Risk-Constrained Optimal Short-Term Scheduling of Integrated Water and Power Grids Using Information Gap decision Theory

Nowadays, water and energy systems are co-operated because of their interdependency. In a combined water and power generation grid, some conventional thermal units, desalination only plants, and coproducers are optimally dispatched to maximize total profit obtained from selling water and energy to consumers while satisfying both demands at each operating time interval. Meanwhile, uncertainty associated with electricity market prices effect on optimum operating point of integrated system. This paper aims to apply information gap decision theory (IGDT) method on water-energy nexus to find maximum reduction of electricity market price under robustness or risk averse mode in a way that total profit is higher than or equal to a given critical value. In opportunistic or risk seeker decision making process, minimum increase in energy market prices is optimally determined so that the expected profit is more than or equal to given target value. A mixed integer nonlinear programming problem (MINLP) is solved using generalized algebraic mathematical modeling system (GAMS) to find optimum operating point of a benchmark cogeneration system composed of coproducers and power only units in risk-taker and robust energy procurement strategies.

Keywords:

Risk-constrained , water-power nexus , robust optimization , information gap decision theory (IGDT) , mixed-integer nonlinear programming (MINLP)