Browsing by Author "Lindner, Berndt Gerald"
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- ItemBi-objective generator maintenance scheduling for a national power utility(Stellenbosch : Stellenbosch University, 2017-03) Lindner, Berndt Gerald; Van Vuuren, J. H.; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.ENGLISH ABSTRACT: One of the key focus areas for the management of a power utility in a regulated energy market is planned preventative maintenance of the power generating units in its power system. The so- called generator maintenance scheduling (GMS) problem refers to finding a schedule according to which the planned maintenance can be performed on the generating units in a power system. A novel bi-objective optimisation model is proposed in this dissertation for the GMS problem in which demand satisfaction reliability is maximised and electricity production cost is minimised. The first scheduling objective is one of the most common objectives in GMS problems in the literature, namely minimising the sum of squared net reserve levels. This objective serves to create an even (reliable) margin of generating capacity over expected demand. The second scheduling objective is the (linear) production cost associated with a maintenance plan of all the generating units in a system. The latter objective is aimed at exploiting the following correlation: planning maintenance on a cost-efficient power station during a high-demand period incurs a higher fuel cost. Production cost is simply taken as fuel cost in this dissertation since it is the most prominent production cost component of power generation. Dominance-based multi-objective simulated annealing is adopted as model solution technique. Solving the aforementioned model clearly demonstrates that maintenance schedules which min- imise the sum of squared reserves are typically also associated with low production costs, but that the lowest sum of squared reserves maintenance schedule does not necessarily achieve the lowest production cost (a sentiment also reported in the literature). Hence there is a need for adopting a multi-objective modelling approach in the context of GMS problems in search of trade-off solutions rather than adopting a standard single-objective modelling paradigm. A sensitivity analysis is performed in respect of model constraint relaxations and the degree of constraint violations. In the process, certain soft constraints which sensitively influence the model objectives are identified. A decision support system, whose working is based on the bi-objective optimisation model described above, is designed and a concept demonstrator of this system is implemented on a personal computer. This concept demonstrator may be used to find and analyse trade-off solutions to instances of the GMS model and offers interactive features which facilitate sensitivity analyses in a very natural way. The viability and practical use of the concept demonstrator is finally illustrated by applying it to two realistic GMS case studies. It is found that the decision system is capable of producing high-quality sets of trade-off maintenance schedules in each case.