OPTIMIZING ENERGY HUB SYSTEM OPERATION WITH ELECTRICAL AND THERMAL DEMAND RESPONSE PROGRAMS

Year 2024, Volume: 12 Issue: 1, 1 - 13, 01.03.2024

Özge Pınar Akkaş , Yağmur Arıkan Yıldız

https://doi.org/10.36306/konjes.1377983

Abstract

Electricity consumption is increasing rapidly and many countries are looking for ways to cope with the energy crisis. Morever, the world is facing the problem of global warming caused by emissions. Therefore, it is of great importance to operate power systems efficiently. Energy Hub (EH) represents a versatile energy system capable of providing efficient and optimal solutions for the operation of power systems across multiple carriers. This paper examines the optimization of an EH encompassing renewable energy systems (RES) like wind and photovoltaic, combined heat and power (CHP), transformer, absorption chiller, energy storage system (ESS) and furnace with aiming at minimizing the cost. Demand response is an energy sector strategy that entails modifying electricity consumption patterns in reaction to fluctuations in electricity supply or pricing. The objective of demand response programs (DRP) is to curtail or shift electricity consumption during periods of elevated electricity prices. Therefore, Electrical Demand Response Program (EDRP) for electrical demand and the Thermal Demand Response Program (TDRP) for heating demand are incorporated into the EH. The optimization problem is formulated as Mixed Integer Linear Programming (MILP) and solved with CPLEX solver in GAMS. The outcomes of various case studies are compared to ascertain the model's efficiency.

Keywords

Demand response program, Energy Hub, Optimization, Renewable energy systems

References

• M. Geidl and G. Andersson, "A modeling and optimization approach for multiple energy carrier power flow," in Proc. IEEE 2005 Power Tech Conference, Russia, 27-30 June 2005.
• X. Lu, H. Li, K. Zhou, and S. Yang, "Optimal load dispatch of energy hub considering uncertainties of renewable energy and demand response," Energy, vol. 262, pp. 125564, 2023.
• A. A. Eladl, M. I. El-Afifi, M. A. Saeed, and M. M. El-Saadawi, "Optimal operation of energy hubs integrated with renewable energy sources and storage devices considering CO2 emissions," Electrical Power and Energy Systems, vol. 117, p. 105719, 2020.
• D. Rakipour and H. Barat, "Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response," Energy, vol. 173, pp. 384-399, 2019.
• M. Tian, A. G. Ebadi, K. Jermsittiparsert, M. Kadyrov, A. Ponomarev, N. Javanshir, and S. Nojavan, "Risk-based stochastic scheduling of energy hub system in the presence of heating network and thermal energy management," Applied Thermal Engineering, vol. 159, p. 113825, 2019.
• M. Nasir, A. R. Jordehi, M. Tostado-Veliz, V. S. Tabar, S. A. Mansouri, and F. Jurado, "Operation of energy hubs with storage systems, solar, wind and biomass units connected to demand response aggregators," Sustainable Cities and Society, vol. 83, p. 103974, 2022.
• V. Davatgaran, M. Saniei, and S. S. Mortazavi, "Optimal bidding strategy for an energy hub in energy market," Energy, vol. 148, pp. 482-493, 2018.
• M. J. Vahid-Pakdel, S. M. Nojavan, B. Mohammadi-ivatloo, and K. Zare, "Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response," Energy Conversion and Management, vol. 145, pp. 117–128, 2017.
• E. Shahrabi, S. M. Hakimi, A. Hasankhani, G. Derakhshan, and B. Abdi, "Developing optimal energy management of energy hub in the presence of stochastic renewable energy resources," Sustainable Energy, Grids and Networks, vol. 26, p. 100428, 2021.
• Y. Cao, Q. Wang, J. Du, S. Nojavan, K. Jermsittiparsert, and N. Ghadimi, "Optimal operation of CCHP and renewable generation-based energy hub considering environmental perspective: An epsilon constraint and fuzzy methods," Sustainable Energy, Grids and Networks, vol. 20, p. 100274, 2019.
• F. Jamalzadeh, A. H. Mirzahosseini, F. Faghihi, and M. Panahi, "Optimal operation of energy hub system using hybrid stochastic-interval optimization approach," Sustainable Cities and Society, vol. 54, p. 101998, 2020.
• A. Dolatabadi and B. Mohammadi-Ivatloo, "Stochastic risk-constrained scheduling of smart energy hub in the presence of wind power and demand response," Applied Thermal Engineering, vol. 123, pp. 40–49, 2017.
• S. Pazouki, M. Haghifam, and A. Moser, "Uncertainty modeling in optimal operation of energy hub in presence of wind, storage and demand response," Electrical Power and Energy Systems, vol. 61, pp. 335–345, 2014.
• S. Pazouki and M. Haghifam, "Optimal planning and scheduling of energy hub in presence of wind, storage and demand response under uncertainty," Electrical Power and Energy Systems, vol. 80, pp. 219–239, 2016.
• V. V. Thang, T. Ha, Q. Li, and Y. Zhang, "Stochastic optimization in multi-energy hub system operation considering solar energy resource and demand response," Electrical Power and Energy Systems, vol. 141, p. 108132, 2022.
• M. Majidi, S. Nojavan, and K. Zare, "A cost-emission framework for hub energy system under demand response program," Energy, vol. 134, pp. 157-166, 2017.
• M. H. Shams, M. Kia, M. Heidari, A. Lotfi, M. Shafie-khah, and J. P. S. Catalao, "Optimal operation of electrical and thermal resources in microgrids with energy hubs considering uncertainties," Energy, vol. 187, p. 115949, 2019.
• S. A. Mansouri, A. Ahmarinejad, M. Ansarian, M. S. Javadi, and J. P. S. Catalao, "Stochastic planning and operation of energy hubs considering demand response programs using Benders decomposition approach," Electrical Power and Energy Systems, vol. 120, p. 106030, 2020.
• W. Jiang, X. Wang, H. Huang, D. Zhang, and N. Ghadimi, "Optimal economic scheduling of microgrids considering renewable energy sources based on energy hub model using demand response and improved water wave optimization algorithm," Journal of Energy Storage, vol. 55, p. 105311, 2022.
• A. Soroudi, M. Aien, and M. Ehsan, "A probabilistic modeling of photovoltaic modules and wind power generation impact on distribution networks," IEEE Systems Journal, vol. 6, no. 2, pp. 254–259, 2012.
• B. Ozerdem, S. Ozer, and M. Tosun, "Feasibility study of wind farms: A case study for Izmir, Turkey," Journal of Wind Engineering and Industrial Aerodynamics, vol. 94, no. 10, pp. 725-743, 2006.
• S. Hadayeghparast, A. S. Farsangi, and H. Shayanfar, "Day-ahead stochastic multi-objective economic/emission operational scheduling of a large scale virtual power plant," Energy, vol. 172, pp. 630-646, 2019.
• A. Soroudi, Power System Optimization Modeling in GAMS. Springer, 2017.
• GAMS. [Online]. Available: http://www.GAMS.com. [Accessed Feb. 26, 2024].