INTEGRATED RENEWABLE ENERGY SYSTEM FOR REMOTE RURAL AREA

Abstract

Despite various electrification efforts in India, rural households in geographically isolated areas lack power due to increasing energy demand and the complexity of extending the conventional grid. Over the past decade, rising pollutant emissions and advancements in solar and wind technologies have emphasized the need for renewable power generation. Utilization of renewable sources has become crucial globally due to their abundance, ability to address emission concerns, and promoting the development of green energy technology. Consequently, renewable energy based power systems are gaining popularity being reliable and cost-effective sources of electricity. These systems, coupled with battery energy storage for stand-alone applications often known as Integrated Renewable Energy System (IRES), offer viable solution when grid extension is impractical or costly. The present research work is intended with the objectives (i) To assess the potential of renewable energy resources and load demand of the selected study area. (ii) To compute the cost of energy (COE) and life cycle cost (LCC) from IRES components by considering system reliability along with its socio-economic environmental benefits. (iii) To analyze a transportation system based on battery Electric Vehicles (EVs) in place of Petrol/Gasoline based engines. (iv) To analyze the performance of battery EVs in comparison to Diesel/Petrol engines in terms of cost of energy and carbon emission. (v) To develop an IRES in order to meet the electrical energy requirements along with battery EVs energy requirement of the study area. To achieve the objectives, an IRES model has been devised to fulfil the electricity, clean water, and food preservation facility energy requirements of the study area i.e. a remote rural hilly area of Munsyari Block, Pithoragarh, Uttarakhand (India). Twelve villages housing 335 households and a total of 1,100 people are not fully electrified based on data collected from Uttarakhand Power Corporation Limited (UPCL) and Rural Electrification Corporation (REC) Limited. Situated at an elevation of 2,200 meters above sea level and 85 km from the conventional grid, undulated terrain makes expanding the grid impractical. Consequently, a stand-alone IRES is considered, utilizing solar, hydro, and biomass as locally available renewable energy sources. The annual average solar radiation in the area is 5 kWh/m²/day, with an ambient temperature of 19°C. Additionally, an estimated 989 tons/year of cattle dung and a hydropower potential of 25 kW contribute to the energy resources in the region. Therefore, this study modelled forty-three configurations incorporating locally available renewable energy sources and diverse BES devices with varying depths of discharge (DODs) at different reliability levels (loss of power supply probability (LPSP)). To identify the best renewable resource mix, various combinations, including SPV/LA at 80% DOD, MHP/SPV/LA at 80% DOD, and BGG/MHP/SPV/LA at 80% DOD, have been modelled. Now, to find the best renewable resource and battery combination, forty configurations were modelled and optimized at various DODs and reliability levels. The LA battery produces a total of ten configurations, five at 70% DOD and five at 80% DOD with different reliability levels (0% LPSP, 1% LPSP, 3% LPSP, 5% LPSP and 10% LPSP). Similarly, each of the Li-Ion, NAS, and Ni-Fe batteries form ten configurations to make a total of forty configurations. To identify the optimal configuration among these forty-three, the study employs the Chimp optimization algorithm (ChOA). Results indicate that the BGG/MHP/SPV/LA at 80% DOD offers LCC of $1,097,203 and COE of 0.26 $/kWh, presenting a 22% and 33% reduction compared to MHP/SPV/LA and SPV/LA at 80% DOD, respectively. Consequently, it is concluded that BGG/MHP/SPV stand as the most economical renewable energy combination. Further simulations show that BGG/MHP/SPV/NAS at 70% DOD provide the lowest LCC and COE at $917,000 and 0.22 $/kWh, respectively. These values are 20%, 51%, and 100% lower than the LCCs and COEs of LA (80% DOD), Ni-Fe (80% DOD), and Li-Ion (80% DOD) battery-based IRESs, respectively, at 0% LPSP. Therefore, BGG/MHP/SPV/NAS at 70% DOD is found as the optimal configuration for electrifying the selected study area. ChOA outperforms all the optimization algorithms and secures 1st rank in all the ranking criteria viz: Best, Worst, and Mean values of LCC, convergence rapidity, and average computation time taken by the algorithm while searching for global best results. Analyzing the proposed IRES configuration, load-resource uncertainties increased the total LCC, NSPV, NBES, and ES by 66%, 300%, 22%, and 373%. Load growth for years 2032 and 2042 saw 66% to 187%, 95% to 268%, 87% to 247%, and 98% to 323% higher LCC, NSPV, NBES, and ES compared to the year 2023. Additionally, sensitivity analysis for LCC and COE indicates that the proposed IRES configuration is most sensitive to variations in initial capital cost (ICC) and BES degradation. Finally, the Integrated Charging (IC) strategy proves optimal, charging 134 EVs using 99.59% of ES, reducing total COE to 0.141 $/kWh, and resulting in a net saving of 94,479.39 tons in greenhouse gas emissions.