| dc.description.abstract | Uganda with an installed generation capacity of 1182.2 MW as of May 2019; identifies electricity as a primary input to industrializing the country. This will foster socioeconomic transformation of its citizens to middle income status. Consequently, the national grid is under radical expansion and new plants such as Xsabo solar plant (20 MW), Isimba (183 MW) and Karuma (600 MW) hydro power plants and several others will increase generation capacity from 1182.2 MW to 2500 MW by 2020.
Electricity is produced on demand to avoid high bulk power storage costs. Generation scheduling involves determination of startup and shutdown times and power outputs of all generating units at each time step, over a specified scheduling period. The scheduling of electricity production in Uganda is done by Uganda Electricity Transmission Company Limited considering only the type of generation plants available to ensure demand-supply balance and grid stability. Therefore, there is need for a scheduling procedure that not only maintains the grid in equilibrium but also maximizes utilization of available plants, minimizes electricity generation and transmission costs while reducing bulk network constraints.
An alternative generation scheduling algorithm was successfully formulated and assessed. The algorithm begins with an hourly load forecast to establish system demand and ends with optimum hourly generation schedule for connected plants. Application of the algorithm to a case study of Uganda 132 kV network, revealed significant improvement in the system performance exhibited by improved node voltage regulation by 3.0 % or 4.0 kV. There was redistribution of line loadings to improve transmission capacity usage, reduction of bulk network loss by 3.2 % consequently reducing cost of transmitting power equivalent to US$ 156,971 annual saving. In addition, plant utilization factors of 65.8 % (Owenfalls), 91 % (Bujagali), 10 % (Electromaxx) and 86.3 % (Jacobsen) reduced cost of generating electricity by 31.3 %, saving US$ 23,462,489 annually. | en_US |
