The question ‘what is the cost of electricity interruptions?’ is fraught with lots of complexities as electricity interruption is not a tradable commodity. A closely associated question is ‘from whose perspective should this cost be assessed – the electric utility or its customers?’ Extant research has shown that the primal focus should be on the electricity customer as the electric utility’s revenue loss after an electricity interruption event is significantly less than customers’ interruption cost (CIC). Existing methods of assessing the cost of electricity interruptions are not always consistent, because analysts make different assumptions, primarily in the incorporation of key parameters of electricity interruptions and customer characteristics in their analyses. However, one thing is important: the chosen assessment method should suit the decision-making context in which the cost data will be applied. In this dissertation, both micro- and macro-level approaches were applied to the assessment of the cost of electricity interruptions to commercial and industrial electricity customers. However, the central investigation is the micro-level assessment of the direct financial cost of electricity interruptions to suit value-based reliability planning and power system operations management. The cost assessment was done from the business customer’s viewpoint via a firm-level survey of commercial and manufacturing businesses in Cape Town. Three CIC models were developed from an analysis of the survey data viz. a time-invariant average interruption cost (TIAIC) model, a time-varying average interruption cost (TVAIC) model, and a time-varying probabilistic interruption cost (TVPIC) model. All three models were applied in an assessment of reliability worth indices for a case study distribution system to demonstrate the practical application of the cost data. The results showed that the TVPIC model is more effective for describing CIC as it accounts for the time-dependencies and uncertainty in CIC estimates. The TVPIC allows for an evaluation of the impact of different confidence levels in decision-making. Reliability worth indices like ECOST derived based on the TVPIC can be expressed as Rands@Risk in different season-time windows. This allows for optimal implementation of contingency measures like load shedding or reliability improvement programs like switch/disconnect placement on distribution feeders. An exploratory macroeconomic analysis was also done using an input-output (IO) model that allowed the investigation of the effect of the removal of the electricity sector from intersectoral interactions in South Africa’s economy. Based on the model’s framework and assumptions, the potential economy-wide cost of a day-long blackout was estimated to be approximately R2.2 billion. Compared to estimates of the economic cost of past load shedding events, this figure seemed to be a very optimistic estimate and a potential lower bound of a day-long blackout in South Africa. Also, the relationship between the firm-level survey and the macroeconomic IO approaches to estimating the cost of electricity interruptions was assessed via a case study of the weekly cost of load shedding to South Africa’s trade and manufacturing sectors. The ensuing discussions show that caution must be exercised in quoting blanket figures of the cost of load shedding to the South African economy without appropriate description of the basis for estimation.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/31310 |
| Date | 25 February 2020 |
| Creators | Akpeji, Kingsley Oladipo |
| Contributors | Folly, Komla A, Awodele, Kehinde O |
| Publisher | Faculty of Engineering and the Built Environment, Department of Electrical Engineering |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MSc |
| Format | application/pdf |
Page generated in 0.0028 seconds