Techno-economic and environmental design of hybrid energy systems using multi-objective optimization and multi-criteria decision making methods

Abstract

Reliable, affordable and sustainable supply of energy is of paramount importance. This can be achieved by designing and implementing hybrid renewable energy systems, also known as micro/smart-grids. The main goal of this study is the techno-economic and environmental multi-objective optimization of a decentralized energy system to provide electrical and thermal loads of a large energy consuming complex with daily average electric and thermal loads of 38.7 and 99.4 MWh, respectively. Pareto-optimal mix of several renewable and non-renewable technologies including photovoltaic (PV), wind turbine (WT), two types of combined heat and power technologies, namely micro-gas turbine (MGT) and fuel cell (FC), grid power, electrolyzer, hydrogen tank (Htank), battery and inverter is investigated. For this purpose, different configuration of these units were simulated in HOMER software, and the exact Pareto set was found by developing a MATLAB code. A total of 1945 optimal non-dominated designs including 11 stand-alone and 41 grid-connected configurations were found, in which the dominant configuration was PV/FC/Electrolyzer/Htank/Battery/Inverter/20%Grid. The Pareto sets included systems with a wide variety of characteristics; the range (average) of net present cost (NPC), loss of power supply probability (LPSP) and carbon dioxide emissions (CE) were 26.9–44.0 (36.1) M$, 0–10 (5.7)% and 8800.9–13649.2 (9790.4) tons/yr for off-grid scenario and 17.2–37.5 (27.2) M$, 0–10 (4.3)% and 11215.1–17968.2 (13476.1) tons/yr for on-grid scenario, respectively. The TOPSIS combined with weighting methods was introduced to choose final design among non-dominated solutions set. At last, sensitivity analysis revealed that the most significant variables on the NPC of the selected micro-grids are real interest rate, investment costs, electric and thermal loads and level of irradiation, respectively.