INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 3, ISSUE 12, DECEMBER 2014 ISSN 2277-8616 65 IJSTR©2014 www.ijstr.org Optimal Hydrothermal Energy Generation for Ghana Christian John Etwire, Stephen B. Twum 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. Keywords: Mixed Integer Linear Programming, Power Generation Scheduling, Marginal Cost, Unit Commitment, Economic Dispatch, Margin cost and Branch and Bound. ———————————————————— 1 INTRODUCTION Electricity is a key infrastructure for economic growth of any country. It is a dynamic energy that underpins a wide range of products and services and improves the quality of life, increases productivity and encourages entrepreneurial activity. A reliable and accessible electricity system is critical in enabling Ghana to meet its long-term economic development goals. In recent times, Ghana as a nation has been experiencing frequent power outages across the length and breadth of the country. This is characterized by the inability of the country‘s power sector to maintain its aging equipment as a result of financial constraint due to under-pricing, mismanagement and fluctuations in crude oil prices on the international market as well as the ever increasing electricity demand by residential and industrial users [4]. This study will however, help to improve the efficiency of power generation in the country. For instance, the results of the study could be used by the major power producer in the country to minimize the production cost of electricity while meeting daily load demands and thus ensure reliable and continuous supply of power. Furthermore, the results of the study could provide a basis to charge realistic tariff. Generation scheduling is an important daily activity for electric power generation companies. Since electricity cannot economically be stored, demand and supply have to be matched at all times. The goal of generation scheduling is to determine which generators must be used in which periods in order to generate enough power to satisfy demand requirements and various technological constraints at minimum operating cost [17]. Hydro-thermal power generation scheduling is a multifaceted problem consisting of Unit Commitment and Economic Dispatch problems. Unit Commitment refers to the problem of deciding on the startup and shutdown of the generators while Economic Dispatch refers the problem of deciding on the loading levels of each of the committed generators to generate enough power to satisfy load demand, budgetary and operational constraints at minimum production cost [12].Many of the research works in the area of power generation scheduling using optimization techniques focus on solution methods such as Dynamic Programming, Bender‘s Decomposition, Lagrangian Relaxation (LR) and Integer and Mixed Integer Linear programming depending on the nature of the problem [11]. Integer and Mixed Integer Programming have been widely applied to solve different optimization problems such as the hydrothermal coordination and unit commitment problems [7]. The commonly shared characteristic of these problems is that they have either continuous, discrete variables or mixed variables. Ni and Luh [10] looked at the price based unit commitment problem in a hydrothermal context. The problem was solved using Lagrangian Relaxation (LR), by relaxing the spot and reserve markets transactions constraints in order to obtain one subproblem for each generating unit. Tseng [16] presented a unified unit decommitment (taking off units) method for solving unit commitment problems. The test results showed that the proposed method was more reliable, efficient, and robust than the LR method. Arroyo and Conejo [7] presented a detailed formulation of start-up and shut-down power trajectories of thermal units using Mixed-Integer Linear Programming. Simulation results showed that the proposed formulation was accurate and computationally efficient. Xu et al. [19] dealt with a power portfolio optimization problem that considered thermal, pumped storage and hydro units on the generation side, and forwards and options on electricity on the contracts side. The problem was solved by a Lagrangian Relaxation method, relaxing the load obligation constraints for decoupling the problem into financial market subproblems and generation unit subproblems. Nadia et al [9] looked at Optimal Unit Commitment Using Equivalent Linear Minimum Up and Down Time Constraints. The results showed that the proposed model was efficient and effective. Ana and Pedroso [1] presented a new MILP-based approach for unit commitment in power production planning. Computational analysis showed that the iterative linear method was capable of reaching the optimum of the quadratic model using much less computational time than required for its quadratic programming solution. Morales-Espana et al [5] presented a ______________________________  Christian John Etwire and Stephen B. Twum  Faculty of Mathematical Sciences, University for Development Studies, P.O. box 1350, Tamale, Ghana  Faculty of Mathematical Sciences, University for Development Studies, P.O. Box 1350, Tamale – Ghana,  Corresponding Author’s Email: jecpapa@yahoo.com