Economic optimization for configuration and sizing of micro integrated energy systems

Abstract

Abstract Based on analysis of construction and operation of micro integrated energy systems (MIES), this paper presents economic optimization for their configuration and sizing. After presenting typical models for MIES, a residential community MIES is developed by analyzing residential direct energy consumption within a general design procedure. Integrating with available current technologies and local resources, the systematic design considers a prime mover, fed by natural gas, with wind power, photovoltaic generation, and two storage devices serving thermal energy and power to satisfy cooling, heating and electricity demands. Control strategies for MIES also are presented in this study. Multi-objective formulas are obtained by analyzing annual cost and dumped renewable energy to achieve optimal coordination of energy supply and demand. According to historical load data and the probability distribution of distributed generation output, clustering methods based on K-means and discretization methods are employed to obtain typical scenarios representative of uncertainties. The modified non-dominated sorting genetic algorithm is applied to find the Pareto frontier of the constructed multi-objective formulas. In addition, aiming to explore the Pareto frontier, the dumped energy cost ratio is defined to check the energy balance in different MIES designs and provide decision support for the investors. Finally, simulations and comparision show the appropriateness of the developed model and the applicability of the adopted optimization algorithm.

Keywords

• Micro integrated energy system (MIES)
• Economic optimization
• Uncertainties
• Non-dominated sorting genetic algorithm (NSGA-II)