Browsing by Author "Pretorius, Coenraad Benjamin"
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- ItemDevelopment of a demand response programme for the coal mining industry(Stellenbosch : Stellenbosch University, 2016-12) Pretorius, Coenraad Benjamin; Vermeulen, H. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: Power grids are facing significant challenges today. Their primary purpose is to provide energy that is reliable, affordable, environmentally friendly and available at the push of a button. The historical power grid based on large, fossil fuel based, centralised power stations is shifting towards a smart grid based on distributed, low carbon power stations. The smart grid of the future is required to be able to adapt and optimise itself in real-time. Demand response is expected to play a major role in balancing supply and demand in future, especially for systems with high penetration of renewable energy. It is important that consumers take an active role in managing their energy consumption and performance. This project focusses on evaluating the potential for demand response in the coal mining industry. The high-level mining processes are reviewed with the view to identify viable demand response assets, i.e. electrical load components that can respond significantly to a demand response event. A detailed analysis of operating parameters and electrical energy consumption profiles of the various mining processes are conducted for six mines, representing both open-pit operations and underground operations. The results indicate that the coal processing plants, draglines and the underground sections represent viable demand response assets. Historical, current and potential demand response events were analysed to characterise the frequency and durations of typical demand response events. These events include pricing based events, voluntary participation programmes, emergency load curtailment and extreme load curtailment. These scenarios were considered both with and without a solar photovoltaic plant on the consumer side of the grid. Regression models, which allow energy consumption to be predicted based on production throughput, were developed for each of the demand response assets. Simulations were conducted to determine the hourly production plan for the demand response assets, with the objective to minimise energy costs. The simulations were limited by the historic operational constraints and the energy constraints, based on the four typical demand response scenarios. The simulations were done for both the MegaFlex and critical peak day tariffs. The results of the simulations indicate that the demand response scenarios could be theoretically accommodated by adjusting production planning while meeting the monthly production throughput. In many cases, potential energy costs savings and production increases may be realised. The need for demand response in the future power grid is clear. It will require changes from governments, utilities and consumers as a crucial first step. The solution is driven by people, behaviour and processes rather than technology. Demand response is, however, further enabled by the advances in smart grids, data analytics, processing power of modern computers and distributed energy resources. The time is apt to develop a clear demand response strategy for South Africa as part of the introduction of smart grid concepts.