Investigating the Effect of Using Renewable Resources on Electricity Supply Demand Presenting a two-objective Mathematical Model

Document Type : Original Article

Authors

Department of Industrial Engineering, Sadjad University of Technology, Mashhad, Iran

Abstract

The increasing demand for electricity and the cost of using fossil fuels has led to the use of renewable resources and the development of clean energy as a means of securing energy and counteracting the negative effects of climate change. Consequently, the presence of renewable energies has increased the complexity of planning for electricity supply, which is one of the most important issues in the energy supply chain. In this paper, we present a two-objective mixed-integer linear programming model that has environmental and economic objectives, so that we can measure the impact of the use of renewable resources on the amount Earnings from energy sales, polluting emissions and fuel consumption of power plants. Since the proposed model follows two objectives, the ε-constraint method is used to obtain Pareto solutions. Finally, according to the solutions, we have concluded that high capacity plants have a larger share in supplying the grid demand either with an economic approach or with an environmental approach, and low capacity power plants are only used to increase network reliability and to cope with fluctuations in demand. At the same time, the use of large-scale renewable resources, in addition to reducing emissions, will increase the profits from the sale of electricity. In addition, the results show that the development of the use of microgrids and distributed generation is a suitable approach for supplying electricity demand.

Keywords


[1] J. Silvente, G. M. Kopanos, E. N. Pistikopoulos, A. Espuña, A rolling horizon optimization framework for the simultaneous energy supply and demand planning in microgrids, Applied Energy, vol. 155, pp. 485 – 501, 2015.
[2] C. Papapostolou, E. Kondili, J. K. Kaldellis, Energy Supply Chain Optimization: Special Considerations for the Solution of the Energy Planning Problem, 24th European Symposium on Computer Aided Process Engineering, Budapest, Hungary, June 15-18, 2014.
[3] C. Papapostolou, E. Kondili, I. K. Kaldellis, W. G.  Früh, Energy Supply Chain modeling for the optimization of a large-scale energy planning problem, 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, Copenhagen, Denmark, 31 May – 4 June, 2015.
[4] C. Zhang, Y. L. Wei, P. F. Cao, M. C. Lin, Energy storage system: Current studies on batteries and power condition system, Renewable and Sustainable Energy Reviews, vol. 82, pp. 3091 – 3109, 2018.
[5] L. Wang, C. Singh, Multicriteria Design of Hybrid Power Generation Systems Based on a Modified Particle Swarm Optimization Algorithm, IEEE TRANSACTIONS ON ENERGY CONVERSION, vol. 24, pp. 163 – 172, 2009.
[6] O. Akgul, N. Mac Dowell, L. G. Papageorgiou, N. Shah, A mixed integer nonlinear programming (MINLP) supply chain optimization framework for carbon negative electricity generation using biomass to energy with CCS (BECCS) in the UK, International Journal of Greenhouse Gas Control, vol. 28, pp. 189 – 202, 2014.
[7] S. Y. Balaman, H. Selim, A fuzzy multiobjective linear programming model for design and management of anaerobic digestion-based bioenergy supply chains, Energy, vol. 74, pp. 928 – 940, 2014.
[8] C. Cambero, T. Sowlati, incorporating social benefits in multi-objective optimization of forestbased bioenergy and biofuel supply chains, Applied Energy, vol. 178, pp. 721 – 735, 2016.
[9] M. Pérez-Fortes, J. M. Laínez-Aguirre, P. Arranz-Piera, E. Velo, L. Puigjaner, Design of regional and sustainable bio-based networks for electricity generation using a multi-objective MILP approach, Energy, vol. 44, pp. 79 – 95, 2012.
[10] J. Ren, D. An, H. Liang, L. Dong, Z. Gao, Y. Geng, Q. Zhu, S. Song, W. Zhao, Life cycle energy and CO2 emission optimization for biofuel supply chain planning under uncertainties, Energy, vol. 103, pp. 151 – 166, 2016.
[11] N. Shabani, S. Sowlati, M. Ouhimmou, M. Ronnqvist, Tactical supply chain planning for a forest biomass power plant under supply uncertainty, Energy, vol. 78, pp. 346 – 355, 2014.
[12] F. d’Amore, F. Bezzo, Strategic optimization of biomass-based energy supply chains for sustainable mobility, Computer and Chemical Engineering, vol. 87, pp. 68 – 81, 2016.
[13] M. Zamarripa, J. C. Vasquez, J. M. Guerrero, M. Graells, Detailed Operation Scheduling and Control for Renewable Energy Powered Microgrids, 21st European Symposium on Computer Aided Process Engineering, 2011.
[14] E. Zondervan, I.E. Grossmann, A.B. de Haan, Energy optimization in the process industries: Unit Commitment at systems level, 20st European Symposium on Computer Aided Process Engineering, 2010.
[15] M. Carrión, J. M. Arroyo, A Computationally Efficient Mixed-Integer Linear Formulation for the Thermal Unit Commitment Problem, IEEE TRANSACTIONS ON POWER SYSTEMS, vol. 21, pp. 1371 – 1378, 2006.
[16] S. Y. Balaman, H. Selim, A network design model for biomass to energy supply chains with anaerobic digestion systems, Applied Energy, vol. 130, pp. 289 – 304, 2014.
[17] T. Niknam, A. Khodaei, F. Fallahi, A new decomposition approach for the thermal unit commitment problem, Applied Energy, vol. 86, pp. 1668 – 1674, 2009.