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The application of multiobjective models and methods in a vast range of problems in the energy sector has been a consolidated practice in the last four decades. The need to consider explicitly multiple axes of evaluation of the merits of solutions in decision processes, generally involving large investments as well as social and environmental impacts, has led to the recognition of the potential benefits of multiobjective optimization approaches. Trends such as the increasing share of renewable sources in the energy generation matrix, the evolution towards smart grids involving the deployment of information and communication technologies, the dissemination of electric mobility and the consumer empowerment by means of the utilization of demand-side resources introduce challenging problems for which the capability of multiobjective models and methods to explore and provide assistance in the appraisal of well-balanced solutions is of utmost importance. This chapter aims to offer a broad view of some of the most challenging problems concerning the application of multiobjective optimization models and methods in the energy sector, with focus on electricity smart grids, outlining promising research avenues in problems of planning and operational nature.
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Alves, M. J., & Antunes, C. H. (2018). A semivectorial bilevel programming approach to optimize electricity dynamic time-of-use retail pricing. Computers & Operations Research, 92, 130–144. CrossRef
Antunes, C. H., & Henriques, C. O. (2016). Multi-objective optimization and multi-criteria analysis models and methods for problems in the energy sector. In M. Ehrgott, J. R. Figueira, & S. Greco (Eds.), Multiple criteria decision analysis: State of the art surveys (2nd ed., Chapter 25, pp. 1067–1165). Springer.
Carpinelli, G., Mottola, F., Proto, D., & Russo, A. (2017). A multi-objective approach for microgrid scheduling. IEEE Transactions on Smart Grid, 8(5), 2109–2118. CrossRef
Chiu, W. Y., Sun, H., & Poor, H. V. (2015). A multiobjective approach to multimicrogrid system design. IEEE Transactions on Smart Grid, 6(5), 2263–2272. CrossRef
Cui, Y., Geng, Z., Zhu, Q., & Han, Y. (2017). Review: Multi-objective optimization methods and application in energy saving. Energy, 125, 681–704. CrossRef
Farzin, H., Fotuhi-Firuzabad, M., & Moeini-Aghtaie, M. (2017). A stochastic multi-objective framework for optimal scheduling of energy storage systems in microgrids. IEEE Transactions on Smart Grid, 8(1), 117–127. CrossRef
Gao, Y., Hu, X., Yang, W., Liang, H., & Li, P. (2017). Multi-objective bilevel coordinated planning of distributed generation and distribution network frame based on multiscenario technique considering timing characteristics. IEEE Transactions on Sustainable Energy, 8(4), 1415–1429. CrossRef
Li, R., Wang, W., & Xia, M. (2018). Cooperative planning of active distribution system with renewable energy sources and energy storage systems. IEEE Access, 6, 5916–5926. CrossRef
Liu, J., & Li, J. (2015). A bi-level energy-saving dispatch in smart grid considering interaction between generation and load. IEEE Transactions on Smart Grid, 6(3), 1443–1452. CrossRef
Muralitharan, K., Sakthivel, R., & Shi, Y. (2016). Multiobjective optimization technique for demand side management with load balancing approach in smart grid. Neurocomputing, 177, 110–119. CrossRef
Oliveira, C., Coelho, D., & Antunes, C. H. (2016). Coupling input–output analysis with multiobjective linear programming models for the study of economy–energy–environment–social (e3s) trade-offs: A review. Annals of Operations Research, 247(2), 471–502. CrossRef
Safdarian, A., Fotuhi-Firuzabad, M., & Lehtonen, M. (2014). A distributed algorithm for managing residential demand response in smart grids. IEEE Transactions on Industrial Informatics, 10(4), 2385–2393. CrossRef
Soares, A., Gomes, A., Henggeler Antunes, C., & Oliveira, C. (2017). A customized evolutionary algorithm for multiobjective management of residential energy resources. IEEE Transactions on Industrial Informatics, 13(2), 492–501.
Zhang, B., Dehghanian, P., & Kezunovic, M. (2019). Optimal allocation of PV generation and battery storage for enhanced resilience. IEEE Transactions on Smart Grid, 10(1), 535–545.
Zhang, X., Wang, H., Peng, J., Liu, Y., Wang, G., & Jiang, H. (2018). GPNBI inspired MOSDE for electric power dispatch considering wind energy penetration. Energy, 144, 404–419. CrossRef
- Multiobjective Optimization in the Energy Sector: Selected Problems and Challenges
Carlos Henggeler Antunes
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