The impact of integrated demand response on robust scheduling of local water-energy systems in the presence of electric and hydrogen vehicles

Document Type : Original Article

Authors

Department of Electrical Engineering, Faculty and Research Institute of Passive Defense and Engineering, Imam Hossein University, Tehran, Iran

10.22059/ses.2023.348024.1014

Abstract

Integrated demand response effectively promotes the use of renewable energy sources and improves energy efficiency in systems with multiple energy carriers. This paper proposes a resilient scheduling model for local energy systems based on electricity, cooling, hydrogen, and water in the presence of electric and hydrogen vehicles. In addition, the role of integrated demand response based on electricity and cooling to reduce the operating cost of the local water-energy system is investigated. The local energy system is equipped with electricity generation sources, a water desalination device, wind turbine, water, electricity, cooling, and hydrogen storage systems, an electricity to hydrogen conversion unit, and an electric chiller to simultaneously meet water and energy demands. To model the uncertainty of wind power generation, a robust optimization approach is used without the need for probability density function and scenario generation, which supports the optimal scheduling of the water-energy system against changes in wind power generation. It also enables the operator to apply a risk-averse approach. Numerical results show that using integrated demand response besides water-energy storage systems reduces the total operating cost of the local system by 5.6%.

Keywords


  • Mirzaei M. A, Nazari-Heris M, Mohammadi-Ivatloo B, Zare K, Marzband M, Pourmousavi SA. Robust flexible unit commitment in network-constrained multicarrier energy systems. IEEE Syst J. 2020;15(4):5267-5276.
  • Wang D, Jia H, Hou K, Du W, Chen N, Wang X, Fan M. Integrated demand response in district electricity-heating network considering double auction retail energy market based on demand-side energy stations. Appl Energy. 2019;248:656-678.
  • Agabalaye‐Rahvar M, Mansour‐Saatloo A, Mirzaei MA, Mohammadi‐Ivatloo B, Zare K. Economic‐environmental stochastic scheduling for hydrogen storage‐based smart energy hub coordinated with integrated demand response program. Int J Energy Research. 2021;45(14):20232-20257.
  • Mirzaei M. A, Nazari-Heris M, Mohammadi-Ivatloo B, Zare K, Marzband M, Anvari-Moghaddam A. A novel hybrid framework for co-optimization of power and natural gas networks integrated with emerging technologies. IEEE Syst J. 2020;14(3):3598-3608.
  • Liu P, Ding T, Zou Z, Yang Y. Integrated demand response for a load serving entity in multi-energy market considering network constraints. Appl Energy. 2019;250:512-529.
  • Lu X, Liu Z, Ma L, Wang L, Zhou K, Feng N. A robust optimization approach for optimal load dispatch of community energy hub. Appl Energy. 2020;259:114195.
  • Xu X, Hu W, Cao D, Huang Q, Liu W, Jacobson MZ, Chen Z. Optimal operational strategy for an offgrid hybrid hydrogen/electricity refueling station powered by solar photovoltaics. J Power Sources. 2020;451:227810.
  • Mansour-Saatloo A, Ebadi R, Mirzaei M. A, Zare K, Mohammadi-Ivatloo B, Marzband M, Anvari-Moghaddam A. Multi-objective IGDT-based scheduling of low-carbon multi-energy microgrids integrated with hydrogen refueling stations and electric vehicle parking lots. Sustain Cities and Soc. 2021;74:103197.
  • Xu X, Hu W, Liu W, Wang D, Huang Q, Huang R, Chen Z. Risk-based scheduling of an off-grid hybrid electricity/hydrogen/gas/refueling station powered by renewable energy. J Cleaner Prod. 2021;315:128155.
  • Mansour-Saatloo A, Pezhmani Y, Mirzaei MA, Mohammadi-Ivatloo B, Zare K, Marzband M, Anvari-Moghaddam A. Robust decentralized optimization of multi-microgrids integrated with power-to-X technologies. Appl Energy. 2021;304:117635.
  • Wu X, Qi S, Wang Z, Duan C, Wang X, Li F. Optimal scheduling for microgrids with hydrogen fueling stations considering uncertainty using data-driven approach. Appl energy. 2019;253:113568.
  • Sui Q, Wei F, Lin X, Li Z. Optimal energy management of a renewable microgrid integrating water supply systems. International Journal of Electrical Power & Energy Systems. 2021;125:106445.
  • Moazeni F, Khazaei J. Optimal operation of water-energy microgrids; a mixed integer linear programming formulation. J Cleaner Prod. 2020;275:122776.
  • Moazeni F, Khazaei J. Dynamic economic dispatch of islanded water-energy microgrids with smart building thermal energy management system. Appl Energy. 2020;276:115422.
  • Mohamed M. A, Almalaq A, Awwad E. M, El-Meligy M. A, Sharaf M, Ali Z. M. An effective energy management approach within a smart island considering water-energy hub. IEEE Trans Ind Appl. 2020.

 

  • Najafi J, Peiravi A, Anvari-Moghaddam A, Guerrero JM. Resilience improvement planning of power-water distribution systems with multiple microgrids against hurricanes using clean strategies. J cleaner prod. 2019;223:109-126.
  • Roustaei M, Niknam T, Salari S, Chabok H, Sheikh M, Kavousi-Fard A, Aghaei J. A scenario-based approach for the design of Smart Energy and Water Hub. Energy. 2020;195:116931.
  • Pakdel MJ, Sohrabi F, Mohammadi-Ivatloo B. Multi-objective optimization of energy and water management in networked hubs considering transactive energy. J Cleaner Prod. 2020;266:121936.
  • Mirzaei MA, Nazari-Heris M, Mohammadi-Ivatloo B, Zare K, Marzband M, Shafie-Khah
    M, Anvari-Moghaddam A, Catalão JP. Network-constrained joint energy and flexible ramping reserve market clearing of power-and heat-based energy systems: a two-stage hybrid IGDT–stochastic framework. IEEE Syst J. 2020;15(2):1547-56.
  • Li Y, Li Z, Wen F, Shahidehpour M. Privacy-preserving optimal dispatch for an integrated power distribution and natural gas system in networked energy hubs. IEEE Trans Sustain Energy. 2018;10(4):2028-2038.
  • Ahrabi M, Abedi M, Nafisi H, Mirzaei M. A, Mohammadi-Ivatloo B, Marzband M. Evaluating the effect of electric vehicle parking lots in transmission-constrained AC unit commitment under a hybrid IGDT-stochastic approach. Int J Elect Power & Energy Syst. 2021;125:106546.