用戶群代表雙層最佳化模型於需量反應市場成效探討

Abstract

近年來，由於能源轉型及氣候變遷影響，造成電力供需失衡。為了解決電力短缺的瓶頸，政府推動電力市場自由化並將民間電力資源引入電力市場。其中，以電力公司所推動的用戶群代表制度與需量反應管理措施為供給與需求端平衡下，供電穩定的解方。因此，本研究將王怡萍 (2020) 針對用戶群代表制度所提出的雙層最佳化模型，利用Karush-Kuhn-Tucker (KKT) 條件及強對偶理論 (Strong duality theorem) 整理為單層二次規劃模型後，收集台灣電力公司再生能源發電量等相關數據資料，並針對特定參數的變動進行抑低電量結果的敏感度分析，探討用戶群代表制度於在兩種需量反應市場情況下的成效。

Facing energy transition and global climate change, improving grid reliability has become an important issue nowadays. In order to minimize the imbalance caused by the uncertain generation of renewable energy sources and extreme climate, developed countries are devoting efforts to electricity market deregulation. Demand Response programs (DR) and aggregators are seen as contributing solutions to this trend. Our research aims to propose the bilevel programming models to evaluate the effectiveness of aggregators in a DR program. We convert the bilevel programming models into single-level quadratic programming models with Karush-Kuhn-Tucker (KKT) conditions, linearize techniques, and strong duality theorem. As a case study, we implement realistic data in Taiwan’ s electricity market to demonstrate the robustness of our models. We find that the aggregators play a crucial role in a DR program.