Key success factors for demand response implementation: A hybrid multi-criteria decision making approach

Document Type : Research Paper

Authors

Department of Industrial Management and Information Technology, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran

Abstract

Today’s societies need more electricity for sustainable development. But the faster growth in demand than supply has led to governments to face the challenge of secure power provision. Demand response (DR) is a clean and cheap way to overcome this challenge. Many factors contribute to the success of DR programs. These factors have also complex and mutual relationships that make it hard to manage all of them. This study tries to determine the role of factors in success of DR programs and identify the factors that have more leverage effect in this regard. This research integrate Analytic Network Process (ANP) and Decision Making Trial and Evaluation Laboratory (DEMATEL) method to overcome the traditional ANP weakness that assumes influential degrees are equal. The proposed model can assess the interrelationship between the factors and provide a cause-effect diagram to evaluate the implementation policies, as well. The results show that, contrary to current efforts, political and cultural factors are more effective than technological ones.

Keywords

Main Subjects


Asano, H., Takahashi, M., Ymaguchi, N. (2011). Market potential and development of automated demand response system. Paper presented at the Power and Energy Society General Meeting, 2011 IEEE.
Babar, M., Nyugen, P., Cuk, V., Kamphuis, I. R., Bongaerts, M., Hanzelka, Z. (2016). The rise of AGILE demand response: Enabler and foundation for change. Renewable and Sustainable Energy Reviews, 56, 686-693.
Balta-Ozkan, N., Davidson, R., Bicket, M., Whitmarsh, L. (2013). Social barriers to the adoption of smart homes. Energy Policy, 63, 363-374.
Borlase, S. (2016). Smart grids: infrastructure, technology, and solutions: CRC press.
Brown, M. A. (2001). Market failures and barriers as a basis for clean energy policies. Energy Policy, 29(14), 1197-1207.
Brubaker, E. R. (1975). Free ride, free revelation, or golden rule? The Journal of Law and Economics, 18(1), 147-161.
Büyüközkan, G., Güleryüz, S. (2016). An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. International Journal of Production Economics, 182, 435-448.
Cappers, P. (2014). Market and policy barriers for demand response providing ancillary services in US markets.
Ceseña, E. A. M., Mancarella, P. (2014). Distribution network reinforcement planning considering demand response support. Paper presented at the Power Systems Computation Conference (PSCC), 2014.
Chai, K.-H., Yeo, C. (2012). Overcoming energy efficiency barriers through systems approach—a conceptual framework. Energy Policy, 46, 460-472.
Chan, D., Cameron, M., Yoon, Y. (2017). Key success factors for global application of micro energy grid model. Sustainable Cities and Society, 28, 209-224.
Chen, J.-K., Chen, I.-S. (2010). Using a novel conjunctive MCDM approach based on DEMATEL, fuzzy ANP, and TOPSIS as an innovation support system for Taiwanese higher education. Expert Systems with Applications, 37(3), 1981-1990.
Chiu, W.-Y., Tzeng, G.-H., Li, H.-L. (2013). A new hybrid MCDM model combining DANP with VIKOR to improve e-store business. Knowledge-Based Systems, 37, 48- 61.
Coalition, S. S. E. D. (2017). Explicit demand response in europe-mapping the markets 2017. SEDC: Brussels, Belgium.
Commission, E. (2014). Integration of renewable energy in Europe (pp. 7-8).
Commission, F. E. R. (2006). Regulatory Commission Survey on Demand Response and Time Based Rate Programs/Tariffs: August.
Corbin, A. L. (1919). Legal analysis and terminology. Yale Lj, 29, 163.
Cordella, A. (2006). Transaction costs and information systems: does IT add up? Journal of information technology, 21(3), 195-202.
Cui, B., Wang, S., Xue, X. (2014). Effects and performance of a demand response strategy for active and passive building cold storage. Energy Procedia, 61, 564-567.
Cutter, E., Woo, C., Kahrl, F., Taylor, A. (2012). Maximizing the value of responsive load. The Electricity Journal, 25(7), 6-16.
Darby, S. (2010). Smart metering: what potential for householder engagement? Building Research & Information, 38(5), 442-457.
Darby, S. J., McKenna, E. (2012). Social implications of residential demand response in cool temperate climates. Energy Policy, 49, 759-769.
Date, J., Athienitis, A. K., Fournier, M. (2015). A study of temperature set point strategies for peak power reduction in residential buildings. Energy Procedia, 78, 2130-2135.
Delmas, M. A., Fischlein, M., Asensio, O. I. (2013). Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012. Energy Policy, 61, 729-739.
Dulleck, U., Kaufmann, S. (2004). Do customer information programs reduce household electricity demand?—the Irish program. Energy Policy, 32(8), 1025-1032.
Dütschke, E., Paetz, A.-G. (2013). Dynamic electricity pricing—Which programs do consumers prefer? Energy Policy, 59, 226-234.
Energy, U. D. o. (2003). “Grid 2030”—A National Vision for Electricity's Second 100 Years.
Faruqui, A., Sergici, S. (2010). Household response to dynamic pricing of electricity: a survey of 15 experiments. Journal of regulatory Economics, 38(2), 193-225.
Faruqui, A., Sergici, S. (2013). Arcturus: international evidence on dynamic pricing. The Electricity Journal, 26(7), 55-65.
Faruqui, A., Sergici, S., Sharif, A. (2010). The impact of informational feedback on energy consumption—A survey of the experimental evidence. Energy, 35(4), 1598-1608.
 
Gans, W., Alberini, A., Longo, A. (2013). Smart meter devices and the effect of feedback on residential electricity consumption: Evidence from a natural experiment in Northern Ireland. Energy Economics, 36, 729-743.
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.
Gerpott, T. J., Paukert, M. (2013). Determinants of willingness to pay for smart meters: An empirical analysis of household customers in Germany. Energy Policy, 61, 483-495.
Good, N., Ellis, K. A., Mancarella, P. (2017). Review and classification of barriers and enablers of demand response in the smart grid. Renewable and Sustainable Energy Reviews, 72, 57-72.
Greening, L. A. (2010). Demand response resources: Who is responsible for implementation in a deregulated market? Energy, 35(4), 1518-1525.
Gyamfi, S., Krumdieck, S., Urmee, T. (2013). Residential peak electricity demand response—Highlights of some behavioural issues. Renewable and Sustainable Energy Reviews, 25, 71-77.
Haider, H. T., See, O. H., Elmenreich, W. (2016). A review of residential demand response of smart grid. Renewable and Sustainable Energy Reviews, 59, 166-178.
Haring, T. W., Kirschen, D. S., Andersson, G. (2015). Incentive compatible imbalance settlement. IEEE Transactions on Power Systems, 30(6), 3338-3346.
He, X., Keyaerts, N., Azevedo, I., Meeus, L., Hancher, L., Glachant, J.-M. (2013). How to engage consumers in demand response: A contract perspective. Utilities Policy, 27, 108-122.
Hu, Z., Kim, J.-h., Wang, J., Byrne, J. (2015). Review of dynamic pricing programs in the US and Europe: Status quo and policy recommendations. Renewable and Sustainable Energy Reviews, 42, 743-751.
Karakaya, E., Hidalgo, A., Nuur, C. (2014). Diffusion of eco-innovations: A review. Renewable and Sustainable Energy Reviews, 33, 392-399.
Khan, A. A., Razzaq, S., Khan, A., Khursheed, F. (2015). HEMSs and enabled demand response in electricity market: An overview. Renewable and Sustainable Energy Reviews, 42, 773-785.
Khan, R. H., Khan, J. Y. (2013). A comprehensive review of the application characteristics and traffic requirements of a smart grid communications network. Computer Networks, 57(3), 825-845.
Kim, J.-H., Shcherbakova, A. (2011). Common failures of demand response. Energy, 36(2), 873-880.
Kowalska-Pyzalska, A. (2016). What makes consumers adopt to innovative energy services in the energy market? : Hugo Steinhaus Center, Wroclaw University of Technology.
Li, X. H., Hong, S. H. (2014). User-expected price-based demand response algorithm for a home-to-grid system. Energy, 64, 437-449.
Liu, C.-H., Tzeng, G.-H., Lee, M.-H. (2012). Improving tourism policy implementation– The use of hybrid MCDM models. Tourism Management, 33(2), 413-426.
 
Liu, H.-C., You, J.-X., Zhen, L., Fan, X.-J. (2014). A novel hybrid multiple criteria decision making model for material selection with target-based criteria. Materials & Design, 60, 380-390.
Ma, J., Deng, J., Song, L., Han, Z. (2014). Incentive mechanism for demand side management in smart grid using auction. IEEE Transactions on Smart Grid, 5(3), 1379-1388.
Meyabadi, A. F., Deihimi, M. (2017). A review of demand-side management: reconsidering theoretical framework. Renewable and Sustainable Energy Reviews, 80, 367-379.
Moe, E. (2010). Energy, industry and politics: Energy, vested interests, and long-term economic growth and development. Energy, 35(4), 1730-1740.
 
Nguyen, D. T., Negnevitsky, M., De Groot, M. (2011). Pool-based demand response exchange—concept and modeling. IEEE Transactions on Power Systems, 26(3), 1677-1685.
Nikzad, M., Mozafari, B. (2014). Reliability assessment of incentive-and priced-based demand response programs in restructured power systems. International Journal of Electrical Power & Energy Systems, 56, 83-96.
Nilashi, M., Zakaria, R., Ibrahim, O., Majid, M. Z. A., Zin, R. M., & Farahmand, M. (2015). MCPCM: a DEMATEL-ANP-based multi-criteria decision-making approach to evaluate the critical success factors in construction projects. Arabian Journal for Science and Engineering, 40(2), 343-361.
Nolan, S., O’Malley, M. (2015). Challenges and barriers to demand response deployment and evaluation. Applied Energy, 152, 1-10.
Oh, H., Thomas, R. J. (2008). Demand-side bidding agents: Modeling and simulation.
 
IEEE Transactions on Power Systems, 23(3), 1050-1056.
 
Ozaki, R. (2011). Adopting sustainable innovation: what makes consumers sign up to green electricity? Business Strategy and the Environment, 20(1), 1-17.
Parkhill, K., Demski, C., Butler, C., Spence, A., Pidgeon, N. (2013). Transforming the UK energy system: public values, attitudes and acceptability: synthesis report.
 
Paterakis, N. G., Erdinç, O., Catalão, J. P. (2017). An overview of Demand Response: Key-elements and international experience. Renewable and Sustainable Energy Reviews, 69, 871-891.
Pinson, P., Madsen, H. (2014). Benefits and challenges of electrical demand response: A critical review. Renewable and Sustainable Energy Reviews, 39, 686-699.
Raghavan, S. S., Khaligh, A. (2012). Impact of plug-in hybrid electric vehicle charging on a distribution network in a smart grid environment. Paper presented at the Innovative Smart Grid Technologies (ISGT), 2012 IEEE PES.
Rassenti, S. J., Smith, V. L., Wilson, B. J. (2002). Demand-side bidding will reduce the level and volatility of electricity prices. The Independent Review, 6(3), 441-445.
Roozbehani, M., Dahleh, M. A., Mitter, S. K. (2012). Volatility of power grids under real- time pricing. IEEE Transactions on Power Systems, 27(4), 1926-1940.
Saaty, T. (1996). Decision making with dependence and feedback: The analytical hierarchy process. Pittsburgh: RWS.
Samadi, P., Mohsenian-Rad, H., Schober, R., Wong, V. W. (2012). Advanced demand side management for the future smart grid using mechanism design. IEEE Transactions on Smart Grid, 3(3), 1170-1180.
Shariatzadeh, F., Mandal, P., Srivastava, A. K. (2015). Demand response for sustainable energy systems: A review, application and implementation strategy. Renewable and Sustainable Energy Reviews, 45, 343-350.
Sharifi, R., Fathi, S., Vahidinasab, V. (2017). A review on Demand-side tools in electricity market. Renewable and Sustainable Energy Reviews, 72, 565-572.
Shen, B., Ghatikar, G., Lei, Z., Li, J., Wikler, G., Martin, P. (2014). The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges. Applied Energy, 130, 814-823.
Shimomura, Y., Nemoto, Y., Akasaka, F., Chiba, R., Kimita, K. (2014). A method for designing customer-oriented demand response aggregation service. CIRP Annals- Manufacturing Technology, 63(1), 413-416.
Sorrell, S. (2015). Reducing energy demand: A review of issues, challenges and approaches. Renewable and Sustainable Energy Reviews, 47, 74-82.
Sorrell, S., O’Malley, E. (2004). The economics of energy efficiency. Books.
Spees, K., Lave, L. B. (2007). Demand response and electricity market efficiency. The Electricity Journal, 20(3), 69-85.
Srivastava, A., Van Passel, S., Laes, E. (2018). Assessing the success of electricity demand response programs: A meta-analysis. Energy Research & Social Science, 40, 110-117.
Stern, P. C. (2000). New environmental theories: toward a coherent theory of environmentally significant behavior. Journal of social issues, 56(3), 407-424.
Strbac, G. (2008). Demand side management: Benefits and challenges. Energy Policy, 36(12), 4419-4426.
Tavanir, M. o. i. t. a. s. o. o. (2016 ). Statistical report on the 47years of activities of Iran electric power industry (1968-2015), . Tehran, Iran:: Tavanir Holding Company.
Thollander, P., Palm, J., Rohdin, P. (2010). Categorizing barriers to energy efficiency–an interdisciplinary perspective Energy Efficiency: InTech.
Torriti, J. (2012). Price-based demand side management: Assessing the impacts of time-of- use tariffs on residential electricity demand and peak shifting in Northern Italy. Energy, 44(1), 576-583.
Torriti, J., Hassan, M. G., Leach, M. (2010). Demand response experience in Europe: Policies, programmes and implementation. Energy, 35(4), 1575-1583.
Tsai, S. B. (2018). Using the DEMATEL model to explore the job satisfaction of research and development professionals in china's photovoltaic cell industry. Renewable and Sustainable Energy Reviews, 81, 62-68.
Tsai, W.-H., Hsu, W. (2010). A novel hybrid model based on DEMATEL and ANP for selecting cost of quality model development. Total Quality Management, 21(4), 439- 456.