A stochastic programming model for an energy planning problem: formulation, solution method and application

Abstract

The paper investigates national/regional power generation expansion planning for medium/longterm analysis in the presence of electricity demand uncertainty. A two-stage stochastic programming is designed to determine the optimal mix of energy supply sources with the aim to minimise the expected total cost of electricity generation considering the total carbon dioxide emissions produced by the power plants.Compared to models available in the extant literature, the proposed stochastic generation expansion model is constructed based on sets of feasible slots (schedules) of existing and potential power plants. To reduce the total emissions produced, two approaches are applied where the first one is performed by introducing emission costs to penalise the total emissions produced. The second approach transforms the stochastic model into a multi-objective problem using the -constraint method for producing the Pareto optimal solutions. As the proposed stochastic energy problem is challenging to solve, a technique that decomposes the problem into a set of smaller problems is designed to obtain good solutions within an acceptable computational time. The practical use of the proposed model has been assessed through application to the regional power system in Indonesia. The computational experiments show that the proposed methodology runs well and the results of the model may also be used to provide directions/guidance for Indonesian government on which power plants/technologies are most feasible to be built in the future. Keywords Energy planning • Stochastic programming • Multi-objective optimization 1 IntroductionGlobal electricity production has grown continuously year by year since 1974. According to International Energy Agency (www.iea.org), world gross electricity production has increased from 6,299 to 26,730 TWh between 1974 and 2018 with an average annual growth rate of 3.3 %. Electricity generation can be divided into three types, namely fossil fuel-based, nuclear, and renewable energy power generation. The fossil fuelbased plants include coal, petroleum, and natural gas which produce large quantity of cheap energy with greenhouse gas (GHG) emissions. The renewable energy consists of hydro, solar, wind, geothermal and biomass which generate clean energy (without GHG emissions or potentially carbon neutral in the case of biomass). However, the cost and feasibility of renewable energy are highly dependent on the potential of regions and its weather conditions (Thangavelu et al, 2015). The strategic energy planning includes the medium-to long-term expansion of the electricity generating capacity. Cost effective and low emission energy

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