MODELLING AND OPTIMIZATION OF HYBRID POWER SYSTEMS FOR RURAL AREAS

Electrification of remote rural areas which do not have accessibility to the national electricity grid is an important issue for many developing countries. The most common solution is using diesel generator to generate electricity. However, this solution has disadvantages such as global warming and high fuel and maintenance cost. This is one of the reason why people are finding the alternative energy sources which are sustainable, renewable and environmental friendly. But, some of the renewable energy sources are seasonal and not available at all time. To overcome this issue, hybrid renewable energy system is utilized with combination of more than one renewable energy sources. This project is aimed to develop a model for hybrid power system optimization using Excel solver with simplex linear programing solving method. The objective function of this model is to find the best combination of energy resources available in the particular area to satisfy the energy needs in the certain area with the lowest cost estimation. The types of energy sources which will be considered are solar energy, wind energy, biomass and hydropower. The model has been developed and validated with the result from another researcher. The result from this model differ 5% to 10% compared with the result that is obtained by Izadyar, Ong, Chong, Mojumder, & Leong using HOMER software. This model gives the optimization result of best hybrid energy configuration at Langkawi, Malaysia which are 9% solar energy, 34% wind energy and 57% hydropower. The error is because this model is using linear programing solving method, which in the reality is not possible and the model used might have some differences with HOMER software. Case study has been done in this project. Kota Kinabalu is chosen to be simulated in the model. The optimization result shows that the best combination is 79% solar energy and 21% wind energy. This program could be improved in the future by using nonlinear programing solving method to increase the accuracy of the program.