在此論文探討應用於未來智慧電網的合作式需求端電源管理技術。具體而言，我們考慮－電力公司集中管理一個社區內用戶們的可控制負載，執行負載排程以達電網平衡之目的，此包括可推遲式負載(例如: 洗衣機、洗碗機等)、可調控式負載(例如: 電動車)與儲存型負載(例如: 電池)等。我們的主要目的為實現即時(real-time)、完全分散式的合作式需求端電源管理。為達此目標，第一，我們發展一基於多重自我迴歸分析(multi-stage autoregressive method)來預估短期未來太陽能電量；第二，利用滾動視窗(rolling window)的概念來執行即時的負載排程；第三，應用分散式的最佳化演算法。其中，我們應用了三種分散式最佳化方法來執行負載規劃，包含對偶次梯度法(dual subgradient method)、對偶共識性次梯度法(dual consensus subgradient)及對偶共識性交替方向收縮法(dual consensus alternating directions method of multipliers, DC-ADMM)。模擬結果證明了以上三種分散式演算法皆可明顯改善電網平衡並且DC-ADMM能提供最佳的性能。

This thesis investigates the cooperative DSM (CoDSM) technique for future smart grid. In particular, we consider that a load aggregator (e.g., the utility company) coordinates the energy consumption of a neighborhood with a large number of customers, in order to achieve real-time power balance. The deferrable loads (such as the dish washer and washing machine etc.) , adjustable loads (e.g., Electric Vehicles (EV) ) and storage devices (e.g., battery) are considered. Our main interest lies in achieving the real power balance by solving the CoDSM problem in a real-time and fully decentralized manner. To this goal, firstly, we develop a multi-stage linear prediction method for estimating the solar power generation in a short future period of time; secondly, a rolling window based control method, which can exploit both real-time and predicted solar power for real-time CoDSM is used; thirdly, distributed optimization methods are applied. Specifically, we study the load scheduling performance of three state-of-the-art distributed algorithms, namely, the distributed dual subgradient (DS) method, the dual consensus subgradient (DCS) method and the dual consensus alternating direction method of multipliers (DC-ADMM). Simulation results show that the distributed CoDSM algorithms can improve the power balance significantly and the DC-ADMM method performs best.

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