Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets

Jian Wang; Ning Xie; Chunyi Huang; Yong Wang

doi:10.1186/s41601-023-00320-y

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Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets

Original Research | 更新时间：2026-09-30

- Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets
- Protection and Control of Modern Power Systems Vol. 8, Issue 3, Pages: 1-20(2023)
- 作者机构：
  
  1. Department of Electrical Engineering, Shanghai Jiao Tong University,Shanghai,China
  2. Department of Energy, Politecnico Di Milano, Milan,Italy
- 作者简介：
- 基金信息：
- DOI：10.1186/s41601-023-00320-y
  CLC：
- Published：01 July 2023
- 稿件说明：
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Jian Wang, Ning Xie, Chunyi Huang, et al. Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets[J]. Protection and Control of Modern Power Systems, 2023, 8(3): 1-20.
DOI：

Jian Wang, Ning Xie, Chunyi Huang, et al. Two-stage stochastic-robust model for the self-scheduling problem of an aggregator participating in energy and reserve markets[J]. Protection and Control of Modern Power Systems, 2023, 8(3): 1-20. DOI： 10.1186/s41601-023-00320-y.

摘要

This paper addresses a two-stage stochastic-robust model for the day-ahead self-scheduling problem of an aggregator considering uncertainties. The aggregator

which integrates power and capacity of small-scale prosumers and flexible community-owned devices

trades electric energy in the day-ahead (DAM) and real-time energy markets (RTM)

and trades reserve capacity and deployment in the reserve capacity (RCM) and reserve deployment markets (RDM). The ability of the aggregator providing reserve service is constrained by the regulations of reserve market rules

including minimum offer/bid size and minimum delivery duration. A combination approach of stochastic programming (SP) and robust optimization (RO) is used to model different kinds of uncertainties

including those of market price

power/demand and reserve deployment. The risk management of the aggregator is considered through conditional value at risk (CVaR) and fluctuation intervals of the uncertain parameters. Case studies numerically show the economic revenue and the energy-reserve schedule of the aggregator with participation in different markets

reserve regulations

and risk preferences.

Abstract

This paper addresses a two-stage stochastic-robust model for the day-ahead self-scheduling problem of an aggregator considering uncertainties. The aggregator

which integrates power and capacity of small-scale prosumers and fexible community-owned devices

trades electric energy in the day-ahead (DAM) and real-time energy markets (RTM)

including minimum ofer/bid size and minimum delivery duration. A combination approach of stochastic programming (SP) and robust optimization (RO) is used to model diferent kinds of uncertainties

including those of market price

power/demand and reserve deployment. The risk management of the aggregator is considered through conditional value at risk (CVaR) and fuctuation intervals of the uncertain parameters. Case studies numerically show the economic revenue and the energy-reserve schedule of the aggregator with participation in diferent markets

reserve regulations

and risk preferences.

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