採用石油的交通基礎設施對於環境的衝擊，再加上對於石油耗盡的恐懼，導致人們對於採用電力的交通基礎設施重新產生興趣。因此，電動車（EV）和可再生能源變得更受歡迎。由於充電站的架構設計和營運管理的優化受到重視，我們著重於具有批次到達與可再生能源的充電站效能評估。另外，客戶是價格敏感型，亦即客戶根據基於可再生能源供應的接受機率來決定是否進入充電站。在本篇研究中，我們分別考慮了四種充電站的情境：單一類別電動車在一系統，兩種類別電動車在一系統，有或沒有優先權的兩種類別電動車在一系統，以及兩種類別電動車分別在兩子系統。在單一類別電動車在一系統的情境下，我們研究所考慮情境的效能。在兩種類別電動車在一系統的情境下，我們研究每一種類別電動車在同質或異質批次抵達的效能。在具有優先權的兩種類別電動車在一系統的情境下，我們著重於不同情境的效能比較，其中將高優先權給予一個或另一個類別。在兩種類別電動車分別在兩個子系統的情境下，我們著重於一個系統和兩個子系統的效能比較。首先，我們推導所考慮系統的解析模型。我們利用疊代演算法來求得穩態機率分布，且計算針對所有電動車的感興趣效能指標。第二，對於具有兩類電動車的情境，我們提出兩種近似方法來計算每一類電動車的效能指標。兩種類別電動車在一系統的情境中，近似方法2的分析結果幾乎總是優於近似方法1的分析結果。第三，我們研究各種系統參數對於效能指標的影響。系統參數包含平均批次抵達速率，平均服務速率，電價權重和電動車輛權重。我們感興趣的效能指標是系統平均EV數量，平均佇列等候時間，平均系統等候時間，平均輸入可再生能源，充電EV平均成本，阻塞機率和成功送達率。最後但非最不重要，在大多數研究情況下，解析結果與模擬結果非常地吻合。

The environmental impact of the petroleum-based transportation infrastructure, along with the fear of oil exhaustion, has led to renewed interest in an electric transportation infrastructure. Therefore, Electric vehicles (EVs) and renewable energy sources become more popular. As the optimization of architecture design and operation management of the charging station are taken seriously, we focus on performance evaluation of the charging station with batch arrivals and renewable energy. Furthermore, the customers are price-sensitive, i.e., a customer decides whether to enter the charging station according to an acceptance probability based on the renewable energy supply. In this work, we study the four scenarios for the charging station: one class of EVs in one system, two classes of EVs in one system, two classes of EVs in one system with or without priority, and two classes of EVs in two subsystems. In one class of EVs in one system scenarios, we study the performance of the considered cases. In two classes of EVs in one system scenarios, we study the performance of each class of EVs with homogeneous or heterogeneous batch. In two classes of EVs in one system with priority scenarios, we focus on the performance comparison of different cases with the high priority being given to one class or the other. In two classes of EVs in two subsystems scenarios, we focus on the performance comparison of one system and two subsystems. First, we derive the analytical models for the systems considered. An iterative algorithm is developed to find the steady state probability distribution and the performance measures of interest of all EVs. Second, we propose two approximations to find the performance measures of each class of EVs for the scenarios with two classes of EVs. For two classes of EVs in one system scenarios, it is shown that the analytical results with approximation-2 nearly always outperform the analytical results with approximation-1. Third, the effect of various system parameters on different performance measures are studied. The system parameters include the average batch arrival rate, the average service rate, the electricity price weight, and the EV number weight. The performance measures of interest are the average number of EVs in the system, the average queueing time, the average waiting time in the system, the average imported renewable energy, the average cost for each charged EV, the blocking probability, and the throughput. Last but not least, in most cases studied, the analytical results are shown to be in good agreement with the simulation results.

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