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1.国家电网公司西北分部,陕西省西安市 710000
2.四川大学电气工程学院,四川省成都市 610000
任景(1982—),女,通信作者,硕士,高级工程师,主要研究方向:调度计划和新能源消纳管理。E-mail:renj@nw.sgcc.com.cn
薛晨(1986—),女,硕士,高级工程师,主要研究方向:调度计划和新能源消纳管理。E-mail:18509287928@163.com
马晓伟(1978—),男,硕士,高级工程师,主要研究方向:电力系统运行与控制。E-mail:maxw@nw.sgcc.com.cn
收稿日期:2020-12-15,
修回日期:2021-03-19,
网络出版日期:2021-06-28,
纸质出版日期:2021-09-25
移动端阅览
任景,薛晨,马晓伟等.源荷联动调峰辅助服务市场两阶段模型[J].电力系统自动化,2021,45(18):94-102.
REN Jing,XUE Chen,MA Xiaowei,et al.Two-stage Model of Peak Regulation Ancillary Service Market with Source-Load Interaction[J].Automation of Electric Power Systems,2021,45(18):94-102.
任景,薛晨,马晓伟等.源荷联动调峰辅助服务市场两阶段模型[J].电力系统自动化,2021,45(18):94-102. DOI: 10.7500/AEPS20201215001.
REN Jing,XUE Chen,MA Xiaowei,et al.Two-stage Model of Peak Regulation Ancillary Service Market with Source-Load Interaction[J].Automation of Electric Power Systems,2021,45(18):94-102. DOI: 10.7500/AEPS20201215001.
新能源大规模并网给电力系统调峰带来巨大挑战,在电源侧深调空间逐步用尽的背景下,亟需高效的市场化机制引导用户侧可控负荷主动参与新能源辅助消纳。文中提出一种负荷聚合商参与的源荷联动调峰辅助服务市场框架,通过构建两阶段决策模型以实现考虑源侧深度调峰的用户侧调峰资源的市场化供给。其中
负荷聚合商测算其签约用户的需求侧响应容量及成本,基于边际效用进行竞价投标;火电机组测算其机组深度可调节能力,基于边际成本进行竞价投标,系统运营商建立采用随机机会约束规划方法的出清模型,实现源荷联动调峰市场出清。此外,进一步对市场的交易流程、出清规则及调控手段等关键问题进行了分析及探讨,算例结果验证了所提市场框架的有效性。
Large-scale integration of renewable energy has brought great challenges to the peak regulation of the power systems. Under the background that the power supply side is gradually running out of the peak regulation capacity
an efficient market mechanism is urgently required to guide the controllable load of the demand side to actively participate in the renewable energy accommodation. This paper proposes a peak regulation auxiliary service market framework for end-users and thermal power units with the participation of the load aggregator (LA). The market framework can be described as a two-stage market scheduling model to achieve peak regulation capacity supply by end-users
while fully considering the flexible peak-regulation capacity of thermal power units. LAs evaluate the response quantity and corresponding cost of their signed end-users
and then bid by their marginal utility prices. Meanwhile
thermal power units evaluate their peak regulation capacity
and then bid by their marginal cost price. After the bidding is done
the system operator uses a real-time peak regulation ancillary service market model based on a chance-constrained stochastic programming method to achieve market clearing. In addition
this paper further analyzes the key issues such as market implementation steps
market clearing rules and resource dispatch methods
etc. Case studies verify the the effectiveness of the proposed market framework.
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