International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Blog/Latest News Contact Us
10th percentile
Powered by  Scopus
Scopus coverage:
Nov 2018 to May 2020


IJSTR >> Volume 3- Issue 12, December 2014 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Optimal Hydrothermal Energy Generation for Ghana

[Full Text]



Christian John Etwire, Stephen B. Twum



Keywords: Mixed Integer Linear Programming, Power Generation Scheduling, Marginal Cost, Unit Commitment, Economic Dispatch, Margin cost and Branch and Bound.



Abstract: Power production and distribution in Ghana is ever more becoming erratic and expensive, both for the power producer and the consumer. It is in this regard that an investigation of hydrothermal power generation scheduling is undertaken for a major power producer in the country. The goal of the study was to determine an optimal power production schedule that meets daily load demands at minimum cost of production and also ascertain the marginal cost of producing electricity per day and therefore tariff rate. The problem was formulated as Mixed Integer Linear Programming (MILP) and the resulting model tested using real data obtained from a major power producer in Ghana. The test results show that daily load demands could be met at a minimum cost. Furthermore, the marginal cost of producing power obtained from the dual of the MILP model provided insight into the appropriate Tariff that is reasonable for the power producer to charge consumers.



[1] Ana Viana and Joao Pedro Pedroso (2012), A new MILP-based approach for Unit Commitment in power production planning, International Journal of Electrical Power and Energy Systems. Vol. 44, pp. 997-1005

[2] Blum, C. and Roli, A. (2003). Metaheuristics in combinatorial optimization: Overview and conceptual comparison 35 (3). ACM Computing Surveys. pp. 268–308.

[3] Cornuejols Gerard (2008).Valid Inequalities for Mixed Integer Linear Programs. Mathematical Programming Ser. B, pp. 112:3-44.

[4] Foster Vivien and Nataliya Pushak, (2011). Ghana‘s Infrastructure: A Continental Perspective. Washington, DC: World Bank Policy Research Paper No.5600.

[5] Germán Morales-España, Jesus M. Latorre y, and Andres Ramos (2013), Tight and Compact MILP Formulation of Start-Up and Shut-Down Ramping in Unit Commitment, IEEE Transactions on Power Systems, vol. 28, no. 2, pp.1288-1296.

[6] John E., Mitchell (2002). "Branch-and-Cut Algorithms for Combinatorial Optimization Problems". Handbook of Applied Optimization: 65–77.

[7] José M. Arroyo, and Antonio J. Conejo, (2004), Modeling of Start-Up and Shut-Down Power Trajectories of Thermal Units, IEEE Transactions ON Power Systems, VOL.19, NO.3, p.234-242

[8] Land A. H. and Doig A. G. (1960). An automatic method of solving discrete programming problems. Econometrica 28 (3). pp. 497–520

[9] Nadia Zendehdel, Ali Karimpour and MajidOloomi (2008), Optimal Unit Commitment Using Equivalent Linear Minimum Up and Down Time Constraints, 2nd IEEE International Conference on Power and Energy. Malaysia, pp. 1021-1026.

[10] Ni, E. &Luh, P. (2000), optimal integrated bidding and hydrothermal scheduling with risk management and self-scheduling requirements, in ‘The 3rd World Congress on Intelligent Control and Automation’, P. R. China, pp. 2023–2028.

[11] Singiresu S. Rao (2010), Engineering Optimization: Theory and Practice. 4th Ed. John Wiley & Sons, Inc., Hoboken, New Jersey.

[12] Sinha N, R. Chakrabarti and P. K. Chattopadhyay, “Evolutionary Programming Techniques Economic Load Dispatch,” IEEE Trans. on Evolutionary Computation, vol. 7, no. 1, pp. 83 – 94.

[13] Sullivan Arthur and Steven M. Sheffrin (2003), Economics: Principle in Action. Upper Saddle River New Jersey, Pearson Prentice Hall, pp.111

[14] Taha H.A,(2011), Operations Research: An Introduction 9th Ed. Pearson Edu. Inc., Prentice Hall USA.

[15] Talbi, E-G. (2009). Metaheuristics: from design to implementation. John Wiley & Sons, Inc., New Jersey.

[16] Tseng C. L., Li A. C. and Oren S. (2000), Solving the Unit Commitment Problem Unit Decommitment Method, journal of optimization theory and applications, Vol. 105, No. 3, pp. 707-730.

[17] Warwick K., A. O. Ekwue and R. Aggarwal (1997), Artificial Intelligence Techniques in Power Systems, IEEE Trans on Power Systems, Vol 11(1), pp. 475-482.

[18] Williams H.P., (1999), Model Building in Mathematical Programming 4th Ed. John Wiley & Sons Ltd., England.

[19] Xu, J., Luh, P., White, F., Ni, E. &Kasiviswanathan, K. (2006), ‘Power portfolio optimization in deregulated electricity markets with risk management’, IEEE Transactions118. VOL. 21, NO. 4,