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Demand response (DR) can improve the reliability and reduce the energy price. In this paper, we focus on Game Theory DR program which is one of the incentive-based DR programs. We incorporate DR into the DEESRD problem by formulating dynamic economic emission and spinning reserve dispatch with demand response (DEESRD-DR) problem. The objective of the DEESRD-DR is to minimize the energy and reserve costs, minimize the amount of emission and maximize the benefit of the generation company (GENCO). The optimal solutions of the DEESRD and DEESRD-DR problems can be obtained using artificial intelligent-based optimization techniques such as differential evolution, particle swarm optimization, artificial immune system, artificial bee colony, etc., however these methods give an open-loop optimal solution. The open-loop nature cannot deals with inaccuracies, modeling uncertainties and unexpected external disturbances where the power system components suffer from, therefore we have designed closed-loop solutions by model predictive control (MPC). The performance of the MPC has been investigated by applying the MPC strategy to the DEESRD and DEESRD-DR problems with test system consisting of five generating units and five customers.<\/jats:p>","DOI":"10.3233\/jifs-179074","type":"journal-article","created":{"date-parts":[[2019,4,2]],"date-time":"2019-04-02T13:47:02Z","timestamp":1554212822000},"page":"159-170","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Model predictive control of electric power and reserve dynamic dispatch including demand response"],"prefix":"10.1177","volume":"37","author":[{"given":"A.M.","family":"Shehata","sequence":"first","affiliation":[{"name":"Department of Mathematics, College of Sciences, University of Bisha, Bisha, Saudi Arabia"},{"name":"Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut, 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