Multi-objective optimization of hybrid solar/wind/diesel/battery system for different climates of Iran
- PDF / 6,768,903 Bytes
- 27 Pages / 439.37 x 666.142 pts Page_size
- 29 Downloads / 172 Views
Multi‑objective optimization of hybrid solar/wind/diesel/ battery system for different climates of Iran Mohammad Shafiey Dehaj1 · Hassan Hajabdollahi1 Received: 21 March 2020 / Accepted: 12 November 2020 © Springer Nature B.V. 2020
Abstract In this paper, a wind/photovoltaic/battery/diesel hybrid system with hourly analysis during a year is modeled and optimized for different cities of Iran with various ranges of wind, solar and ambient temperature. A number of solar panels, wind turbines, batteries as well as nominal capacity of diesel engine are considered as design parameters. Fuel ratio and total annual cost (TAC) are selected as two simultaneous objective functions, and particle swarm optimization algorithm is used to find the optimum value of design parameter. The optimum results reveal that Zahedan has the significant lower TAC compared with other studied cases. Optimum cost increases 4.63%, 5.85%, 8.24%, 15.45% and 17.60%, respectively, in the Bushehr, Kerman, Tabriz, Tehran and Mashhad as compared with Zahedan. Optimum results reveal that annual cost extremely increases for the system with the absence of diesel engine (highest fuel ratio). For example, TAC increases at least 100% for the improvement of fuel ratio from 0.8 to 1 for all studied cities. The results also reveal a regular fluctuation in the battery charging and discharging is observed in the high available radiation cities such as Zahedan and Kerman. Furthermore, TAC increases in a linear manner, while fuel ratio increases in an exponentially manner with the increase in the number of PV panels in the optimum situation for all studied cases. Keywords Photovoltaic panel · Wind turbine · Battery bank · diesel engine · Total annual cost · Fuel ratio Abbreviations A Annual cost coefficient (-) Cin Investment cost ($) Cm Annual maintenance cost ($/year) C Capital cost ($) FR Fuel ratio (-) Ib Direct beam (kW/m2) Id Diffuse beam (kW/m2) Ih Sum of direct and diffuse beam (kW/m2) * Mohammad Shafiey Dehaj [email protected] 1
Department of Mechanical Engineering, Faculty of Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran
13
Vol.:(0123456789)
M. Shafiey Dehaj, H. Hajabdollahi
Isc PV Short-circuit current (A) fVoc_T Temperature correction of voltage fIsc_T Temperature correction of current i Interest rate (-) Mf ,Hyb Annual fuel consumption in the hybrid system (kg/hour) Mf ,Trad Annual fuel consumption in the traditional system (kg/hour) Vc Cut-in wind speed (m/s) Vf Cut-off wind speed (m/s) Vr Rated wind speed (m/s) V Wind speed (m/s) Q̇ o Exhaust recovering heat (kW) Q̇ wj Water jacket recovering heat (kW) TAC Total annual cost ($/year) Y Depreciation time (year) P Power (kW) Per Rated electrical power (kW Greek abbreviation 𝜎 Hourly self-discharge rate 𝜂 Efficiency (-) 𝜎 Hourly self-discharge rate 𝜂 Efficiency (-) 𝛽 Panel surface angle (degree) 𝜌g Reflectance from the surroundings (-) 𝜏DE Hourly operational hours of diesel engine (Hour) 𝜙f Unit price of fuel ($/kg) 𝜓CO2 Emission penalty
Data Loading...
