Managing green Energy feed-in uncertainty for cost-efficient and reliable power system operation via AC CHance-constrained security constrained Optimal power flow (ECHO)

通过 AC CHance 约束的安全约束的最佳潮流 (ECHO) 管理绿色能源馈入的不确定性，实现经济高效且可靠的电力系统运行

• 批准号: 471229899
• 负责人: Professor Dr.-Ing. Pu Li
• 金额: --
• 依托单位: Institut für Automatisierungs- und Systemtechnik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/471229899?language=en
• 关键词: Managing; green; Energy; feed; uncertainty

The ECHO project focuses on the security-constrained (or contingency-constrained) optimal power flow (SCOPF), aiming at improving the decision-making for day-ahead planning of power system operation, i.e., to ensure a cost-efficient and reliable power system scheduling for every hour of the next day. In addition, power systems are facing increasingly uncertain operation conditions, due to growing amounts of fluctuating renewable generation. The deterministic version of SCOPF, which fits only the most likely forecasted scenario, is not anymore suitable since it may lead to either sub-optimal or unreliable/risky operating conditions. To overcome this limitation, the ECHO project will develop a new SCOPF approach which manages the uncertainty via chance constrained optimization that enforces the set of constraints to satisfy a user-defined probability level. To this end, we resort to the inner-outer approximation method, which is a new method recently developed by the applicants in the area of chance constrained optimization. The very few existing works on this topic were based on the questionable AC grid model approximation as a linear direct current (DC) model (whose optimal control actions could be infeasible for real operation of the network as reactive power and bus voltages variations are ignored) and were applied to small systems. Unlike these previous works, the ECHO project is leveraged for the first time to the accurate fully nonlinear AC grid model for a medium size power systems (e.g. at country level). The project will comprehensively explore the aspects and implications of adopting chance constraints for security management. The ECHO project will demonstrate that a comprehensive SCOPF approach to security management of power system operation under uncertainty is indeed possible and this will lead to a better trade-off between optimality and reliability in the presence of a large penetration of renewable generation. We expect that this approach would be of interest to academia, utilities, and software developers, and it could support policy making of the network operators during the energy transition phase.

ECHO项目的重点是安全受限（或应有的）最佳电力流（SCOPF），旨在改善电力系统运营日期计划的决策，即确保第二天每小时的每小时的成本效率可靠的电力系统计划。此外，由于可再生能源的波动量增加，电力系统正面临越来越不确定的操作条件。 SCOPF的确定性版本仅适合最可能的预测场景，它不再适合，因为它可能导致次优或不可靠/不可靠/风险的操作条件。为了克服这一限制，Echo项目将开发一种新的SCOPF方法，该方法通过机会约束优化来管理不确定性，从而强制执行一组约束，以满足用户定义的概率级别。为此，我们诉诸于内部近似方法，这是申请人最近在机会约束优化领域开发的一种新方法。关于该主题的现有作品很少是基于可疑的AC网格模型近似值作为线性直流（DC）模型（其最佳控制动作可能不可避免地用于网络的真实操作，因为反应能力和总线电压变化被忽略），并应用于小型系统。与这些先前的作品不同，Echo项目首次利用了中等尺寸动力系统的准确完全非线性AC网格模型（例如在国家 /地区）。该项目将全面探讨采用机会限制对安全管理的方面和含义。 ECHO项目将表明，在不确定性下，在不确定性下对电力系统操作的安全管理进行了全面的SCOPF方法，这将导致在可再生生成大量渗透的情况下，在最优性和可靠性之间取消折衷。我们希望这种方法对学术界，公用事业和软件开发人员感兴趣，并且可以在能源过渡阶段支持网络运营商的政策制定。