Optimal operation of water-energy microgrids; a mixed integer linear programming formulation

[摘要] Increasing energy efficiency in water distribution systems is one of the most important aspects of a sustainable water infrastructure. Additionally, providing this energy from renewable sources is an essential step towards a cleaner production in energy infrastructures. Therefore in this paper, an optimization model is developed to minimize the energy consumption of a water-energy microgrid system. A day-ahead economic dispatch model is developed to minimize the daily cost of energy in the waterenergy microgrid. The energy consumption of water system is minimized using tank's and pump's scheduling and operation, hydraulic factors, and daily demand. Particularly, the electricity consumption of the pump is minimized by adjusting its head gain and flow rate via a variable speed. The energy unit is composed of an aggregated conventional power generation, solar photovoltaic, wind generation, and battery energy storage system. To offer a global optimum for the proposed non-linear programming formulation, bivariate piecewise linear approximation is used to linearize the pump's power consumption and gain, and conservation of energy-mass. In addition, univariate piecewise linear approximation is used to linearize the energy consumption function of conventional power generation systems. The optimization results of the mixed integer linear programming and mixed integer non-linear programming formulations for the studied water-energy microgrid system are compared and discussed. These models are developed to concurrently minimize the electricity consumption of a micro water-energy distribution network in two scenarios of (1) standalone water distribution system operation and (2) an integrated islanded micro water-energy system with electrical loads. (C) 2020 Elsevier Ltd. All rights reserved.

[发布日期] 2020-12-01

[关键词] Water-energy microgrid;Cost optimization;Mixed integer non-linear programming (MINLP);Mixed integer linear programming (MILP);Co-optimization;Piecewise linearization