Electricity distribution planning automation involves a great deal of information, residing in different systems. Information sharing among these systems is essential in improving the efficiency and quality of distribution system planning. This paper presents an integrated solution for computerized distribution planning in a geographic information system (GIS) context, a synergy that magnifies the data accessibility between load forecasting and feeder planning tools, sealing the traditional gap between long-term and short-term distribution system planning. A stochastic cell-based load forecasting algorithm is first developed, followed by an optimal load allocation module, NODESIM, which spatially relates the load growth to the vector-based circuit topology from feeder planning tools. NODESIM enables the multi-year distribution system studies in a GIS context, to best assist utility planners in deciding where and when the customers will grow and how to expand the system facilities to meet the demand growth.
