Showing 2 results for Load Forecasting
L. Ghods, M. Kalantar,
Volume 6, Issue 3 (9-2010)
Abstract
Prediction of peak loads in Iran up to year 2011 is discussed using the Radial
Basis Function Networks (RBFNs). In this study, total system load forecast reflecting the
current and future trends is carried out for global grid of Iran. Predictions were done for
target years 2007 to 2011 respectively. Unlike short-term load forecasting, long-term load
forecasting is mainly affected by economy factors rather than weather conditions. This
study focuses on economical data that seem to have influence on long-term electric load
demand. The data used are: actual yearly, incremental growth rate from previous year, and
blend (actual and incremental growth rate from previous years). As the results, the
maximum demands for 2007 through 2011 are predicted and is shown to be elevated from
37138 MW to 45749 MW for Iran Global Grid. The annual average rate of load growth
seen per five years until 2011 is about 5.35%
S. Najafi Ravadanegh,
Volume 10, Issue 1 (3-2014)
Abstract
Optimal distribution substation placement is one of the major components of optimal distribution system planning projects. In this paper optimal substation placement problem is solved using Imperialist Competitive Algorithm (ICA) as a new developed heuristic optimization algorithm. This procedure gives the optimal size, site and installation time of medium voltage substation, using their related costs subject to operating and optimization constraints. A multistage and pseudo-dynamic expansion planning is applied to consider dynamic of the system parameters for example, load forecasting uncertainty, asset management and geographical constraints. In order to evaluate the effectiveness of the proposed method a sensitivity analysis of ICA parameters on obtained results is done. A graphical representation of obtained results is used to show the efficiency and capability of the proposed method both from the planning view and graphical aspects. The results show the efficiency and capability of the proposed method which has been tested on a real size distribution network.
