Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g

Abstract

The integration of renewable energies into combined cooling, heating, and power (CCHP) systems has become increasingly popular in recent years. However, the optimization of renewable energies integrated CCHP (RECCHP) systems (i.e., optimal component configurations) is far from being well addressed, especially in isolated mode. This study aims to fill this research gap. A multi-objective optimization model characterizing the system reliability, system cost, and environmental sustainability is constructed. In this model, the objectives include minimization of annual total cost (ATC), carbon dioxide emission (CDE), and loss of energy supply probability (LESP). The decision variables representing the configuration of the RECCHP system include the number of photovoltaic (PV) panels and wind turbines (WTs), the tilt angle of PV panels, the height of WTs, the maximum fuel consumption, and the capacity of battery and heat storage tanks (HSTs). The multi-objective model is solved by a multi-objective evolutionary algorithm, namely, the preference-inspired coevolutionary algorithm (PICEA-g), resulting in a set of Pareto optimal (trade-off) solutions. Then, a decision-making process is demonstrated, selecting a preferred solution amongst those trade-off solutions by further considering the decision-maker preferences. Furthermore, on the optimization of the RECCHP system, operational strategies (i.e., following electric load, FEL, and following thermal load, FTL) are considered, respectively. Experimental results show that the FEL and FTL strategies lead to different optimal configurations. In general, the FTL is recommended in summer and winter, while the FEL is more suitable for spring and autumn. Compared with traditional energy systems, RECCHP has better economic and environmental advantages.

A Hybrid Algorithm Based on Simplified Swarm Optimization for Multi-Objective Optimizing on Combined Cooling, Heating and Power System

“…In recent years, the combination of CCHP and renewable energy is the developing trend because the development of renewable energy is becoming more and more mature. Thus, several algorithms are proposed to solve the related problems [21][22][23][24][25]. Soheyli et al considered the space constraints of CCHP units, wind power generation, and solar power generation units, hoping to obtain the best unit combination in a limited space, and adopted a multi-objective swarm algorithm based on particle-swarm optimization (PSO) to solve the problem [23].…”

“…Wang et al combined CCHP and solar power generation, using solar collectors to store solar thermal energy and targeting life cycle assessment, and optimized the problem by genetic algorithm (GA) [24]. Li et al took the CCHP of island operation as a model and considered the influence of the location of renewable energy devices, such as the angle of solar panel installation and the height of wind turbines, which was solved by an evolutionary algorithm: the preference-inspired coevolutionary algorithm [25].…”

An Improved General Type-2 Fuzzy Approach for Planning Energy Resources Systems with Air Quality Requirements

“…With the goal of maximizing the system revenue and energy utilization of the micro-energy grid, Chen et al (2019) provides decision-makers with a variety of optimal scheduling schemes. Simultaneously, with the goal of minimizing the total cost of the system, carbon dioxide emissions, and the lack of energy supply, the two operating strategies were considered to optimize the configuration of the system (Li et al, 2018a). Liu et al (2019) comprehensively considered the economic impact and environmental benefits and transformed the multi-objective optimization problem into a single objective problem in a weighted manner.…”

Multi-objective Optimization of Combined Cooling, Heating and Power System

“…The CCHP system, featured by the coupling among multiple energies, encompasses devices of various technical categories and structural forms [2][3]. The system devices include power generators, refrigerators, heaters, energy storage devices and waste heat recovery systems.…”