“…Corrective and preventive load shaping activities are applied to assess their impact on the reliability of generating systems [6], [7]. Load shaping has been addressed to estimate production reliability and cost [14]. Renewable energies and load shaping have been integrated in [15], [16], [17] to evaluate the adequacy of supply.…”
The load shaping technique is an important key that has been widely implemented inelectrical power systems. The benefits of this activity involve system reliability enhancement and operation requirement satisfaction. In this study, the benefits of load shaping are investigated based on reliability impact. First, the reliability indices have been assessed with no original load. Secondly, the same indices are assessed when load shaping is considered. Results show that the proposed model yields higher accurate reliability assessment and, therefore, a more robust strategy to be implemented. Monte Carlo simulation is utilized to calculate predicted energy not supplied.The paper demonstrates IEEE reliability test system. It describes a comparison of reliability of generating systems based on real time assessment.
“…Corrective and preventive load shaping activities are applied to assess their impact on the reliability of generating systems [6], [7]. Load shaping has been addressed to estimate production reliability and cost [14]. Renewable energies and load shaping have been integrated in [15], [16], [17] to evaluate the adequacy of supply.…”
The load shaping technique is an important key that has been widely implemented inelectrical power systems. The benefits of this activity involve system reliability enhancement and operation requirement satisfaction. In this study, the benefits of load shaping are investigated based on reliability impact. First, the reliability indices have been assessed with no original load. Secondly, the same indices are assessed when load shaping is considered. Results show that the proposed model yields higher accurate reliability assessment and, therefore, a more robust strategy to be implemented. Monte Carlo simulation is utilized to calculate predicted energy not supplied.The paper demonstrates IEEE reliability test system. It describes a comparison of reliability of generating systems based on real time assessment.
“…Considerable work has been performed on the load shifting technique as peaking units. Load shifting has been proposed under generation adequacy assessment to measure the influance of peak shaving activity on the production cost and reliability [9]. Peak clipping activity has been thoroughly studied in [10] to assess its effect on the reserve margin and available generating capacity.…”
<p><span>The load shifting technique is widely implemented in electrical power generation due to its considerable impact on system reliability. The evaluation of load shifting benefits towards the adequacy of generation systems requires an accurate assessment. If the generation unit’s capacity is insufficient to meet the system load, then assistance is required from alternative sources. Load shifting, as a primary demand-side management technique, is used efficiently in electrical power networks given that the energy clipped/curtailed owing to load curtailment and peak clipping can be recovered during the off-peak period. The reliability of a generic framework for the prospective integration of a load shifting technique, with preventative and corrective actions as alternatives to peaking units, is investigated in this study. The optimal rate of load shifting in terms of expected energy not supplied is also investigated. Results show that preventive load shifting (PLS) can act as peaking units when the total generated capacity is within specific limits. Meanwhile, corrective load shifting can act as a better alternative than PLS and peaking units. To calculate expected energy not supplied, sequential Monte Carlo simulation is utilized. This study is conducted using the IEEE reliability test system.</span></p>
“…The economic and environmental effects after integrating DSM and supply-side management strategies were studied [19]. Peak-clipping technique was modelled to evaluate the worth of DSM in the planning framework of generation systems [20]. Load-shifting technique was analysed by considering the duty cycle of generation units, outage postponability, unit commitment policy, operating reserve, the starting time of generation units, planned outages and running and starting failure repairs [10,21].…”
The load shifting strategy is a form of demand side management program suitable for increasing the reliability of power supply in an electrical network. It functions by clipping the load demand that is above an operator-defined level, at which time is known as peak period, and replaces it at off-peak periods. The load shifting strategy is conventionally performed using the preventive load shifting (PLS) program. In this paper, the corrective load shifting (CLS) program is proven as the better alternative. PLS is implemented when power systems experience contingencies that jeopardise the reliability of the power supply, whereas CLS is implemented only when the inadequacy of the power supply is encountered. The disadvantages of the PLS approach are twofold. First, the clipped energy cannot be totally recovered when it is more than the unused capacity of the off-peak period. The unused capacity is the maximum amount of extra load that can be filled before exceeding the operator-defined level. Second, the PLS approach performs load curtailment without discrimination. This means that load clipping is performed as long as the load is above the operator-defined level even if the power supply is adequate. The CLS program has none of these disadvantages because it is implemented only when there is power supply inadequacy, during which the amount of load clipping is mostly much smaller than the unused capacity of the off-peak period. The performance of the CLS was compared with the PLS by considering chronological load model, duty cycle and the probability of start-up failure for peaking and cycling generators, planned maintenance of the generators and load forecast uncertainty. A newly proposed expected-energy-not-recovered (EENR) index and the well-known expected-energy-not-supplied (EENS) were used to evaluate the performance of proposed CLS. Due to the chronological factor and huge combinations of power system states, the sequential Monte Carlo was employed in this study. The results from this paper show that the proposed CLS yields lower EENS and EENR than PLS and is, therefore, a more robust strategy to be implemented.
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