Mathematical modeling and optimal control of energy management in microgrids with combined heat and power
DOI:
https://doi.org/10.21638/spbu10.2024.402Abstract
The production and integration of renewable energy sources into microgrid systems have recently demonstrated significant growth due to their ability to meet growing electricity needs while having minimal impact on environmental pollution. Combined cooling, heating, and power (CCHP) systems, also known as trigeneration systems, are the most efficient and stable way to use energy, which has a wide range of applications. However, to increase energy efficiency and reduce overall operating costs of such systems, the development of a mathematical model and optimal control model for CCHP is required. This paper presents a review of known mathematical models and optimal control models that ensure cost reduction while meeting electricity, heating, and cooling needs. The problem of joint optimization of several efficiency criteria: electricity consumption from the grid, annual total costs, and carbon dioxide emissions is considered. The characteristics of CCHP systems obtained taking into account different exploitation strategies are compared with separate cooling, heating, and power systems.
Keywords:
combined cooling, heating and power systems, power generation unit, separated production, multi-objective optimization, evaluation criteria, following electrical load, following thermal load
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References
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Hemmati M., Ivatloo B. Day-ahead profit-based reconfigurable microgrid scheduling considering uncertain renewable generation and load demand in the presence of energy storage // Journal of Energy Storage. 2020. Vol. 28. Art. N 101161.
Naderi E., Shayeghi H. Sustainable energy scheduling of grid-connected microgrid using Monte Carlo estimation and considering main grid penetration level // International Journal on Technical and Physical Problems of Engineering. 2020. Vol. 12. N 1. P. 10–19.
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Cho H., Mago P. J., Luck R., Chamra L. M. Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme // Applied Energy. 2009. Vol. 86. P. 2540–2549.
Wang J. J., Jing Y. Y., Zhang C. F., Zhai Z. J. Performance comparison of combined cooling, heating and power system in different operation modes // Applied Energy. 2011. Vol. 88. Art. N 462131.
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Jing R., Wang M., Wang W., Brandon N., Li N., Chen J., Zhao Y., Economic and environmental multi-optimal design and dispatch of solid oxide fuel cell based CCHP system // Energy Conversion and Management. 2017. Vol. 154. P. 365–379.
Cao Y., Wang Q., Du J., Nojavan S., Jermsittiparsert K., Ghadimi N. Optimal operation of CCHP and renewable generation-based energy hub considering environmental perspective: An epsilon constraint and fuzzy methods // Sustainable Energy, Grids and Networks. 2019. Vol. 20. Art. N 100274.
Hou J., Wang J., Zhou Y., Lu X. Distributed energy systems: Multi-objective optimization and evaluation under different operational strategies // Journal of Clean Production. 2020. Art. N 124050.
Gao L., Hwang Y., Cao T. An overview of optimization technologies applied in combined cooling, heating and power systems // Renewable and Sustainable Energy Reviews. 2019. Vol. 114. Art. N 109344.
Abbasi M. H., Sayyaadi H., Tahmasbzadebaie M. A methodology to obtain the foremost type and optimal size of the prime mover of a CCHP system for a large-scale residential application // Applied Thermal Engineering. 2018. Vol. 135. P. 389–405.
Yan Y., Zhang C., Li K., Wang Z. An integrated design for hybrid combined cooling, heating and power system with compressed air energy storage // Applied Energy. 2018. Vol. 210. P. 1151–1166.
Chen X., Zhou H., Li W., Yu Zh., Gong G., Yan Y., Luo L., Wan Zh., Ding Y. Multi-criteria assessment and optimization study on 5 kW PEMFC based residential CCHP system // Energy Conversion and Management. 2018. Vol. 160. P. 384–395.
Song Z., Liu T., Lin Q. Multi-objective optimization of a solar hybrid CCHP system based on different operation modes // Energy. 2020. Vol. 206. Art. N 118125.
Deb K., Pratap A., Agarwal S., Meyarivan T. A fast and elitist multi-objective genetic algorithm: NSGA-II // IEEE Transaction of Evolutionary Computation. 2002. Vol. 6. P. 182–197.
Ren F., Wei Z., Zhai X. Multi-objective optimization and evaluation of hybrid CCHP systems for different building types// Energy. 2021. Vol. 215. Pt A. Art. N 119096.
Konak A., Coit D. W., Smith A. E. Multi-objective optimization using genetic algorithms: A tutorial // Reliability Engineering and System Safety. 2006. Vol. 91. P. 992–1007.
Dawes R., Corrigan B. Linear models in decision making // Psychological Bulletin. 1974. Vol. 81. N 2. P. 95–106.
References
Kim T. H., Shin H., Kim W. A parallel multi-period optimal scheduling algorithm in microgrids with energy storage systems using decomposed inter-temporal constraints. Energy, 2020, vol. 202, no. 1, art. no. 117669.
Hemmati M., Ivatloo B. Day-ahead profit-based reconfigurable microgrid scheduling considering uncertain renewable generation and load demand in the presence of energy storage. Journal of Energy Storage, 2020, vol. 28, art. no. 101161.
Naderi E., Shayeghi H. Sustainable energy scheduling of grid-connected microgrid using Monte Carlo estimation and considering main grid penetration level. International Journal on Technical and Physical Problems of Engineering, 2020, vol. 12, no. 1, pp. 10–19.
Hasankhani A., Hakimi S. M. Stochastic energy management of smart microgrid with intermittent renewable energy resources in electricity market. Energy, 2021, vol. 219, art. no. 119668.
Lekvan A. A., Habibfar R., Jermsittipareset K. Robust optimization of renewable-based multi-energy microgrid integrated with flexible energy conversion and storage devices. Sustainable Cities and Society, 2021, vol. 64, art. no. 102532.
Fumo N., Mago P. J., Chamra L. M. Analysis of cooling, heating, and power systems based on site energy consumption. Applied Energy, 2009, vol. 86, pp. 928–932.
Ghaebi H., Yari M., Gargari S. G., Rostamzadeh H. Thermodynamic modeling and optimization of a combined biogas steam reforming system and organic Rankine cycle for coproduction of power and hydrogen. Renewable Energy, 2019, vol. 130, pp. 87–102.
Wang J. J., Jing Y. Y., Zhang C. F. Optimization of capacity and operation for CCHP system by genetic algorithm. Applied Energy, 2010, vol. 87, pp. 1325–1335.
Kerr T. Combined heat and power: Evaluating the benefits of greater global investment. IEA, International Energy Agency, 2008. Available at: https://energiatalgud.ee/sites/default/files/images_sala/5/5a/IEA._Combined_Heat_and_Power._2008.pdf (accessed: September 30, 2024).
Zhang J., Cao S., Yu L., Zhou Y. Comparison of combined cooling, heating and power (CCHP) systems with different cooling modes based on energetic, environmental and economic criteria. Energy Conversion and Management, 2018, vol. 160, pp. 60–73.
Cho H., Mago P. J., Luck R., Chamra L. M. Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme. Applied Energy, 2009, vol. 86, pp. 2540–2549.
Wang J. J., Jing Y. Y., Zhang C. F., Zhai Z. J. Performance comparison of combined cooling, heating and power system in different operation modes. Applied Energy, 2011, vol. 88, art. no. 462131.
Mago P. J., Hueffed A. K. Evaluation of a turbine driven CCHP system for large office buildings under different operating strategies. Energy Build, 2010, vol. 42, pp. 1628–1636.
Smith A., Luck R., Mago P. J. Analysis of a combined cooling, heating and power system model under different operating strategies with input and model data uncertainty. Energy Build, 2010, vol. 42, pp. 2231–2240.
Jing Y. Y., Bai H., Wang J. J., Liu L. Life cycle assessment of a solar combined cooling, heating and power system in different operation strategies. Applied Energy, 2012, vol. 92, art. no. 84353.
Afzali S. F., Mahalec V. Optimal design, operation and analytical criteria for determining optimal operating modes of a CCHP with fired HRSG, boiler, electric chiller and absorption chiller. Energy, 2017, vol. 139, pp. 1052–1065.
Wang J., Yang Y., Mao T., Sui J., Jin H. Life cycle assessment (LCA) optimization of solarassisted hybrid CCHP system. Applied Energy, 2015, vol. 146, pp. 38–52.
Wang J., Zhai Z. J., Jing Y., Zhang C. Particle swarm optimization for redundant building cooling, heating and power system. Applied Energy, 2010, vol. 87, pp. 3668–3679.
Hajabdollahi H., Ganjehkaviri A., Jaafar M. N. M. Assessment of new operational strategy in optimization of CCHP plant for different climates using evolutionary algorithms. Applied Thermal Engineering, 2015, vol. 75, pp. 468–480.
Li M., Mu H., Li N. Optimal design and operation strategy for integrated evaluation of CCHP (combined cooling, heating and power) system. Energy, 2016, vol. 99, pp. 202–220.
Mohammadkhani N., Sedighizadeh M., Esmaili M. Energy and emission management of CCHPs with electric and thermal energy storage and electric vehicle. Therm. Sci. Eng. Prog., 2018, vol. 8, pp. 494–508.
Khaloie H., Abdollahi A., Shafie-Khah M., Siano P., Nojavan S., Anvari-Moghaddam A., Catalao J. P. S. Co-optimized bidding strategy of an integrated wind-thermal-photovoltaic system in deregulated electricity market under uncertainties. Journal of Clean Production, 2020, vol. 242, art. no. 118434.
Khaloie H., Abdollahi A., Shafie-Khah M., Siano P., Nojavan S., Anvari-Moghaddam A., Catalao J. P. S. Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model. Applied Energy, 2020, vol. 259, art. no. 114168.
Jing R., Wang M., Wang W., Brandon N., Li N., Chen J., Zhao Y. Economic and environmental multi-optimal design and dispatch of solid oxide fuel cell based CCHP system. Energy Conversion and Management, 2017, vol. 154, pp. 365–379.
Cao Y., Wang Q., Du J., Nojavan S., Jermsittiparsert K., Ghadimi N. Optimal operation of CCHP and renewable generation-based energy hub considering environmental perspective: An epsilon constraint and fuzzy methods. Sustainable Energy, Grids and Networks, 2019, vol. 20, art. no. 100274.
Hou J., Wang J., Zhou Y., Lu X. Distributed energy systems: Multi-objective optimization and evaluation under different operational strategies. Journal of Clean Production, 2020, art. no. 124050.
Gao L., Hwang Y., Cao T. An overview of optimization technologies applied in combined cooling, heating and power systems. Renewable and Sustainable Energy Reviews, 2019, vol. 114, art. no. 109344.
Abbasi M. H., Sayyaadi H., Tahmasbzadebaie M. A methodology to obtain the foremost type and optimal size of the prime mover of a CCHP system for a large-scale residential application. Applied Thermal Engineering, 2018, vol. 135, pp. 389–405.
Yan Y., Zhang C., Li K., Wang Z. An integrated design for hybrid combined cooling, heating and power system with compressed air energy storage. Applied Energy, 2018, vol. 210, pp. 1151–1166.
Chen X., Zhou H., Li W., Yu Zh., Gong G., Yan Y., Luo L., Wan Zh., Ding Y. Multi-criteria assessment and optimization study on 5 kW PEMFC based residential CCHP system. Energy Conversion and Management, 2018, vol. 160, pp. 384–395.
Song Z., Liu T., Lin Q. Multi-objective optimization of a solar hybrid CCHP system based on different operation modes. Energy, 2020, vol. 206, art. no. 118125.
Deb K., Pratap A., Agarwal S., Meyarivan T. A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Transaction of Evolutionary Computation, 2002, vol. 6, pp. 182–197.
Ren F., Wei Z., Zhai X. Multi-objective optimization and evaluation of hybrid CCHP systems for different building types. Energy, 2021, vol. 215, pt A, art. no. 119096.
Konak A., Coit D. W., Smith A. E. Multi-objective optimization using genetic algorithms: A tutorial. Reliability Engineering and System Safety, 2006, vol. 91, pp. 992–1007.
Dawes R., Corrigan B. Linear models in decision making. Psychological Bulletin, 1974, vol. 81, no. 2, pp. 95–106.
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