Agents for fuzzy indices of reliability power system with uncertainty using Monte Carlo algorithm

Shalash, Nadheer A.; Ahmad, Abu Zaharin

doi:10.1109/peoco.2014.6814436

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…2. Each fuzzy load number is defined by three values of load to usetriangular fuzzy numbers [14,16] comprehensive effects of transmission line [18]. In Table I, The fuzzy numbers offered ten satisfaction levels in addition, area percentage of loads and the maximum degree of membership.…”

Section: Proposed Methodsmentioning

confidence: 99%

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Fuzzy Numbers Based on Energy Indicators of Reliability Power System

AShalash¹,

ZaharinAhmad²

2016

ELELIJ

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This paper presents the approach of fuzzy numbers for reliability calculation of electrical energy indices and compared to an analytical method. In this paper, the fuzzy numbers which are represented by triangular fuzzy numbers are used to evaluate the load duration curve and the probabilities capacity generators that are in services, in term of the expected energy not supplied (EENS), loss of energy expectation (LOEE) and the energy index of the reliability (EIR). A case study based on the Malaysia distribution network (DISCO-Net) is carried out.The proposed method shows a simple implementation andthe results seem to be a good approximation to the analytical approach.

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Section: Proposed Methodsmentioning

confidence: 99%

“…The fuzzy approach must be derived before an action is taken by an engineer. In this paper, the special class of fuzzy numbers for load called triangular fuzzy numbers is used [12,16].The fuzzy set G is called a normal fuzzy set. A fuzzy number is a fuzzy method in the load that is both convex and normal.…”

Section: Fuzzy Numbermentioning

confidence: 99%

Fuzzy Numbers Based on Energy Indicators of Reliability Power System

AShalash¹,

ZaharinAhmad²

2016

ELELIJ

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“…Power loss is left out of the equation, the maximum AP is obtained when the resistive of the power transmission line is very small near to zero, that means the power loss can be neglected, because it needs to test distribution indices, and regulated power levels are taken for granted. They are acceptable objects for dependability analysis (Shalash et al. , 2014).…”

Section: Load Flow Analysismentioning

confidence: 99%

Reliability assessment of grid-connected multi-inverter for renewable power generation sector

Abed

Mhalla²

2023

AGJSR

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PurposeThe paper aims to present a grid-connected multi-inverter for solar photovoltaic (PV) systems to enhance reliability indices after selected the placement and level of PV solar.Design/methodology/approachIn this study, the associated probability is calculated based on the solar power generation capacity levels and outages conditions. Then, based on this probability, dependability indices like average energy not supplied (AENS), expected energy not supplied and loss of load expectations (LOLE) are computed, also, another indices have been computed such as (customer average interruption duration index (CAIDI), system average interruption frequency index (SAIFI) and system average interruption duration index (SAIDI)) addressing by affected customers with distribution networks reliability assessment, including PV. On the basis of their dependability indices and active power flow, several PV solar modules installed in several places are analyzed. A mechanism for assessing the performance of the grid's integration of renewable energy sources is also under investigation.FindingsThe findings of this study based on data extracted form a PV power plant connected to the power network system in Diyala, Iraq 132 kV, attempts to identify the system's weakest points in order to improve the system's overall dependability. In addition, enhanced reliability indices are given for measuring solar PV systems performance connected to the grid and reviewed for the benefit of the customers.Originality/valueThe main contributions of this study are two methods for determining the reliability of PV generators taking into consideration the system component failure rates and the power electronic component defect rates in a PV system which depend on the power input and the power loss using electrical transient analysis program (ETAP) program.

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“…The inertia weight ω in ( 6) is employed to drive the convergence of the PSO. Generally, the inertia weight ω is based on the following formula [23]- [25]:…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Short term load forecasting using evolutionary algorithm for Tajikistan

Hussein,

Abood,

Firuz

et al. 2023

IJPEDS

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<p>Load forecasting is a significant element in the energy management system of power systems. Precise load forecasting aids electric utilities to conduct decisions of unit commitment, reduction of spinning reserve capacity, and schedule device maintenance plan. Furthermore, load forecasting contributes to reducing the generation cost, and it is fundamental to the reliability of the power systems. On the other hand, short-term load forecasting is substantial for economic running. The forecasting precision directly affects the reliability, economy running and supplying power quality of the power system. Hence, finding the required load forecasting method to enhance the accuracy is valuable for forecasting precision. This paper proposed particle swarm optimization (PSO) to improve working support vector machine (SVM), SVM regression model is derived; also derived SVM with PSO. Support vector machine (SVM) model is adopted with and without PSO based on the historical load data and meteorological data of Tajikistan country, analysis the various factors affecting the forecast. The historical data and the load forecasting factors to be considered are normalized. The two parameters of SVM significantly influenced the model, and therefore it optimized using evolutionary algorithm.</p>

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Agents for fuzzy indices of reliability power system with uncertainty using Monte Carlo algorithm

Cited by 6 publications

References 12 publications

Fuzzy Numbers Based on Energy Indicators of Reliability Power System

Fuzzy Numbers Based on Energy Indicators of Reliability Power System

Reliability assessment of grid-connected multi-inverter for renewable power generation sector

Short term load forecasting using evolutionary algorithm for Tajikistan

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