Int. J. of Applied Decision Sciences   »   2017 Vol.10, No.1

 

 

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Title: Policy-based unit commitment problem: a case in a peaking power generation plant

 

Authors: Robert I. Wamilda Jr.; Luke Rey T. Santillan; Kenn Brylle A. Senen; Lanndon A. Ocampo

 

Addresses:
Department of Industrial Engineering, University of San Carlos, 6000 Cebu City, Philippines
Department of Industrial Engineering, University of San Carlos, 6000 Cebu City, Philippines
Department of Industrial Engineering, University of San Carlos, 6000 Cebu City, Philippines
School of Management, University of the Philippines Cebu, 6000 Cebu City, Philippines

 

Abstract: Unit commitment (UC) along with economic load dispatch (ELD) is an integral optimisation problem in the power generation industry. In this paper, policy-based algorithms are developed to address dispatch problems under different system configurations with the benefit of providing flexibility in addressing several desired policies of decision-makers. A case study is conducted in a diesel-fired, power plant in central Philippines to elucidate the proposed approach. Three policies were created to effectively address the optimisation problem: 1) classic UC model; 2) buying and selling strategy; 3) continuous loading strategy with various issues being considered. Results show that the strategies exhibit a significant decrease in total costs and ease of implementation with respect to the current production schedule of the case firm. Furthermore, the second policy provides the least generated cost which implies that generating firms must consider the option to sell power when market prices reach desired levels.

 

Keywords: economic load dispatch; ELD; unit commitment; rule-based algorithm; conventional methodology; constrained optimisation; power generation; case study; diesel-fired power plants; Philippines; buying and selling strategy; continuous loading.

 

DOI: 10.1504/IJADS.2017.10002428

 

Int. J. of Applied Decision Sciences, 2017 Vol.10, No.1, pp.1 - 26

 

Available online: 20 Jan 2017

 

 

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