隨著電力需求的成長，能源安全與氣候變遷成為眾所關切的議題。為達永續發展的目標，各國開始發展再生能源及實施需求面管理(Demand Side Management)。需求面管理的需量反應(Demand Response)能幫助電力公司解決日用電需求變動幅度大的問題。近年來，在現有的電網或發展中的智慧電網中，需量反應的時間電價(Time-of-Use)常被用來鼓勵用戶移轉尖峰用電。平緩的日需求曲線能延緩電廠擴增、降低供電成本、提升供電系統的穩定性與利用率。因此，本研究希望能幫助電力公司訂定時間電價。
本研究以電力公司的觀點提出一非線性多目標的差異定價模式。在永續經營與用戶滿意度的考量下，以平緩電力日需求曲線與減緩用電的環境衝擊為目標，訂定時間電價。針對用戶對電價的滿意度，本研究提出一整合用戶滿意度函數，包含三類用戶：愛好型、中立型以及趨避型。為求解模型，本研究使用權重法將多目標模式轉換為單目標模式。
最後，本研究藉由台灣時間電價的探討驗證所提出的模式，結果顯示模式提供的時間電價除了能平緩電力日需求曲線與減緩用電的環境衝擊，亦有利於電力公司與用戶。同時，本研究對用戶滿意度作敏感度分析，提供用戶滿意度與目標間的權衡資訊給電力公司。由案例探討可知，本研究能幫助電力公司訂定合理的時間電價。

With the rise in electricity demand, energy security and climate change have become imperative problems. To reach the goal of sustainable development, each country has embarked on the development of renewable energy and demand side management. In demand side management, demand response helps an electric utility company to deal with the wide variation of electricity consumption throughout the day. Recently, Time-of-Use is a common and effective demand response program which encourages the modification of consumption ways in both existing traditional grid and developing smart grid. The equalized daily consumption curve can postpone the construction of new generation units, lower generation costs, and increase both reliability and efficiency of the supply system. Based on these ideas, this study aims to help the electric utility company decide Time-of-Use prices.
To deal with a Time-of-Use pricing problem from the viewpoint of the electric utility company, this study proposes a differential pricing model in the form of nonlinear multi-objective programming to determine Time-of-Use prices. The estimated hourly consumption, which reacts to Time-of-Use prices, can also be derived from the model. In the model, the objectives are to equalize consumption throughout the day and reduce the environmental impact of daily consumption while considering business development and consumer satisfaction. To describe consumer satisfaction, an integrated consumer satisfaction in response to each electricity price is presented by considering the three types of consumers, namely, aggressive, neutral, and passive consumers. To solve the multi-objective programming model, multi-objective functions are transformed into a single objective function by the weighted sum method.
An illustrative case of Time-of-Use pricing in Taiwan is used to verify the proposed model. The results show that the suggested electricity prices can benefit both the electric utility company and consumers. The benefits can be exemplified by the minimal range of the estimated hourly consumption and the minimal estimated daily carbon dioxide emissions. Sensitivity analysis is conducted on the consumer satisfaction level to provide the electric utility company information related to the trade-off between consumer satisfaction and the objectives. The results of this study can assist the electric utility company in formulating a promising decision on setting Time-of-Use prices.

[1] Albadi, M.H. and El-Saadany, E., "A summary of demand response in electricity markets." Electric power systems research, 78(11): p. 1989-1996, 2008.
[2] Boshell, F. and Veloza, O. "Review of developed demand side management programs including different concepts and their results." Paper presented at Transmission and Distribution Conference and Exposition, 2008 IEEE/PES,Latin America: p. 1-7, 2008.
[3] Celebi, E. and Fuller, J.D., "A model for efficient consumer pricing schemes in electricity markets." IEEE Transactions on Power Systems, 22(1): p. 60-67, 2007.
[4] Dütschke, E. and Paetz, A.-G., "Dynamic electricity pricing—Which programs do consumers prefer?" Energy Policy, 59: p. 226-234, 2013.
[5] Fahrioglu, M. and Alvarado, F.L. "Designing cost effective demand management contracts using game theory." Paper presented at Power Engineering Society 1999 Winter Meeting, IEEE, 1: p. 427-432, 1999.
[6] Fahrioglu, M. and Alvarado, F.L., "Using utility information to calibrate customer demand management behavior models." IEEE Transactions on Power Systems, 16(2): p. 317-322, 2001.
[7] Flath, C.M. "An optimization approach for the design of time-of-use rates." Paper presented at Industrial Electronics Society, IECON 2013-39th Annual Conference of the IEEE: p. 4727-4732, 2013.
[8] Goldman, C. et al. "Does Real-Time Pricing Deliver Demand Response? A Case Study of Niagara Mohawk’s Large Customer RTP Tariff." Paper presented at Proceedings of the ACEEE 2004 Summer Study on Energy Efficiency in Buildings, 2004.
[9] Kirschen, D.S., "Demand-side view of electricity markets." IEEE Transactions on Power Systems, 18(2): p. 520-527, 2003.
[10] Marler, R.T. and Arora, J.S., "Function-transformation methods for multi-objective optimization." Engineering Optimization, 37(6): p. 551-570, 2005.
[11] Moezzi, M. et al. "Real time pricing and the real live firm." Paper presented at 2004 ACEEE Summer Study on Energy Efficiency in Buildings,Pacific Grove, CA, 2004.
[12] Nazar, N., Abdullah, M., Hassan, M., and Hussin, F. "Time-based electricity pricing for Demand Response implementation in monopolized electricity market." Paper presented at 2012 IEEE Student Conference on Research and Development (SCOReD): p. 178-181, 2012.
[13] Palensky, P. and Dietrich, D., "Demand side management: Demand response, intelligent energy systems, and smart loads." IEEE Transactions on Industrial Informatics, 7(3): p. 381-388, 2011.
[14] Pinson, P. and Madsen, H., "Benefits and challenges of electrical demand response: A critical review." Renewable and Sustainable Energy Reviews, 39: p. 686-699, 2014.
[15] Samadi, P. et al. "Optimal real-time pricing algorithm based on utility maximization for smart grid." Paper presented at 2010 First IEEE International Conference on Smart Grid Communications (SmartGridComm): p. 415-420, 2010.
[16] Shariatzadeh, F., Mandal, P., and Srivastava, A.K., "Demand response for sustainable energy systems: A review, application and implementation strategy." Renewable and Sustainable Energy Reviews, 45: p. 343-350, 2015.
[17] Strbac, G., "Demand side management: Benefits and challenges." Energy policy, 36(12): p. 4419-4426, 2008.
[18] Wang, H.F., "Chap 8. FOUNDATION OF MODA." in Multicriteria Decision Analysis: From Certainty to Uncertainty, Tsang Hai Publishing, 2004.
[19] Wu, Q., Wang, L., and Cheng, H. "Research of TOU power price based on multi-objective optimization of DSM and costs of power consumers." Paper presented at Proceedings of the 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies, 2004(DRPT 2004), 1: p. 343-348, 2004.
[20] Yang, L., Dong, C., Wan, C.J., and Ng, C.T., "Electricity time-of-use tariff with consumer behavior consideration." International Journal of Production Economics, 146(2): p. 402-410, 2013.
[21] Yang, P., Tang, G., and Nehorai, A., "A game-theoretic approach for optimal time-of-use electricity pricing." IEEE Transactions on Power Systems, 28(2): p. 884-892, 2013.
[22] Zhang, Q. and Li, J. "Demand response in electricity markets: A review." Paper presented at 2012 9th International Conference on the European Energy Market (EEM): p. 1-8, 2012.
[23] Bureau of Energy, Ministry of Economic Affair, Taiwan. Energy Monthly (2014 May), p.19-24, 2014. Retrieved 2015.03.05, from energymonthly.tier.org.tw/outdateorder.asp?ReportIssue=201405.
[24] Credit Suisse. Global Wealth Report 2014, p.55, 2015. Retrieved 2015.03.25, from www.credit-suisse.com/ch/en/news-and-expertise/research/credit-suisse-research-institute/publications.html.
[25] Enerdata. Global Energy Statistical Yearbook 2014, 2015. Retrieved 2015.05.17, from yearbook.enerdata.net.
[26] Industrial Technology Research Institute. Taiwan 2050 Calculator, 2014. Retrieved 2015.02.02, from my2050.twenergy.org.tw.
[27] Ontario Energy Board. Electricity Time-of-use Price Periods, 2015. Retrieved 2015.05.20, from www.ontarioenergyboard.ca/OEB/Consumers/Electricity/Electricity+Prices.
[28] Taiwan Power Company. 2014 Taiwan Power Company Sustainability Report, 2015. Retrieved 2015.03.05, from www.taipower.com.tw/UpFile/CompanyENFile/2014.pdf.
[29] Taiwan Power Company. Disclosure of Information, 2014. Retrieved 2015.02.02, from www.taipower.com.tw/content/new_info/new_info01.aspx.
[30] U.S. Department of Energy. Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them: A Report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005, 2006. Retrieved 2016.03.13, from www.energy.gov/oe/downloads/benefits-demand-response-electricity-markets-and-recommendations-achieving-them-report.
[31] United Nations. Framework Convention on Climate Change, 2014. Retrieved 2015.05.17, from unfccc.int/essential_background/convention/items/6036.php.
[32] United Nations Industrial Development Organization and Renewable Energy and Energy Efficiency Partnership. "Module 15. Demand Side Management." in the training package on Sustainable Energy Regulation and Policymaking for Africa, 2005. Retrieved 2015.03.10, from www.unido.org/fileadmin/import/83268_Module15.pdf.