{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:14:24Z","timestamp":1760242464186,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2017,8,23]],"date-time":"2017-08-23T00:00:00Z","timestamp":1503446400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Energies"],"abstract":"<jats:p>Retail energy providers (REPs) can employ different strategies such as offering demand response (DR) programs, participating in bilateral contracts, and employing self-generation distributed generation (DG) units to avoid financial losses in the volatile electricity markets. In this paper, the problem of setting dynamic retail sales price by a REP is addressed with a robust optimization technique. In the proposed model, the REP offers price-based DR programs while it faces uncertainties in the wholesale market price. The main contribution of this paper is using a robust optimization approach for setting the short-term dynamic retail rates for an asset-light REP. With this approach, the REP can decide how to participate in forward contracts and call options. They can also determine the optimal operation of the self-generation DG units. Several case studies have been carried out for a REP with 10,679 residential consumers. The deterministic approach and its robust counterpart are used to solve the problem. The results show that, with a slight decrease in the expected payoff, the REP can effectively protect itself against price variations. Offering time-variable retail rates also can increase the expected profit of the REPs.<\/jats:p>","DOI":"10.3390\/en10091245","type":"journal-article","created":{"date-parts":[[2017,8,23]],"date-time":"2017-08-23T11:32:27Z","timestamp":1503487947000},"page":"1245","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Dynamic Pricing for Demand Response Considering Market Price Uncertainty"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0638-7221","authenticated-orcid":false,"given":"Mohammad","family":"Fotouhi Ghazvini","sequence":"first","affiliation":[{"name":"GECAD\u2014Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development-Polytechnic of Porto (IPP), R. Dr. Ant\u00f3nio Bernardino de Almeida 431, 4200-072 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4172-4502","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Soares","sequence":"additional","affiliation":[{"name":"GECAD\u2014Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development-Polytechnic of Porto (IPP), R. Dr. Ant\u00f3nio Bernardino de Almeida 431, 4200-072 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5906-4744","authenticated-orcid":false,"given":"Hugo","family":"Morais","sequence":"additional","affiliation":[{"name":"Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark (DTU), Elektrovej, Building 326, DK-2800 Kgs. Lyngby, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3108-8880","authenticated-orcid":false,"given":"Rui","family":"Castro","sequence":"additional","affiliation":[{"name":"Instituto de Engenharia de Sistemas e Computadores\u2014Investiga\u00e7\u00e3o e Desenvolvimento\/Instituto Superior T\u00e9cnico (INESC-ID\/IST), University of Lisbon, 1049-001 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4560-9544","authenticated-orcid":false,"given":"Zita","family":"Vale","sequence":"additional","affiliation":[{"name":"GECAD\u2014Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development-Polytechnic of Porto (IPP), R. Dr. Ant\u00f3nio Bernardino de Almeida 431, 4200-072 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2105","DOI":"10.1109\/TPWRS.2007.907397","article-title":"Forward contracting and selling price determination for a retailer","volume":"22","author":"Conejo","year":"2007","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1016\/j.ijepes.2015.06.025","article-title":"Robust optimization based price-taker retailer bidding strategy under pool market price uncertainty","volume":"73","author":"Nojavan","year":"2015","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"ref_3","unstructured":"Eydeland, A., and Wolyniec, K. (2003). Energy and Power Risk Management, John Wiley & Sons, Inc."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.energy.2013.09.014","article-title":"Robust optimization based self scheduling of hydro-thermal Genco in smart grids","volume":"61","author":"Soroudi","year":"2013","journal-title":"Energy"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1418","DOI":"10.1109\/TPWRS.2010.2092793","article-title":"Offering strategy via robust optimization","volume":"26","author":"Baringo","year":"2011","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jup.2015.03.002","article-title":"Decision-making framework for supplying electricity from distributed generation-owning retailers to price-sensitive customers","volume":"37","author":"Khojasteh","year":"2015","journal-title":"Util. Policy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1808","DOI":"10.1109\/TPWRS.2010.2095431","article-title":"A stochastic-based decision-making framework for an electricity retailer: Time-of-use pricing and electricity portfolio optimization","volume":"26","author":"Hatami","year":"2011","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1705","DOI":"10.1002\/etep.2173","article-title":"A short-term optimal decision making framework of an electricity retailer considering optimized EVs charging model","volume":"26","author":"Badri","year":"2016","journal-title":"Int. Trans. Electr. Energy Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1016\/j.energy.2015.01.090","article-title":"Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market","volume":"82","author":"Faria","year":"2015","journal-title":"Energy"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.apenergy.2015.04.067","article-title":"A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers","volume":"151","author":"Soares","year":"2015","journal-title":"Appl. Energy"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1016\/j.apenergy.2016.11.024","article-title":"Optimal stochastic energy management of retailer based on selling price determination under smart grid environment in the presence of demand response program","volume":"187","author":"Nojavan","year":"2017","journal-title":"Appl. Energy"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1109\/TSG.2014.2376522","article-title":"Energy pricing and dispatch for smart grid retailers under demand response and market price uncertainty","volume":"6","author":"Wei","year":"2015","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1016\/j.apenergy.2015.06.059","article-title":"The design of a risk-hedging tool for virtual power plants via robust optimization approach","volume":"155","author":"Shabanzadeh","year":"2015","journal-title":"Appl. Energy"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1258","DOI":"10.1049\/iet-gtd.2015.0144","article-title":"Strategic scheduling of energy storage for load serving entities in locational marginal pricing market","volume":"10","author":"Fang","year":"2016","journal-title":"IET Gener. Transm. Distrib."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.enbuild.2017.03.020","article-title":"Demand response implementation in smart households","volume":"143","author":"Soares","year":"2017","journal-title":"Energy Build."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1926","DOI":"10.1109\/TPWRS.2012.2195037","article-title":"Volatility of power grids under real-time pricing","volume":"27","author":"Roozbehani","year":"2012","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_17","unstructured":"(2017, August 08). Appendix 5: Price Elasticity of Demand, Available online: https:\/\/www.aer.gov.au\/system\/files\/Ausgrid - Appendix 5 Price Elasticity of Demand - November 2015.pdf."},{"key":"ref_18","unstructured":"Danoun, O. (2016). Optimisation of the Energy Use in a Residential Environment, University of Gent."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.apenergy.2012.02.034","article-title":"Integrated day-ahead and hour-ahead operation model of discos in retail electricity markets considering DGs and CO2 emission penalty cost","volume":"95","author":"Ghadikolaei","year":"2012","journal-title":"Appl. Energy"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.epsr.2008.06.003","article-title":"Optimal selling price and energy procurement strategies for a retailer in an electricity market","volume":"79","author":"Hatami","year":"2009","journal-title":"Electr. Power Syst. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s10107-003-0396-4","article-title":"Robust discrete optimization and network flows","volume":"98","author":"Bertsimas","year":"2003","journal-title":"Math. Program."},{"key":"ref_22","unstructured":"(2017, August 08). GAMS 24.4. Available online: https:\/\/www.gams.com\/24.8\/docs\/releasenotes\/24.4.html."},{"key":"ref_23","unstructured":"(2012). GAMS software GmbH CPLEX 12. GAMS\u2014The Solver Manuals, GAMS Development Corporation."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.ijepes.2008.09.003","article-title":"Electricity price forecasting in deregulated markets: A review and evaluation","volume":"31","author":"Aggarwal","year":"2009","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1014","DOI":"10.1109\/TPWRS.2002.804943","article-title":"ARIMA models to predict next-day electricity prices","volume":"18","author":"Contreras","year":"2003","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1109\/TPWRS.2005.846054","article-title":"Day-ahead electricity price forecasting using the wavelet transform and ARIMA models","volume":"20","author":"Conejo","year":"2005","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1109\/TPWRS.2006.873409","article-title":"Day-ahead price forecasting of electricity markets by a new fuzzy neural network","volume":"21","author":"Amjady","year":"2006","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_28","unstructured":"(2017, May 22). PJM\u2014Energy Market. Available online: http:\/\/www.pjm.com\/markets-and-operations\/energy.aspx."},{"key":"ref_29","unstructured":"Schofield, J.R., Carmichael, R., Tindemans, S., Bilton, M., Woolf, M., and Strbac, G. (2017, August 08). Low Carbon London Project: Data from the Dynamic Time-of-Use Electricity Pricing Trial, 2013. Available online: https:\/\/discover.ukdataservice.ac.uk\/catalogue?sn=7857."},{"key":"ref_30","unstructured":"Northwest Energy Efficiency Alliance (NEEA) (2017, May 22). Regional Data Resources. Available online: http:\/\/neea.org\/resource-center\/regional-data-resources."}],"container-title":["Energies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1996-1073\/10\/9\/1245\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:43:07Z","timestamp":1760208187000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1996-1073\/10\/9\/1245"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,23]]},"references-count":30,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2017,9]]}},"alternative-id":["en10091245"],"URL":"https:\/\/doi.org\/10.3390\/en10091245","relation":{},"ISSN":["1996-1073"],"issn-type":[{"type":"electronic","value":"1996-1073"}],"subject":[],"published":{"date-parts":[[2017,8,23]]}}}