Impact Of Demand-Side Management On Generating Systems Adequacy Assessment

Electrical power systems have to be aware of the major challenges that still lie ahead, for example, the massive penetration of electrical vehicle and load and supply-side uncertainties. Since, the adequacy of power supply assessment is an important process in power systems planning phase, demand-side management (DSM) programme is one of the most efficient and applicable solution to be considered. If the generation unit’s capacity is insufficient to meet the system load, then assistance is required from alternative sources. A load shifting strategy is a form of DSM programme, which is widely implemented in electrical power generation due to its considerable impact on system reliability and efficiency. The load shifting strategy is conventionally performed using the preventive load shifting (PLS) programme. PLS is implemented usually when power systems experience contingencies that jeopardise the reliability of the power supply. The disadvantages of the PLS approach are threefold. First, the clipped energy cannot be totally recovered when it is more than the unused capacity of the off-peak period. Second, the PLS approach performs load clipping without discrimination between adequacy and inadequacy of power supply period. Third, the more number of peak clipping and energy recovery action, the more DSM programme uncertainty. In this study, the corrective load shifting (CLS) program is proposed as the better alternative to PLS. The CLS program has none of PLS disadvantages because it is implemented only when there is power supply inadequacy. Generating capacity adequacy assessment is usually performed by using two-state model in which all generation units transit only between up and down states regardless of the types of generators. The two-state model does not take the partial outage of the large thermal generation units into consideration. As well, the two-state model cannot be properly used to model peaking and cycling generation units, as they may not be needed when they are out of service due to an unplanned outage. A hybrid model is proposed in this study, which takes into consideration all above assumptions, to increase the accuracy of generating capacity adequacy assessment. When planned maintenance is considered, the risk level is approximately compounded because of the reduction in reserve margin at different times of the year. Uncertain future load requires a higher capacity reserve than fixed load. Thus, the planned maintenance and load forecast uncertainty (LFU) are unavoidable considerations. These two considerations are taken into account to investigate the robustness of CLS comparing to PLS. As will, this study investigates the impact of PLS and CLS as alternatives to peaking units. The findings from this thesis show that the proposed CLS can perform better than PLS and is, therefore, a more robust strategy to be implemented. In addition, the findings show that hybrid model leads to more accurate and realistic assessment of adequacy of supply than two-state model. The application of CLS tends to significantly overcome the effects of LFU and planned maintenance. Thus, CLS is an applicable tool to be adopted and integrated into such considerations to significantly mitigate the expected energy not-supplied deterioration. The sequential Monte Carlo simulation (MCS) was employed in this study. The study was conducted using the IEEE-reliability test system (RTS)