以經濟可行性為核心的電動公車V2G最佳化系統分析

Abstract

近年來，城市電動化與淨零排放政策推動下，電動公車不僅是潔淨載具，更逐漸展現作為電網儲能單元的潛力。然而，V2G（車連網）系統的實際運作牽涉高度複雜性，其必須同時整合公車排班、太陽能發電變化、時間電價制度（TOU）、電池衰退成本與充電樁設施配置等多重因素，並考量這些因素之間的交互影響與時序關聯。由於傳統的操作方法無法處理這類動態、非線性且離散的調度問題，因此本研究提出一套混合整數線性規劃（MILP）模型，作為最佳化運算框架，以提升整體營運與能源管理效益。本研究以臺北市為場域，結合三座主要電動公車場站、九條路線與周邊學校屋頂太陽能系統進行模擬分析。模型結果顯示，在基線情境下，導入 V2G 系統每月可降低營運成本約新台幣 22 萬元，惟若初期投資過高，回收期仍可能超過 36 年。透過 Latin Hypercube Sampling（LHS）與 Sobol 全域敏感度分析，本研究發現”建物售電價格”與”尖峰時間電價”為關鍵政策參數；而電池衰退成本與太陽能轉換率亦具次要但不可忽視的影響。在參考政策與技術組合下，如建物售電價格 NT$2/kWh、TOU 尖峰電價 NT$10/kWh、電池容量 500kWh、衰退成本 NT$0.26/kWh，回收期可縮短至 6 年內。研究亦指出，當車隊電動化比例達 75%、並採取 1:2.22 的車樁配置時，可進一步縮短投資回收期並提升經濟效益。本研究提供一套具實證基礎的策略架構，協助政府與運輸單位在資源有限情境下，有效推動具經濟韌性的電動公車能源系統整合與永續城市轉型。

As cities worldwide move toward transportation electrification and carbon neutrality, electric buses are increasingly recognized not only as clean transport solutions but also as distributed energy storage units through Vehicle-to-Grid (V2G) systems. However, managing a large-scale V2G operation presents considerable complexity. It involves simultaneously coordinating bus dispatch schedules, solar generation fluctuations, time-of-use (TOU) electricity peak prices, battery degradation, and infrastructure constraints. These factors require careful alignment between charging, discharging, and route needs. As such, simple rule-based strategies are insufficient; an optimization-based framework is essential for maximizing cost-effectiveness while maintaining operational feasibility. To address this challenge, this study proposes an optimization-based framework that integrates V2G operations with rooftop solar photovoltaic (PV) systems in an urban transit context. A mixed-integer linear programming (MILP) model is developed to minimize total operational costs while considering real-world bus schedules, depot constraints, and solar generation from adjacent school rooftops in Taipei City. The model simulates 3 bus depots and 9 routes under various energy and policy scenarios. Baseline results show V2G can reduce monthly operational costs by NT$220,000, though the payback periods payback period exceeds 36 years hdue to high initial investment. Sensitive analyses using Latin Hypercube Sampling (LHS) and Sobol methods identify building solar electricity selling price which usually considering as feed in tariff (FIT) and TOU rates as dominant policy leverages. When some favorable conditions are applied NT$2/kWh solar feed-in price, NT$10/kWh TOU peak rate, 500 kWh battery capacity, and NT$0.26/kWh degradation cost the payback periods can be reduced to under six years. The model also finds that V2G becomes viable only when at least 75% of the fleet is electrified and recommends a charger-to-bus ratio of 1:2.22 to minimize capital investment. These insights provide a data-driven foundation for transit agencies and policymakers to design scalable, cost-effective, and policy-responsive V2G deployment strategies for sustainable urban transportation.