Research Institute Beijing ChinaAbstract The decision‐making and risk assessment of electricity purchase and sales is the key to adapt to the electricity market for independent electricity retailers in China. This research carried out the purchase and sales risks of electricity for electricity retailers and constructed the multi‐level market purchase and sales combination optimization model. Based on the portfolio optimization theory, the conditional value at risk theory (CVaR) was proposed. Based on the evaluation index about the conditional risk profit and CVaR, electricity retailers purchase and sales combined optimization model has been constructed to explore the impact of purchase and sales risks by different factors in multi‐level electricity market. The example analysis was carried out by the fixed spread mode and the linkage spread mode. The results showed that the mathematical mean and variance of market spread had great influence on the electricity purchase and sales combination. Especially in the mature electricity market, the mathematical mean of spread and risk in medium‐ and long‐term market was smaller than that in spot market, and the best point of the electricity purchase and sales combination was shown on the smallest value of CVaR, while the electricity purchase and sales combination was optimal under limited conditions.https://doi.org/10.1002/ese3.457conditional value at risk theoryelectricity retailerrisk assessmentspread model |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaobao Yu Yixin Sun |
spellingShingle |
Xiaobao Yu Yixin Sun Trading risk control model of electricity retailers in multi‐level power market of China Energy Science & Engineering conditional value at risk theory electricity retailer risk assessment spread model |
author_facet |
Xiaobao Yu Yixin Sun |
author_sort |
Xiaobao Yu |
title |
Trading risk control model of electricity retailers in multi‐level power market of China |
title_short |
Trading risk control model of electricity retailers in multi‐level power market of China |
title_full |
Trading risk control model of electricity retailers in multi‐level power market of China |
title_fullStr |
Trading risk control model of electricity retailers in multi‐level power market of China |
title_full_unstemmed |
Trading risk control model of electricity retailers in multi‐level power market of China |
title_sort |
trading risk control model of electricity retailers in multi‐level power market of china |
publisher |
Wiley |
series |
Energy Science & Engineering |
issn |
2050-0505 |
publishDate |
2019-12-01 |
description |
Abstract The decision‐making and risk assessment of electricity purchase and sales is the key to adapt to the electricity market for independent electricity retailers in China. This research carried out the purchase and sales risks of electricity for electricity retailers and constructed the multi‐level market purchase and sales combination optimization model. Based on the portfolio optimization theory, the conditional value at risk theory (CVaR) was proposed. Based on the evaluation index about the conditional risk profit and CVaR, electricity retailers purchase and sales combined optimization model has been constructed to explore the impact of purchase and sales risks by different factors in multi‐level electricity market. The example analysis was carried out by the fixed spread mode and the linkage spread mode. The results showed that the mathematical mean and variance of market spread had great influence on the electricity purchase and sales combination. Especially in the mature electricity market, the mathematical mean of spread and risk in medium‐ and long‐term market was smaller than that in spot market, and the best point of the electricity purchase and sales combination was shown on the smallest value of CVaR, while the electricity purchase and sales combination was optimal under limited conditions. |
topic |
conditional value at risk theory electricity retailer risk assessment spread model |
url |
https://doi.org/10.1002/ese3.457 |
work_keys_str_mv |
AT xiaobaoyu tradingriskcontrolmodelofelectricityretailersinmultilevelpowermarketofchina AT yixinsun tradingriskcontrolmodelofelectricityretailersinmultilevelpowermarketofchina |
_version_ |
1725058179651338240 |