Economic optimization for configuration and sizing of micro integrated energy systems

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.

Optimally Coordinated Expansion Planning of Coupled Electricity, Heat and Natural Gas Infrastructure for Multi-Energy System

“…The electricity peak load of the first year is 178.8 MW with an average annual growth rate of 3% for the next 9 years. The spinning reserve requirement of electricity load is 5% [22]. The investment discount rate is 5% and the PLL is 10000$/MWh [13].…”

“…In [21] the expansion of power substations, CCHP, GBs and air conditioning equipment are conducted in an active distribution network, and the influence of extreme load scenario on power supply reliability is analyzed. Yu et al [22] considered the regional geographical resource endowment and put forward the optimal scheme to coordinate energy suppliers and demands in a micro integrated energy system. In [23], a demand response scheme was tailored to coordinate the power to gas devices, heat pumps, storage and flexible loads, subsequently the optimal dispatch solution with considering interactions among multiple energy carriers was achieved.…”

Optimal component configuration and capacity sizing of a mini integrated power supply system

“…An economic optimization for the configuration and sizing of micro integrated energy systems (MIES) based on an analysis of construction and operation is presented in a work by Yu et al. (). The study shows the appropriateness of the applicability of the adopted optimization algorithm through simulations and comparisons.…”

Optimal Operation Analysis of the Distribution Network Comprising a Micro Energy Grid Based on an Improved Grey Wolf Optimization Algorithm

“…With the increased level of integration in the fields of energy, automation, computers, and communications, the micro energy grid attracted the attention of an increasing number of experts and scholars [1][2][3], who integrated them into electricity, heating, cooling, and gas grids. The micro energy grid is a micro integrated energy system [4][5][6], and a natural extension of the microgrid, which is mainly used in urban communities, industrial and agricultural parks, and rural areas.…”

“…In summary, the current research had the following problems: (1) In the distribution network comprising the microgrid, only a simple electrical-load demand existed, and the demands of heating and cooling loads were not considered. (2) Recent studies of the interaction between the microgrid and the distribution network considered only the economic performance of both sides, and did not consider that the output power of the microgrid would affect the operation of the distribution network.…”