DEVELOPMENT OF HYBRID ENERGY SYSTEM FOR FUNGLING TOWN OF TAPLEJUNG, NEPAL

Abstract

Renewable energy is a proven means to enhance the quality of rural life. It is more economic and serves better when hybridized. A hybrid renewable energy system is very cost effective and has higher reliability if it is optimized with proper methodology and dispatch control strategy while addressing the site strengths and limitations. This dissertation work aims to meet the energy demand of a typical isolated village town Furigling Town in Taplejung district of Nepal with minimum possible cost of energy. Unlike other studies, demand constraint of components is also considered which aims at reduction of unnecessary energy conversion and component rating. This also simplifies the control strategy as well as reduces the human involvement. A Build-Lease-Transfer model to build a community bio-digester is also proposed that generates biogas from the municipal solid waste. On the other hand, the bio-digester is also found to reduce the burden of fuel cost and hence resulted to a reduced levelized cost of energy, by which the community could be benefited. The proposed simulation and optimization tool written in Java programming has two broad parts: simulation part and optimization parts. The simulation part has a user supplied search space with different practical sizes of the components right from zero. The proposed tool makes all the possible combination of the components with the given sizes and simulates the energy demand against energy generated hour by hour for a period of one year. Any surplus energy after battery charging is dumped and any deficit of energy after battery discharging is recorded hourly. At the end of the simulation period, the total (annual) energy deficit is compared with total (annual) energy supplied. If the value of annual capacity shortage defined as the ratio of annual energy shortage to the annual energy supplied is in acceptable range, levelized cost of energy is calculated and recorded. Finally, the best combination that yields the minimum levelized cost of energy while satisfying the constraints is selected and recommended.