Hybrid Strategy for optimal scheduling of an integrated electrical water distribution system in presence of water and power producer under uncertain electricity price based on Stochastic/Robust Approach

Document Type : Original Article


1 Imam hossein university




Recently, seawater desalination is known as a way to face water distribution network challenges related to increasing water demand. A seawater desalination process generally requires a significant amount of heat generated by an electrical energy source. Therefore, the combined water and power (CWP) generating units are applied to reduce the electrical consumption of seawater desalination processes. In the CWP units, the heat energy required for seawater desalination is supplied by using the waste heat of the flue gases exhausted from the power generation part. Therefore, it is highlighted that the freshwater of the CWP unit is dependent on the amount of electrical power generated by this unit. The CWP power generation is usually related to the electrical price in separated electrical and water distribution networks. However, this value can be scheduled based on the value of water demand and electrical price in an integrated electrical-water distribution network. In this paper, a hybrid scheduling model based on stochastic/robust is proposed to minimize the operation cost of an integrated water-electrical system by considering the uncertainty of electricity price and technical constraints of electrical and water distribution systems. The proposed hybrid scheduling model is solved based on the price information obtained by executing an interval forecasting model. In other words, the upper and lower bound of price is forecasted in an interval forecasting model. Then, such parameters are used to find the worst of integrated electrical-water distribution systems against the electrical price uncertainty.


Main Subjects

Articles in Press, Accepted Manuscript
Available Online from 27 July 2021
  • Receive Date: 01 May 2021
  • Revise Date: 04 July 2021
  • Accept Date: 27 July 2021