Power generation capacity planning under budget constraint in developing countries

Show simple item record

dc.contributor.author Afful‐Dadzie, E.
dc.contributor.author Afful‐Dadzie, A.
dc.contributor.author Awudu, I
dc.contributor.author Banuro, J.K.
dc.date.accessioned 2019-02-12T17:03:46Z
dc.date.available 2019-02-12T17:03:46Z
dc.date.issued 2017
dc.identifier.citation Afful-Dadzie, Anthony (University of Ghana Business School, University of Ghana, Accra (Ghana)); Afful-Dadzie, Eric (Faculty of Applied Informatics, Tomas Bata University in Zlin, Zlin (Czech Republic)); Awudu, Iddrisu (Department of Management, Quinnipiac University, 275 Mt. Carmel Avenue, Hamden, CT 06518 (United States)); Banuro, Joseph Kwaku (University of Ghana Business School, University of Ghana, Accra (Ghana)), E-mail: aafful-dadzie@ug.edu.gh en_US
dc.identifier.other DOI: http://dx.doi.org/10.1016/j.apenergy.2016.11.090
dc.identifier.uri http://ugspace.ug.edu.gh/handle/123456789/27468
dc.description.abstract This paper presents a novel multi-period stochastic optimization model for studying long-term powergeneration capacity planning in developing countries. A stylized model is developed to achieve threeobjectives: (1) to serve as a tool for determining optimal mix, size and timing of power generation typesin the face of budget constraint, (2) to help decision makers appreciate the consequences of capacityexpansion decisions on level of unserved electricity demand and its attendant impact on the nationaleconomy, and (3) to encourage the habit of periodic savings towards new generation capacity financing.The problem is modeled using a stochastic mixed-integer linear programming (MILP) technique underdemand uncertainty. The effectiveness of the model, together with valuable insights derived from consid-ering different levels of budget constraints are demonstrated using Ghana as a case study. The resultsindicate that at an annual savings equivalent to 0.75% of GDP, Ghana could finance the needed generationcapacity to meet approximately 95% of its annual electricity demand between 2016 and 2035.Additionally, it is observed that as financial constraint becomes tighter, decisions on the mix of new gen-eration capacities tend to be more costly compared to when sufficient funds are available en_US
dc.language.iso en en_US
dc.publisher ELSEVIER en_US
dc.subject Generation Capacity Planning en_US
dc.subject Unreserved demand en_US
dc.subject stochastic optimization en_US
dc.subject scenario generation en_US
dc.subject budget constraint en_US
dc.title Power generation capacity planning under budget constraint in developing countries en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search UGSpace


Browse

My Account