Two-stage stochastic operation framework for optimal management of the water-energy-hub

This study proposes a bi-level stochastic framework to address optimal scheduling of energy hub (EH) in a pool-based short-term market considering electrical-thermal-water demands. EH acts as an independent price-maker producer in a day-ahead electricity market aiming to maximise its profit. The market settlement mechanism is constructed as the pay-at-market-clearing price (MCP), where each producer/consumer is paid at the MCP. The problem model is formulated as a bi-level optimisation approach in a stochastic environment, in which the upper level defines the profit maximisation of the proposed strategic producer, whereas the lower-level expresses the dispatch cost of the considered power grid. This results in a problem formulation with mathematical equilibrium constraints which is transformed into a new mixed-integer linear programme based on Karush-Kuhn-Tucker conditions. A stochastic framework based on unscented transform is developed to model the high uncertainties of EH water demand, EH thermal demand, EH electric demand, generators and loads submitted price to the market. The simulation results on the IEEE test system advocate the effectiveness and appropriate performance of the proposed strategic EH producer in the electricity market and its effect on the locational marginal prices of buses in a transmission-constrained market.