考量全球暖化以及政府政策的影響，各國使用電動車的占比日益增加，大量具有不確定性的電動車負載將加入電網中，造成區域線路過載、電網壅塞等問題。而電動車除了作為負載外，因電池特性可以在短時間內進行充電或放電，為電網提供即時電力供應需求，因此可透過一個管理系統規劃電動車充電與放電的最佳化排程，並統整大量電動車電力，向電網提供輔助服務。
本論文旨在同時實現停車場經營者的最大利潤與電動車用戶的最低成本，背景為在現有停車場中安裝電動車充電樁，以資源有限的情況下最佳化電動車的整體排程，並參與輔助服務市場機制。此外，本文亦考量因參與升/降載輔助服務市場而產生的電池老化損失，將此成本加入目標函式中。所使用分散式差分演算法最佳化排程乃應用於商業區之停車場，故採用其行為機率模型。在模擬結果中比較分析電價資訊與升降載輔助服務市場參與程度對排程結果的關聯性，並探討用戶行為對各別成本的影響。電動車排程結果表明商業形停車場參與升降載輔助服務市場是可行的。

This thesis is aimed at realizing the maximum profits of parking lot owners and the minimum cost of EV users at the same time. The background is to install EV charging stations in a parking lot with limited power resources to optimize the overall schedule of EVs and participate in the market mechanism for supporting services. In addition, this thesis also considers the loss of battery degradation due to participating in the ancillary market and adds this cost to the objectives function. The decentralized differential evolution (DE) algorithm for optimal scheduling is applied in the commercial parking lot with the user's probabilistic behavior models simulated. In the simulation results, the relevance of electricity price information and ramping ancillary service market participation are compared and analyzed. The impact of user behavior on individual costs are discussed as well.
Key words: decentralized architecture, optimal scheduling of charging and discharging, electric vehicle (EV), flexible ramping market (FRM), battery degradation

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