隨著科技進步與環保意識高漲，在交通運輸方面，電動車越來越受到大家的關注，隨之而來的是關於電動車充電相關議題的討論。電動車的高滲透率有可能為電網帶來極大的負擔，若是有大量的電動車在同一時間充電，將會導致電網的不穩定性與不安全性提高，雖然電動車為電網帶來威脅性，但也同時為電網帶來另一種解決方案，即為電動車參與輔助服務。

為了使電網維持穩定狀態，本研究使用需量反應作為輔助服務，調整電價為驅使用戶改變用電行為的手段，吸引用戶在離峰時刻用電，讓用電量的最大值能夠下降。在本研究中，利用電價與用戶行為的關係來建立一套充電排程，假設在已知充電站總數與電動車總數下，將充電站與電動車視為彼此互相競爭的參賽者，利用數學式描述兩者的互動關係，研究的主要目的是透過這樣的充電排程方式分散充電行為，讓電網得以降低最大用電峰值，運用賽局理論處理彼此的競爭關係。實驗結果證明，在電動車依照自身的條件下選擇符合自己偏好的充電站，若是可以有彈性地去調整充電站價格，不僅可以有效的使最高峰值下降同時也增加充電站的利潤。

The burden on the power grid caused by electric vehicle charging will continue to increase in direct relation to the penetration rate of electric vehicles. Too many electric vehicles charging at the same time will lead to the destabilization of the power grid. Though providing auxiliary services to electric vehicles poses a threat to the power grid, they can also benefit the power grid if managed properly.

In this study, the relationship between the price of electricity and user behavior is used to establish a set of charging schedules to maintain the stability of the power grid. Fluctuations in the price of electricity can be used to influence consumer habits in scheduling electric vehicle charging. The main purpose of our research is to reduce peak power consumption by adjusting the electricity price to influence consumers’ charging schedules. Experimental results show that electric vehicle owners choose charging stations and times that meet their own preferences and needs. Charging stations can minimize peak power consumption while also maximizing profits by dynamically adjusting the price to charge.

Adhikari, R., Pipattanasomporn, M., & Rahman, S. (2018). An algorithm for optimal management of aggregated hvac power demand using smart thermostats. Applied Energy, 217, 166-177.
Bahrami, S., Amini, M. H., Shafie-khah, M., & Catal˜ao, J. P. S. (2018). A decentralized electricity market scheme enabling demand response deployment. IEEE Transactions on Power Systems, 33(4), 4218-4227.
Bahrami, S., & Parniani, M. (2014). Game theoretic based charging strategy for plug-in hybrid electric vehicles. IEEE Transactions on Smart Grid, 5(5), 2368-2375.
Barabadi, B., & Yaghmaee, M. H. (2019). A new pricing mechanism for optimal load scheduling in smart grid. IEEE Systems Journal, 13(2), 1737-1746.
Boulanger, A. G., Chu, A. C., Maxx, S., & Waltz, D. L. (2011). Vehicle electrification:Status and issues. Proceedings of the IEEE, 99(6), 1116-1138.
Chekired, D. A., & Khoukhi, L. (2017). Smart grid solution for charging and discharging services based on cloud computing scheduling. IEEE Transactions on Industrial Informatics, 13(6), 3312-3321.
Chekired, D. A., Khoukhi, L., & Mouftah, H. T. (2018). Decentralized cloud-sdn architecture in smart grid: A dynamic pricing model. IEEE Transactions on Industrial Informatics, 14(3), 1220-1231.
Chen, C., Wang, J., & Kishore, S. (2014). A distributed direct load control approach for large-scale residential demand response. IEEE Transactions on Power Systems, 29(5), 2219-2228.
Cort´es-Arcos, T., Bernal-Agust´ın, J. L., Dufo-L´opez, R., Lujano-Rojas, J. M., & Contreras, J. (2017). Multi-objective demand response to real-time prices (rtp) using a task scheduling methodology. Energy, 138, 19-31.
Daina, N., Sivakumar, A., & Polak, J. W. (2017). Electric vehicle charging choices: Modelling and implications for smart charging services. Transportation Research Part C: Emerging Technologies, 81, 36 - 56.
Danandeh, A., Zhao, L., & Zeng, B. (2014). Job scheduling with uncertain local generation in smart buildings: Two-stage robust approach. IEEE Transactions on
Smart Grid, 5(5), 2273-2282.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Transactions on Evolutionary Computation, 6(2), 182-197.
Fan, Z. (2011). Distributed demand response and user adaptation in smart grids. In 12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops (pp. 726–729).
Farhangi, H. (2010). The path of the smart grid. IEEE Power and Energy Magazine, 8(1), 18-28.
Gan, L., Topcu, U., & Low, S. H. (2013). Optimal decentralized protocol for electric vehicle charging. IEEE Transactions on Power Systems, 28(2), 940–951.

Gelazanskas, L., & Gamage, K. A. (2014). Demand side management in smart grid: A review and proposals for future direction. Sustainable Cities and Society, 11, 22-30.
Gupta, V., Kumar, R., & Panigrahi, B. K. (2020). User-willingness-based decentralized ev charging management in multiaggregator scheduling. IEEE Transactions on Industry Applications, 56(5), 5704-5715.
Hafez, O., & Bhattacharya, K. (2018). Integrating ev charging stations as smart loads for demand response provisions in distribution systems. IEEE Transactions on Smart Grid, 9(2), 1096-1106.
Han, S., Han, S., & Sezaki, K. (2010). Development of an optimal vehicle-to-grid aggregator for frequency regulation. IEEE Transactions on Smart Grid, 1(1), 65-72.
Hassija, V., Chamola, V., Garg, S., Krishna, D. N. G., Kaddoum, G., & Jayakody, D. N. K. (2020). A blockchain-based framework for lightweight data sharing and energy trading in v2g network. IEEE Transactions on Vehicular Technology, 69(6), 5799-5812.
Hou, L., Wang, C., & Yan, J. (2020). Bidding for preferred timing: An auction design for electric vehicle charging station scheduling. IEEE Transactions on Intelligent Transportation Systems, 21(8), 3332-3343.
IEA. (2020). Global ev outlook 2020. Retrieved Oct 25, 2020, from the World Wide Web: https://www.iea.org/reports/global-ev-outlook-2020.
Imani, M. H., Talouki, M. Y., Niknejad, P., & Yousefpour, K. (2018). Running direct load control demand response program in microgrid by considering optimal position of storage unit. In 2018 IEEE Texas Power and Energy Conference (TPEC) (pp.1–6).
Jiang, X., & Wu, L. (2020). A residential load scheduling based on cost efficiency and consumer’s preference for demand response in smart grid. Electric Power Systems Research, 186, 106410.
Kang, Q., Feng, S., Zhou, M., Ammari, A. C., & Sedraoui, K. (2017). Optimal load scheduling of plug-in hybrid electric vehicles via weight-aggregation multi-objective evolutionary algorithms. IEEE Transactions on Intelligent Transportation Systems, 18(9), 2557–2568.
Kiran, P., & Pindoriya, N. M. (2019). Centralized demand response framework of an aggregator under uncertainty. In 2019 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia) (pp. 4096–4101).
Loffredo, D. (2015). Electric vehicles integration in island systems–challenges and innovative solutions: Case study of reunion island (Unpublished master’s thesis). KTH Royal Institute of Technology, Sweden.
Lu, N., & Zhang, Y. (2013). Design considerations of a centralized load controller using thermostatically controlled appliances for continuous regulation reserves. IEEE Transactions on Smart Grid, 4(2), 914-921.
Ma, Z., Callaway, D. S., & Hiskens, I. A. (2011). Decentralized charging control of large populations of plug-in electric vehicles. IEEE Transactions on control systems technology, 21(1), 67–78.
Mohsenian-Rad, A., Wong, V. W. S., Jatskevich, J., Schober, R., & Leon-Garcia, A. (2010). Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Transactions on Smart Grid,
1(3), 320-331.
Mortaji, H., Ow, S. H., Moghavvemi, M., & Almurib, H. A. F. (2017). Load shedding and smart-direct load control using internet of things in smart grid demand response management. IEEE Transactions on Industry Applications, 53(6), 5155-5163.
Mukherjee, J. C.,&Gupta, A. (2015). A review of charge scheduling of electric vehicles in smart grid. IEEE Systems Journal, 9(4), 1541-1553.
Qin, H., & Zhang, W. (2011). Charging scheduling with minimal waiting in a network of electric vehicles and charging stations. In Proceedings of the Eighth ACM International Workshop on Vehicular Inter-networking (pp. 51–60).
Rajeev, T., & Ashok, S. (2014). Demand management of electric vehicle charging based on a cloud computing framework. In 2014 IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific) (pp. 1–4).
Saad, W., Han, Z., Poor, H. V., & Basar, T. (2012). Game-theoretic methods for the smart grid: An overview of microgrid systems, demand-side management, and smart grid communications. IEEE Signal Processing Magazine, 29(5), 86-105.
Samadi, P., Mohsenian-Rad, A.-H., Schober, R., Wong, V. W., & Jatskevich, J. (2010). Optimal real-time pricing algorithm based on utility maximization for smart grid. In 2010 First IEEE International Conference on Smart Grid Communications (pp. 415–420).
Shao, S., Zhang, T., Pipattanasomporn, M., & Rahman, S. (2010). Impact of tou rates on distribution load shapes in a smart grid with phev penetration. In IEEE PES T&D 2010 (pp. 1–6).
Song, L., Xiao, Y., & van der Schaar, M. (2014). Demand side management in smart grids using a repeated game framework. IEEE Journal on Selected Areas in Communications, 32(7), 1412-1424.
Sun, C., Wen, X., Lu, Z., Zhang, J., & Chen, X. (2021). A graphical game approach to electrical vehicle charging scheduling: Correlated equilibrium and latency minimization. IEEE Transactions on Intelligent Transportation Systems, 22(1), 505–517.
Tan, Z., Yang, P., & Nehorai, A. (2014). An optimal and distributed demand response strategy with electric vehicles in the smart grid. IEEE Transactions on Smart Grid, 5(2), 861-869.
Tang, Q., Wang, K., Yang, K., & Luo, Y. (2020). Congestion-balanced and welfaremaximized charging strategies for electric vehicles. IEEE Transactions on Parallel and Distributed Systems, 31(12), 2882-2895.
Tang, R., Wang, S., & Yan, C. (2018). A direct load control strategy of centralized airconditioning systems for building fast demand response to urgent requests of smart grids. Automation in Construction, 87, 74-83.
Theodoropoulos, T. V., Damousis, I. G., & Amditis, A. J. (2016). Demand-side management ict for dynamic wireless ev charging. IEEE Transactions on Industrial Electronics, 63(10), 6623-6630.
Tian, Z., Jung, T., Wang, Y., Zhang, F., Tu, L., Xu, C., . . . Li, X. (2016). Real-time charging station recommendation system for electric-vehicle taxis. IEEE Transactions on Intelligent Transportation Systems, 17(11), 3098-3109.
Vardakas, J. S., Zorba, N., & Verikoukis, C. V. (2015). A survey on demand response programs in smart grids: Pricing methods and optimization algorithms. IEEE Communications Surveys Tutorials, 17(1), 152-178.
Waseem, M., Lin, Z., Liu, S., Sajjad, I. A., & Aziz, T. (2020). Optimal gwcso-based home appliances scheduling for demand response considering end-users comfort. Electric Power Systems Research, 187, 106477.
Xiang, S., Chang, L., Cao, B., He, Y., & Zhang, C. (2020). A novel domestic electric water heater control method. IEEE Transactions on Smart Grid, 11(4), 3246-3256.
Xie, S., Zhong, W., Xie, K., Yu, R., & Zhang, Y. (2016). Fair energy scheduling for vehicle-to-grid networks using adaptive dynamic programming. IEEE Transactions on Neural Networks and Learning Systems, 27(8), 1697-1707.
Xing, H., Fu, M., Lin, Z., & Mou, Y. (2016). Decentralized optimal scheduling for charging and discharging of plug-in electric vehicles in smart grids. IEEE Transactions on Power Systems, 31(5), 4118-4127.
Yang, X., Wang, G., He, H., Lu, J., & Zhang, Y. (2020). Automated demand response framework in elns: Decentralized scheduling and smart contract. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(1), 58-72.
Yoon, J. H., Bladick, R., & Novoselac, A. (2014). Demand response for residential buildings based on dynamic price of electricity. Energy and Buildings, 80, 531-541.
Yu, M., & Hong, S. H. (2016). A real-time demand-response algorithm for smart grids: A stackelberg game approach. IEEE Transactions on Smart Grid, 7(2), 879-888.
Zhang, C., Liu, Y., Wu, F., Tang, B., & Fan, W. (2021). Effective charging planning based on deep reinforcement learning for electric vehicles. IEEE Transactions on Intelligent Transportation Systems, 22(1), 542-554.
Zhang, T., Chen, W., Han, Z., & Cao, Z. (2014). Charging scheduling of electric vehicles with local renewable energy under uncertain electric vehicle arrival and grid power price. IEEE Transactions on Vehicular Technology, 63(6), 2600-2612.
Zhou, K., Cheng, L., Wen, L., Lu, X., & Ding, T. (2020). A coordinated charging scheduling method for electric vehicles considering different charging demands. Energy, 213, 118882.
吳秋雨. (2020). 電動車新生活. 台電月刊(687), 26-29.
王忠慶. (2017). 電動車時代來臨：歐洲2025年起禁售燃油車引爆汽車產業革
命. Retrieved Oct 26, 2020, from the World Wide Web: https://energymagazine.itri.org.tw/Cont.aspx?CatID=2&ContID=2857.
臺灣電力公司. (2020). 空調運用技術研討會非傳統機組參與輔助服務機制介紹. Retrieved Oct 26, 2020, from the World Wide Web: https://www.taipower.com.tw/upload/130/2020070315455384240.pdf.
臺灣電力公司. (2021). 今日電力資訊. Retrieved APR 28, 2021, from the World Wide Web: https://www.taipower.com.tw/tc/page.aspx?mid=206.
駐台北荷蘭代表處. (2020). 六月份荷蘭新車銷售量增加. Retrieved Oct 26, 2020, from the World Wide Web: https://origin-www.roc-taiwan.org/nl/post/9700.html.