The planning of distribution networks with earth return is highly dependent on the ground's electrical properties. This study incorporates a load flow algorithm for Single Wire Earth Return (SWER) networks into the planning of such systems. The earth's variable conductive properties are modelled into the load flow algorithm and the model considers load growth over different time periods. It includes optimal conductor selection for the SWER system and can also be used to forecast when an initially selected conductor will need to be upgraded. The planning procedure is based on indices derived through an iterative heuristic process that aims to minimise losses and investment costs subject to load flow constraints. A case study in Uganda was used to test the model's practical application.

Power flow in earth return distribution systems typically depends on geographical location and specific earth properties. The planning of such systems has to take into account different operational and safety constraints from conventional distribution systems. This work presents the mathematical modeling and planning of Single Wire Earth Return (SWER) power distribution networks. The SWER load flow is modeled and formulated as an optimization problem. Then by using a heuristic iterative procedure, a planning algorithm is developed for the SWER system. The developed procedure includes optimal feeder routing and overhead conductor selection for both primary and lateral feeders with load growth over several time periods. A 30 node test network extracted from a rural area in Uganda is used to test the algorithm's practical application to give reasonable and consistent results. The model presented can be used in planning SWER networks for areas which have previously not been electrified as well as determining suitable upgrades for existing SWER distribution feeders. The algorithm's mathematical modeling and simulations were done using the General Algebraic Modeling System (GAMS).Index Terms--Optimal power flow, power distribution, power system modeling, power system planning.

The use of the ground as the current return path often presents planning and operational challenges in power distribution networks. This study presents optimization-based models for the optimal selection of conductor sizes in Single Wire Earth Return (SWER) power distribution networks. By using mixed integer non-linear programming (MINLP), models are developed for both branch-wise and primary-lateral feeder selections from a discrete set of overhead conductor sizes. The models are based on a mathematical formulation of the SWER line, where the objective function is to minimize fixed and variable costs subject to constraints specific to SWER power flow. Load growth over different time periods is considered. The practical application is tested using a case study extracted from an existing SWER distribution line in Namibia. The results were consistent for different network operating scenarios.

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Countries that have restructured their electricity markets to wholesale markets have had significant benefits, including reduced generation costs, lower transmission losses and better consumer prices. In these markets, generators are dispatched in such a way that the financial benefits of both generator owners (producer surplus) and consumers (consumer surplus) are maximized. Retailers and large-scale consumers transact directly with power producers in a spot market or through contracts at wholesale level. Uganda's current singlebuyer market (in which generation companies sell their power to a single entity that in turn transmits and sells it to distribution companies) was introduced in 2001 after the transition from a vertically integrated monopoly model. The market is expected to evolve into a wholesale market as the next restructuring step. This paper investigates the performance of the Uganda bulk network in a wholesale electricity market environment as modelled in Power World simulator. It considers different operation scenarios and possible infrastructure enhancements required for improved performance. Results showed that in the wholesale market model, transmission energy losses fell from an average of 4.3% to 3.8% compared to the single-buyer model due to more efficient network utilization. The economic analysis showed that off-peak and peak prices in the wholesale market system were 68.6% and 13.5% lower than in the current market respectively. However, old high loss transmission lines contributed to higher energy prices at receiving nodes. Transmission congestion, whose cost is embedded in a Location Marginal Price, caused sharp increases in the market's prices; this was addressed by using the network reconfiguration technique.

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