Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH / (Record no. 97589)

MARC details
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fixed length control field 04431ntm a2200373 i 4500
003 - CONTROL NUMBER IDENTIFIER
control field MY-KuUP
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251125110110.0
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 220908t20212021my a|||fr|||| 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE000910 (Local)
Qualifying information hardback
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
Language of cataloging eng
Transcribing agency UMP
Description conventions rda
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) KK.H34 2021 r Thesis
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Norhafidzah Mohd Saad,
Relator term author.
245 10 - TITLE STATEMENT
Title Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH /
Statement of responsibility, etc. Norhafidzah Mohd Saad
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Pahang :
Name of producer, publisher, distributor, manufacturer UMP,
Date of production, publication, distribution, manufacture, or copyright notice 2021
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice © 2021
300 ## - PHYSICAL DESCRIPTION
Extent xix, 196 pages :
Other physical details Illustration ;
Dimensions 30 cm. +
Accompanying material 1 CD-ROM
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
336 ## - CONTENT TYPE
Content type term text
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337 ## - MEDIA TYPE
Media type term unmediated
Source rdamedia
337 ## - MEDIA TYPE
Media type term computer
Source rdamedia
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Carrier type term volume
Source rdacarrier
338 ## - CARRIER TYPE
Carrier type term computer disc
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
500 ## - GENERAL NOTE
General note College of Engineering
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2021
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical reference
520 3# - SUMMARY, ETC.
Summary, etc. In recent years, photovoltaic distributed generation (PVDG) has seen rapid growth due to its benefits in supporting the power system network, enhancing the transmission and distribution of power, and minimizing power congestion. PVDGs are connected directly to the load and produce power locally for the users, thus help to relieve the entire grid by reducing the demand especially during the peak load. Due to the random nature of the weather and occurrences of uncertainty, the planning and optimization of PVDG in the power system network with predicted uncertainty in photovoltaic generations and load variations are of crucial importance to minimize power losses. Thus, this research aims to develop a new optimization framework based on Monte Carlo embedded hybrid variant mean – variance mapping optimization (MVMO-SH) for the planning of PVDGs by considering these uncertainties. In this work, the probabilistic method in managing the risk of solar irradiance uncertainty with load variability is prepared. Uncertainty management is focused on the Malaysian tropical climate. Using meteorological data for one reference year, the Monte-Carlo simulation is performed in the Beta probability density function (PDF) to model continuous random variables of solar irradiances. For the load modelling studies, the Monte Carlo simulation is performed in Gaussian PDF to develop a probability model of various types of loads. The urban residential, commercial and industrial load profiles for one reference year are used for the load modelling. The probabilistic values of PV generation and load models are employed as the input data to the load flow analysis for the radial distribution network. The load flow patterns will significantly have affected when uncertain PV generation – load models are considered into the power flow algorithm. A new method of probabilistic backward – forward sweep power flow (BFSPF) based on Monte Carlo – PDF is developed as the fitness evaluation for the PVDG planning. A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. The objective function is to minimize the active power loss (APL) index. The proposed algorithm is applied to the standard radial test system to examine the usefulness and effectiveness of the proposed method. The impacts of PVDG on the power system network have been examined. As the results of the study, the uncertainty model of solar irradiance in Monte Carlo – Beta PDF has shown an almost similar pattern with less than 15% deviation as compared to the model from SEDA. The reductions in the power system’s total power losses have been shown with appropriate planning of PVDG in the power system network considering uncertainty in PV generation and load variations based on the Malaysian Tropical climate. When probabilistic BFSPF is optimized by MVMO-SH embedded Monte Carlo – PDF under uncertainties, the results show a better APL index compared to utilizing PSO and GA. The results also revealed that the uncertainties had the greatest influence on the optimal planning of PVDG in the power system network.
610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element College of Engineering
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Universities and colleges
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Thesis
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Thesis
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost Library of Congress Classification   Not for loan Reference UMPLIB GAMBANG UMPLIB GAMBANG 08/09/2022   KK.H34 2021 r Thesis T000001902 08/09/2022 1 08/09/2022 Thesis
  Not lost Library of Congress Classification   Not for loan Reference UMPLIB GAMBANG UMPLIB GAMBANG 08/09/2022   CD13115 T000001903 30/01/2023 1 08/09/2022 Thesis

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