A HYBRID SIMULATION APPROACH IN DEVELOPING A RISK QUANTIFICATION MODEL FOR COAL PROCUREMENT IN POWER GENERATION

• Main Authors: Jafni Ibrahim, Hasimah Sapiri, Razman Mat Tahar
• Format: Article
• Language: English
• Published: UUM Press 2015-03-01
• Series: Journal of ICT
• Online Access: https://www.scienceopen.com/document?vid=64e59a19-b95b-48d2-ab3d-c25db588875d

All energy systems provide some level of security to its consumers. However, the right or optimum level of security is very diffi cult to assess. In order to make a comparison between the cost of providing energy security and level of security, the quantifi ed risks have to be in the common accounting platform of cost. Then, an optimum level of security and cost can be estimated using appropriate methods. Since no such attempts have been done to compare the risks and the cost in the same platform, i.e. monetary unit, it is unpractical to determine the optimum point between the risks and cost of providing security in any energy systems. The objective of this paper is to present a new hybrid simulation model in risk analysis which computes the total exposure of coal procurement in power generation through the summation of quantifi ed supply shortage risk in monetary terms and the cost of coal procurement. The hybrid simulation model is made up of two main components: 1) Dynamic Risk Calculation Program (DR-P) which was developed in System Dynamics platform for capturing the effect of dynamics behavior of price toward coal procurement risk, and 2) Non-delivery Probability Table Program (NdPT-P) which was developed in Matlab platform for computing all possible shortage level and the probability of shortage in selected coal procurement portfolio. The result from this paper has shown that the risks of coal procurement were increased as the cost of coal procurement were decreased and vice versa. However, the summation of risk and cost which give the total exposure of coal procurement has provided more accurate information for selecting the best coal procurement portfolio option.