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Ancillary Services Acquisition Model: Considering market interactions in policy design
Applied Energy ( IF 11.2 ) Pub Date : 2021-09-10 , DOI: 10.1016/j.apenergy.2021.117697
Samuel Glismann

A rapidly changing electricity sector requires adjusted and new ancillary services, which enable the secure and reliable operation of the electricity system. However, assessments and policy advice regarding ancillary services and market design lack methods to evaluate the complex interaction of markets and services. Therefore, this paper contributes an open-source agent-based model to test design options for ancillary services and electricity markets. The Ancillary Services Acquisition Model (ASAM) combines the agent-based modeling framework MESA with the toolbox Python for Power System Analysis (PyPSA). The model provides various design parameters per market and agent-specific strategies as well as detailed clearing algorithms for the day-ahead market, intra-day continuous trading, redispatch, and imbalances. Moreover, ASAM includes numerous policy performance indicators, including a novel price mark-up indicator and novel redispatch performance indicators. A stylized simulation scenario verified and validated the model and addressed a redispatch design question. The results displayed the following implications from order types in redispatch markets with multi-period all-or-none design: (1) The order design provides few risks for market parties, as orders are fully cleared. (2) Large orders may lead to dispatch ramps before and after the delivery period and may cause “ramp-risk” mark-ups as well as additional trading of imbalances on intra-day. (3) All-or-none design in a liquid situation leads to the over-procurement of redispatch by the grid operator, as orders cannot be partially activated. Moreover, it is likely that the grid operator induces imbalances to the system by “incomplete” redispatch activation (i.e. upward and downward redispatch volumes are not equal).



中文翻译:

辅助服务获取模型:在政策设计中考虑市场互动

快速变化的电力部门需要经过调整的新辅助服务,以确保电力系统的安全可靠运行。然而,关于辅助服务和市场设计的评估和政策建议缺乏评估市场和服务复杂相互作用的方法。因此,本文贡献了一个基于开源代理的模型来测试辅助服务和电力市场的设计选项。该辅助服务获取模型(ASAM) 将基于代理的建模框架 MESA 与用于电力系统分析的工具箱 Python (PyPSA) 相结合。该模型为每个市场和特定于代理的策略提供了各种设计参数,以及针对日前市场、日内连续交易、再调度和不平衡的详细清算算法。此外,ASAM 包括许多政策绩效指标,包括新颖的价格加价指标和新颖的再调度绩效指标。程式化的仿真场景验证并验证了模型并解决了重新调度设计问题。结果显示了多周期全有或全无设计的再调度市场订单类型的以下含义:(1)订单设计为市场各方提供的风险很小,因为订单已完全清算。(2) 大订单可能会导致交割期前后的发货斜坡,并可能导致“斜坡风险”加价以及日内额外的不平衡交易。(3) 流动情况下的全有或全无设计导致电网运营商过度采购再调度,因为订单无法部分激活。此外,电网运营商很可能通过“不完全”重新调度激活(即向上和向下重新调度量不相等)引起系统不平衡。

更新日期:2021-09-10
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