Multi-objective and multi-criteria optimization for power generation expansion planning with CO2 mitigation in Thailand

• Main Authors: Kamphol Promjiraprawat, Bundit Limmeechokchai
• Format: Article
• Language: English
• Published: Prince of Songkla University 2013-06-01
• Series: Songklanakarin Journal of Science and Technology (SJST)
• Subjects: power generation expansion planning (PGEP); multi-objective genetic algorithm (MOGA); analytic hierarchy process (AHP); pareto optimality
• Online Access: http://rdo.psu.ac.th/sjstweb/journal/35-3/35-3-349.pdf

In power generation expansion planning, electric utilities have encountered the major challenge of environmental awareness whilst being concerned with budgetary burdens. The approach for selecting generating technologies should depend on economic and environmental constraint as well as externalities. Thus, the multi-objective optimization becomes a more attractive approach. This paper presents a hybrid framework of multi-objective optimization and multi-criteria decision making to solve power generation expansion planning problems in Thailand. In this paper, CO2 emissions and external cost are modeled as a multi-objective optimization problem. Then the analytic hierarchy process is utilized to determine thecompromised solution. For carbon capture and storage technology, CO2 emissions can be mitigated by 74.7% from the least cost plan and leads to the reduction of the external cost of around 500 billion US dollars over the planning horizon. Results indicate that the proposed approach provides optimum cost-related CO2 mitigation plan as well as external cost.