Optimal Energy Resource Planning and Combined Heat and Power Sizing in a Residential Area to Supply Electrical and Thermal Demand in a Reconfigured Power Grid | ||
| Renewable Energy Research and Applications | ||
| دوره 4، شماره 1، فروردین 2023، صفحه 113-123 اصل مقاله (1.07 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22044/rera.2022.11568.1099 | ||
| نویسندگان | ||
| Seyed E. Hoseini؛ M. Simab* ؛ B. Bahmani-Firouzi | ||
| Department of Electrical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran. | ||
| چکیده | ||
| The argument of power systems planning in home microgrids has become one of the burning topics in optimization studies today among the researchers. Since the installation and use of high-capacity energy sources in power systems have many limitations and constraints, so part of the perspective of power systems studies tends to operate residential microgrids. For this purpose, in this paper, operation planning is based on a residential microgrid consisting of combined heat and power (CHP), heat storage tank and boiler, and when possible, surplus electricity is sold to the upstream network to generate revenue. One of the innovations of this paper is the use of the exergy function to complete the optimization and, in practice, combine energy with economics. Other objective functions of this paper are to discuss the reduction of carbon dioxide in the air and the cost of operation. Energy management and planning in this home microgrid is tested with different capacities and types of CHPs, so that the home operator can choose the best mode to use. The multi-stage decision based dynamic programing (MSD-DP) optimization approach is used to minimize the operation costs of proposed framework. The most important innovation of this paper is the use of exergy function for energy management in a residential complex where CHP can also be used to generate electricity and heat simultaneously. Therefore, determining the capacity of CHP and the possibility of exchanging electricity with the upstream network can be mentioned as other innovations of this research. | ||
| کلیدواژهها | ||
| Reconfiguration؛ Planning؛ Residential Microgrid؛ Optimization | ||
| مراجع | ||
|
[1] Aziz, T., Waseem, M., Liu, S., and Lin, Z. (2022). Two-Stage MILP Model for Optimal Skeleton-Network Reconfiguration of Power System for Grid-Resilience Enhancement. Journal of Energy Engineering, 148(1), 04021060.
[2] Aziz, T., Lin, Z., Waseem, M., and Liu, S. (2021). Review on optimization methodologies in transmission network reconfiguration of power systems for grid resilience. International Transactions on Electrical Energy Systems, 31(3), e12704.
[3] Kahouli, O., Alsaif, H., Bouteraa, Y., Ben Ali, N., and Chaabene, M. (2021). Power System Reconfiguration in Distribution Network for Improving Reliability Using Genetic Algorithm and Particle Swarm Optimization. Applied Sciences, 11(7), 3092.
[4] Li, S., Wang, L., Gu, X., Zhao, H., and Sun, Y. (2022). Optimization of loop-network reconfiguration strategies to eliminate transmission line overloads in power system restoration process with wind power integration. International Journal of Electrical Power and Energy Systems, 134, 107351.
[5] Alayi, R., Seydnouri, S. R., Jahangeri, M., and Maarif, A. (2021). Optimization, Sensitivity Analysis, and Techno-Economic Evaluation of a Multi-Source System for an Urban Community: a Case Study. Renewable Energy Research and Application.
[6] Nikoukar, J., Momen, S., and Gandomkar, M. (2021). Determining the Optimal Arrangement of Distributed Generations in Microgrids to Supply the Electrical and Thermal Demands Using the Improved Shuffled Frog Leaping Algorithm. Renewable Energy Research and Applications.
[7] Beiranvand, A., Ehyaei, M. A., Ahmadi, A., and Silvaria, J. L. (2020). Energy, exergy, and economic analyses and optimization of solar organic Rankine cycle with multi-objective particle swarm algorithm. Renewable Energy Research and Application.
[8] Sun, T., Lu, J., Li, Z., Lubkeman, D. L., and Lu, N. (2017). Modeling combined heat and power systems for microgrid applications. IEEE Transactions on Smart Grid, 9(5), 4172-4180.
[9] Liu, N., Wang, J., and Wang, L. (2017). Distributed energy management for interconnected operation of combined heat and power-based microgrids with demand response. Journal of Modern Power Systems and Clean Energy, 5(3), 478-488.
[10] Nazari-Heris, M., Mohammadi-Ivatloo, B., Gharehpetian, G. B., and Shahidehpour, M. (2018). Robust short-term scheduling of integrated heat and power microgrids. IEEE Systems Journal, 13(3), 3295-3303.
[11] Misaghian, M. S., Saffari, M., Kia, M., Heidari, A., Shafie-khah, M., and Catalão, J. P. S. (2018). Tri-level optimization of industrial microgrids considering renewable energy sources, combined heat and power units, thermal and electrical storage systems. Energy, 161, 396-411.
[12] Romero-Quete, D. and Garcia, J. R. (2019). An affine arithmetic-model predictive control approach for optimal economic dispatch of combined heat and power microgrids. Applied energy, 242, 1436-1447.
[13] Bornapour, M., Hooshmand, R. A., Khodabakhshian, A., &Parastegari, M. (2016). Optimal coordinated scheduling of combined heat and power fuel cell, wind, and photovoltaic units in micro grids considering uncertainties. Energy, 117, 176-189.
[14] Zhang, G., Cao, Y., Cao, Y., Li, D., and Wang, L. (2017). Optimal energy management for microgrids with combined heat and power (CHP) generation, energy storages, and renewable energy sources. Energies, 10(9), 1288.
[15] Wang, X., Chen, S., Zhou, Y., Wang, J., and Cui, Y. (2018). Optimal dispatch of microgrid with combined heat and power system considering environmental cost. Energies, 11(10), 2493.
[16] Iris, Ç. and Lam, J. S. L. (2021). Optimal energy management and operations planning in seaports with smart grid while harnessing renewable energy under uncertainty. Omega, 103, 102445.
[17] Naseri, A., Fazlikhani, M., Sadeghzadeh, M., Naeimi, A., Bidi, M., and Tabatabaei, S. H. (2020). Thermodynamic and exergy analyses of a novel solar-powered CO2 transcritical power cycle with recovery of cryogenic LNG using stirling engines. Renewable Energy Research and Application, 1(2), 175-185.
[18] Mirlohi, S. M., Sadeghzadeh, M., Kumar, R., and Ghassemieh, M. (2020). Implementation of a Zero-energy Building Scheme for a Hot and Dry Climate Region in Iran (a Case Study, Yazd). Renewable Energy Research and Application, 1(1), 65-74.
[19] Lai, F., Wang, S., Liu, M., and Yan, J. (2020). Operation optimization on the large-scale CHP station composed of multiple CHP units and a thermocline heat storage tank. Energy Conversion and Management, 211, 112767.
[20] Zhang, H., Zhang, Q., Gong, T., Sun, H., and Su, X. (2018). Peak load regulation and cost optimization for microgrids by installing a heat storage tank and a portable energy system. Applied Sciences, 8(4), 567.
[21] Li, Y., Sun, F., Zhang, Q., Chen, X., and Yuan, W. (2020). Numerical Simulation Study on Structure Optimization and Performance Improvement of Hot Water Storage Tank in CHP System. Energies, 13(18), 4734.
[22] Liu, M., Wang, S., and Yan, J. (2021). Operation scheduling of a coal-fired CHP station integrated with power-to-heat devices with detail CHP unit models by particle swarm optimization algorithm. Energy, 214, 119022.
[23] Jiang, H., Xu, L., Li, J., Hu, Z., and Ouyang, M. (2019). Energy management and component sizing for a fuel cell/battery/super-capacitor hybrid powertrain based on two-dimensional optimization algorithms. Energy, 177, 386-396.
[24] Chen, H., Zhang, Z., Guan, C., and Gao, H. (2020). Optimization of sizing and frequency control in battery/super-capacitor hybrid energy storage system for fuel cell ship. Energy, 197, 117285.
[25] Thomas, B. (2008). Benchmark testing of Micro-CHP units. Applied Thermal Engineering, 28(16), 2049-2054.
| ||
|
آمار تعداد مشاهده مقاله: 2,531 تعداد دریافت فایل اصل مقاله: 803 |
||