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
基本信息
- 批准号:471229899
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:德国
- 项目类别:Research Grants
- 财政年份:
- 资助国家:德国
- 起止时间:
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
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项目专注于安全约束(或应急约束)最优潮流(SCOPF),旨在改善电力系统运行日前规划的决策,即确保经济高效且可靠的电力第二天每个小时的系统调度。此外,由于可再生能源发电量不断增加,电力系统面临着越来越不确定的运行条件。 SCOPF 的确定性版本仅适合最可能的预测场景,因此不再合适,因为它可能导致次优或不可靠/有风险的操作条件。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,该优化强制执行一组约束以满足用户定义的概率水平。为此,我们采用内-外近似方法,这是申请人最近在机会约束优化领域开发的一种新方法。关于该主题的现有工作极少数基于作为线性直流(DC)模型的有问题的交流电网模型近似(其最佳控制行为对于网络的实际运行可能不可行,因为忽略了无功功率和母线电压变化)并应用于小型系统。与之前的工作不同,ECHO 项目首次用于中等规模电力系统(例如国家级)的精确全非线性交流电网模型。该项目将全面探讨采用机会约束进行安全管理的各个方面和影响。 ECHO项目将证明,在不确定性下对电力系统运行进行全面的SCOPF安全管理方法确实是可能的,这将在可再生能源发电大量普及的情况下实现最优性和可靠性之间的更好权衡。我们预计这种方法会引起学术界、公用事业和软件开发商的兴趣,并且它可以支持网络运营商在能源转型阶段的政策制定。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Professor Dr.-Ing. Pu Li其他文献
Professor Dr.-Ing. Pu Li的其他文献
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{{ truncateString('Professor Dr.-Ing. Pu Li', 18)}}的其他基金
Optimal and Robust Operations of Complex Processes withNon-Gaussian Distributed Uncertain Variables under ChanceConstraints - Extension to Model Predictive Control of Parabolic Partial Differential Equation Systems
机会约束下非高斯分布不确定变量复杂过程的最优鲁棒运行——抛物型偏微分方程系统模型预测控制的推广
- 批准号:
182502969 - 财政年份:2010
- 资助金额:
-- - 项目类别:
Research Grants
Optimierung und robuster Betrieb komplexer Systeme unter Unsicherheiten mit der stochastischen Programmierung
使用随机规划在不确定性下优化和鲁棒运行复杂系统
- 批准号:
5438696 - 财政年份:2004
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Optimal pressure and water age management of water distribution systems - Under Uncertain Demand and Flexible Electrical Energy Tariff
供水系统的最佳压力和水龄管理 - 在需求不确定和灵活的电价下
- 批准号:
327870500 - 财政年份:
- 资助金额:
-- - 项目类别:
Research Grants
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