Abstract
The Saudi Electricity Company (SEC) in Jeddah city is facing a big challenge in the operations of power transmission and distribution during the next years, actually the power demand exceeds the electricity endurance and the gap will increase with the expected growth in different activity sectors. Problems in electricity supply during the last three years especially in summer season, gave an indicator for the need to build new transmission/distribution substations year after another. A very natural question is to ask: How many substations are required in future? And what is the optimum schedule for their establishment?
This paper focuses on the electricity field in Jeddah; it is devoted for predicting and economically scheduling the needed number of electric transmission/distribution substations for long-term time horizon (10 years). The forecasting is based on predicting the electricity total demand in each year and then finding the needed number of substations for each year. The scheduling is aiming at minimizing the total cost based on a dynamic programming model under the constraints of needed demand and budget availability. The model requires formulating an appropriate recursive relationship for the problem. The decision variables are the number of transmission/distribution substations to be built in each year (stage). The state of the system is the number of transmission/distribution substations still required in remaining years. The objective function is to minimize the total cost for establishing the substations under the needed demand and budget constraints.
The proposed dynamic programming model will provide SEC with a systematic scientific procedure for determining the optimal combination of decisions to determine the number of substations to be built in each year during the planning time horizon. It is very important and vital issue for SEC, it will help for optimal scheduling on a global scope under the constraints of needed demand and budget availability.