Adaptive Residential Energy Hubs Scheduling Considering Renewable Sources

Document Type : Research paper


Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran


One of the crucial challenges within the optimal operation of smart cities is coordinated management of multiple energy carriers in the residential buildings owing to disparate and often conflicting objectives. In response to this challenge, this paper proposes a novel conceptual cost-emission-based scheme for optimal energy-gas use in a smart home in the context of residential energy hubs considering a meaningful trade-off between cost saving and environmental protection. Various energy conversion resources containing energy and heat storage systems, rooftop photovoltaic modules, and also combined heat and power units along with responsible electrical and thermal loads are taken into account in the proposed model. Furthermore, an efficient stochastic scenario-based method is executed to tackle the intense uncertainty associated with photovoltaic production. The proposed model reduces domestic energy consumption and utility costs by incorporating a weighted summation mixed objective function under various system constraints and user preferences, while at t the same time optimal task scheduling and comfort for the resident that it can guarantee a good lifestyle. The presented scheme is carried out on a realistic case study equipped with energy hubs and as expected, introduces its applicability and effectiveness in the optimal energy management of the proposed residential energy hub problem. The simulation results confirm that energy procurement costs can be saved by up to 46.16% and emission costs by 34.07% while maintaining the desired level of comfort for the head of the household.


  1. Wuetal, "Optimal integration of a hybrid solar-battery power source into smart home nanogrid with plug-in electric vehicle," J. Power Sources, vol. 363, pp. 277–283, 2017.
  2. Hashemzadeh, and M. Hejri, "A Fast and Accurate Global Maximum Power Point Tracking Method for Solar Strings under Partial Shading Conditions," J. Oper. Autom. Power Eng., vol. 8, no. 3, pp. 245–256, 2020.
  3. Samadi Gazijahani, J. Salehi, "Stochastic multi-objective framework for optimal dynamic planning of interconnected microgrids," IET Renew. Power Gener., vol. 11, no. 14, pp. 1749–1759, 2017.
  4. Samadi Gazijahani, J. Salehi, "Optimal bi-level model for stochastic risk-based planning of microgrids under uncertainty," IEEE Trans. Ind. Inf. , vol. 14, no. 7, pp. 3054–3064, 2018.
  5. Wuetal, "Stochastic control of smart home energy management with plug-in electric vehicle battery energy storage and photovoltaic array," J. Power Sources, vol. 333, pp. 203–212, 2016.
  6. Geidl, G. Koeppel, P. Favre-Perrod, B. Klockl, G. Andersson, and K. Frohlich, "Energy hubs for the future," IEEE power energy mag., vol. 5, pp. 24–30, 2007.
  7. Roustai, M. Rayati, A. Sheikhi, and A. M. Ranjbar, "A scenario-based optimization of smart energy hub operation in a stochastic environment using conditional-value-at-risk," Sust. Cities and Society, 2018.
  8. Gram-Hanssen and S. J. Darby, "Home is where the smart is"? Evaluating smart home research and approaches against the concept of home, Energy Rese. Social Scie., vol. 37, pp. 94–101, 2018.
  9. Kamyab and S. Bahrami, "Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets," Energy, vol. 106, pp. 343–355, 2016.
  10. Yongjie, D. Xie, M. Zhou, Y. Wang, Y. Hou, and Y. Sun, "Hierarchical optimal operation for integrated energy system based on energy hub," 2nd IEEE Conf. Energy Internet Energy Sys. Integ., vol. 12 , pp. 1–6. IEEE, 2018.
  11. Miao, Z. Yue, T. Niu, A. A. Alizadeh, and K. Jermsittiparsert, "Optimal emission management of photovoltaic and wind generation based energy hub system using compromise programming," J. Cleaner Produc., pp. 124333, 2020.
  12. A. Eladl, M. I. El-Afifi, M. A. Saeed, and M. M. ElSaadawi, "Optimal operation of energy hubs integrated with renewable energy sources and storage devices considering CO2 emissions," Int. J. Elec. Power Energy Syst., vol. 117, pp. 105719, 2020.
  13. Gerami Moghaddam, M. Saniei, and E. Mashhour, "A comprehensive model for self-scheduling an energy hub to supply cooling," heating and electrical demands of a building, Energy, vol. 94, pp. 157–170, 2016.
  14. Niknam, et al, "Optimal operation management of fuel cell/wind/photovoltaic power sources connected to distribution networks," J. Power Sources, vol. 196, no. 20, pp. 8881–8896, 2011.
  15. Fabrizio, V. Corrado, and M. Filippi, "A model to design and optimize multi-energy systems in buildings at the design concept stage," Renewable Energy, vol. 35, no. 3, pp. 644–655, 2010.
  16. Mansour-Saatloo, M. Agabalaye-Rahvar, M. A. Mirzaei, B. Mohammadi-Ivatloo, M. Abapour, and K. Zare, "Robust scheduling of hydrogen based smart micro energy hub with integrated demand response," J. Cleaner Produ., vol. 267, pp. 122041, 2020.
  17. Babaei, A. Safari, and J. Salehi, "Evaluation of Delaysbased Stability of LFC Systems in the Presence of Electric Vehicles Aggregator," J. Oper. Autom. Power Eng., vol. 10 no. 2, pp. 165–174, 2022.
  18. R. Aghajani, and I. Heydari, "Energy management in microgrids containing electric vehicles and renewable energy sources considering demand response, " J. Oper. Automa. Power Eng., vol. 9, no. 1, pp. 34–48, 2021.
  19. Mazlumi, and A. Shabani, "DC microgrid protection in the presence of the photovoltaic and energy storage systems." J. Oper. Automa. Power Eng., vol. 6, no. 2, pp. 243–254, 2018.
  20. B. Sani, M. Sedighizadeh, D. Sedighizadeh, and R. Abbasi, "Risk Averse Optimal Operation of Coastal Energy Hub Considering Seawater Desalination and Energy Storage Systems," J. Oper. Automa. Power Eng., vol. 10 no. 2, pp. 90–104, 2022.
  21. Ghaedi, H. Gorginpour, and E. Noroozi, "Operation Studies of the Power Systems Containing Combined Heat and Power Plants." J. Oper. Automa. Power Eng. vol. 9, no. 2, pp. 160–171, 2021.
  22. Alizad, H. Rastegar, and F. Hasanzad, "Dynamic planning of Power-to-Gas integrated energy hub considering demand response programs and future market conditions," Int. J. Electr. Power Energy Syst., vol. 143, pp. 108503, 2022.
  23. Honarmand, S. M. Rashid, "A sustainable framework for long-term planning of the smart energy hub in the presence of renewable energy sources," energy storage systems and demand response program, J. Energy Storage, vol. 52, pp. 105009, 2022
  24. Rahgozar, A. Z. G. Seyyedi, and P. Siano , "A resilienceoriented planning of energy hub by considering demand response program and energy storage systems," J. Energy Storage, vol. 52, pp. 104841, 2022.
  25. Aghamohamadi, A. Mahmoudi, Ward, M. J. Ghadi, and J. P. Catalão, "Block-Coordinate-Descent Adaptive Robust Operation of Int. J. Elec. Power Energy Syst.strial Multilayout Energy hubs under Uncertainty," Electr. Power Syst. Res., vol. 212, 108334, 2022.
  26. Bahmani, H. Karimi, and S. Jadid, "Cooperative energy management of multi-energy hub systems considering demand response programs and ice storage." Int. J. Electr. Power Energy Syst., vol. 130, pp. 106904, 2021.
  27. R. Ramatian, A. Ghaderi Shamim, S. Bahramara, " Optimal Operation of the Energy Hubs in the islanded Multi-Carrier Energy System Using Cournot model." Appl. Thermal Eng., pp. 116837, 2021.
  28. 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, pp. 100428, 2021.
  29. Khorasany, A. Najafi-Ghalelou, R. Razzaghi, and B. Mohammadi-Ivatloo, "Transactive energy framework for optimal energy management of multi-carrier energy hubs under local electrical, thermal, and cooling market constraints," International Journal of Electrical Power and Energy Systems, vol. 129, pp. 106803, 2021.
  30. Tiwari, and J. G. Singh, "Optimal energy management of multi-carrier networked energy hubs considering efficient integration of demand response and electrical vehicles, A cooperative energy management framework," J. Energy Storage, vol. 51, pp. 104479, 2022
  31. Salehi, A. Namvar, F. S. Gazijahani, M. Shafie-khah, and J. P. Catalão, Effect of power-to-gas technology in energy hub optimal operation and gas network congestion reduction, Energy, vol. 240, pp. 122835, 2022
  32. Sattarpour, D. Nazarpour, and S. Golshannavaz, "A multiobjective hem strategy for smart home energy scheduling, A collaborative approach to support microgrid operation," Sust. Cities Society, vol. 37, pp. 26–33, 2018.
  33. Samadi Gazijahani, S. N. Ravadanegh, and J. Salehi, "Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies," ISA trans., vol. 73, pp. 100–111, 2018.
  34. Samadi Gazijahani, and J. Salehi, "Integrated DR and reconfiguration scheduling for optimal operation of microgrids using hong’s point estimate method," Int. J. Electr. Power Energy Syst., vol. 99, pp. 481–492, 2018.
  35. Samadi Gazijahani, and J. Salehi, "Robust design of microgrids with reconfigurable topology under severe uncertainty," IEEE Trans. Sust. Energy, vol. 9, no. 2, pp. 559–569, 2018.
  36. Rajasekharan, and V. Koivunen, "Optimal energy consumption model for smart grid households with energy storage," IEEE J. Sel. Top. Signal Process., vol. 8, no. 6, pp. 1154–1166, 2014.
  37. Ghobadpour, M. Gandomkar, and J. Nikoukar, "MultiObjective Function Optimization for Locating and Sizing of Distributed Generation Sources in Radial Distribution Networks with Fuse and Recloser Protection," J. Oper. Autom. Power Eng. vol. 9, no. 3, pp. 266–273, 2021.
  38. Abdolahi, and et al, "Probabilistic multi-objective arbitrage of dispersed energy storage systems for optimal congestion management of active distribution networks including solar/wind/CHP hybrid energy system," J. Renewable Sustainable Energy , vol. 10, no. 4, pp. 045502, 2018.
  39. Samadi Gazijahani, J. Salehi, and M. Shafie-khah, "Benefiting from Energy-Hub Flexibilities to Reinforce Distribution System Resilience, " A Pre-and Post-Disaster Management Model," IEEE Systems J. , 20221.
  40. Salyani, and et al, "Chance constrained simultaneous optimization of substations, feeders, renewable and nonrenewable distributed generations in distribution network," Electr. Power Syst. Res. , vol. 158,56–69, 2018.
  41. M Atwa, E. F. El-Saadany, M. M. A. Salama, and R. Seethapathy, "Optimal renewable resources mix for distribution system energy loss minimization," IEEE Trans. Power Syst., vol. 25, no. 1 , pp. 360–370, 2010.
  42. Behnamfar, H. Barati, and M. Karami, "Stochastic short-term hydro-thermal scheduling based on mixed integer programming with volatile wind power generation," J. Oper. Autom. Power Eng., vol. 8, pp. 195–208, 2020.
  43. Samadi Gazijahani, J. Salehi, Reliability constrained twostage optimization of multiple renewable-based microgrids incorporating critical energy peak pricing demand response program using robust optimizationapproach, Energy, vol. 161, pp. 999–1015, 2018.
  44. Samadi Gazijahani, J. Salehi, "Game theory based profit maximization model for microgrid aggregators with presence of EDRP using information gap decision theory," IEEE Syst. J., vol. 99, pp. 1–9, 2018.
  45. The gams software website, Available: %2Fsolvers%2Findex.html , 2017.
  46. Rastegar and M. Fotuhi-Firuzabad, "Load management in a residential energy hub with renewable distributed energy resources," Energy Build., vol. 107, pp. 234–242, 2015.
  47. Samadi Gazijahani, J. Salehi, and M. Shafie-khah, "A Parallel Fast-Track Service Restoration Strategy Relying on Sectionalized Interdependent Power-Gas Distribution Systems," IEEE Trans. Ind. Inf., 2022.

Articles in Press, Corrected Proof
Available Online from 16 December 2022
  • Receive Date: 02 July 2022
  • Revise Date: 18 October 2022
  • Accept Date: 30 October 2022
  • First Publish Date: 16 December 2022