Browsing by Author "Girma, Zeleke"

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    Long Term Load Forecasting and Transmission System Expansion Planning (Case Study: Central and Southern Region of Ethiopian Electric Power)
    (Addis Ababa University, 2019-07) Girma, Zeleke; Singh, N.P. (Prof.)
    A sustainable supply of electric power is a prerequisite to foster all sorts of development in any country. Development of electricity infrastructure is undoubtedly a capital intensive project that needs a careful planning especially when future expansion of Generation and Transmission systems is taken into consideration. To keep Ethiopia abreast with other developing countries, the existing gap between the electric power demand and supply scenario of the country must be bridged. Till now, the country is still deeply entrenched in constructing opportunity for development due to frequent power outages resulting from an insufficient transmission lines even if there is enough generation capacity for existing demand. Furthermore, inefficient transmission and distribution facilities have been another recounted setback in the electric power sector of the country. Moreover, within the ambient of socio economic development and increase in human population, electric load demand will tend to increase from time to time over the year to come. Thus, the performance of the existing transmission system facilities must be investigated and appropriate expansion planning may be carried out to supply the future load demand of the country Load demand forecasting is an essential process in electric power system operation and planning. It involves the accurate prediction of both magnitude and geographical location of electric load over the different period of the planning horizon. The electric power transmission system has the prominent role of connecting the generation system with distribution system and large industrial consumers. The design and configuration of transmission network should assure the much needed equipoise of electrical load demand and supply for a foreseen future period. In this thesis, long term load forecasting for the whole country is carried out using Artificial Neural Network (ANN) and transmission system expansion planning to supply the future load demand of the country is investigated using highly interactive MATLAB and ETAP 16 software. The performance of the existing transmission system for central and southern regions of the Ethiopian Electric Power (EEP) is investigated through load flow analysis to identify and find the overloading problems in the system. A method for choosing the best possible expansion plan for the transmission system is presented. Furthermore, contingency analysis (CA) is carried out to investigate the performance of the expanded transmission system by simulating the contingencies such as unexpected opening of the power transmission lines, generators tripping condition, sudden changes in power generation and unexpected changes in loads. The long term load forecasting used by Ethiopian Electric power (EEP) and EEP master plan (PB) engineers for next 26 year was Econometric method while the Artificial Neural Network (ANN) does it for 22 years. Both forecasts have the same load profile. The estimated demand in year of 2037 is 137752.09GWh. Comparing the ANN forecast with the earlier EEP master Plane (PB) as well as the updated EEP forecast, total demand is significantly lower, during 2022-2027 period; the single large impact is lower the increased anticipated demand and the export are lower with several belated anticipations beyond 2030. In the Central and Southern region of EEP, there are twenty nine 132/15kV substations. From this, 25 (almost 90%) substations are congested and load shading is imminently looming and frequent power interruption is going during peak hours (morning from 09:30 AM- 12PM and night 06:00PM- 09:00PM.