Multi-objective distribution feeder reconfiguration by considering energy not supplied with distributed generation

Abstract

Original scientific paper Nowadays, the operational performance of the Distribution system can be improved by exchanging the functional links between the elements of the system, called reconfiguration. This paper aims at achieving such optimization through the reconfiguration of distribution systems taking into account various criteria. The newness of the method is in the fact that optimization is evaluated on active power distribution systems i.e by incorporating the distributed generators directly to the main distribution system. This paper presents a proficient method for solving the multi-objective reconfiguration of radial distribution systems with regard to distributed generators. The conformist distribution feeder reconfiguration (DFR) problem cannot meet the reliability requirements. The recommended approach considers reliability (Energy Not Supplied), voltage deviation and power loss problem simultaneously. By taking the reliability objective into account, the DFR problem becomes more complicated than before and it needs to be solved with a precise algorithm. Therefore this study utilizes Non Dominated Sorted Genetic Algorithm-II (NSGA-II) for DFR and Gravitational Search Algorithm (GSA) for DG placement is to find the optimal location and sizing of DGs which minimizes real power loss, Energy Not Supplied (ENS) and improves voltage profile of the network. Keywords: distributed generation; Distribution Feeder Reconfiguration (DFR); Energy not Supplied (ENS); GSA; NSGA-II Rekonfiguracija multi-objektivnog distribucijskog napojnog voda s obzirom na neisporučenu energiju distribuirane proizvodnjeIzvorni znanstveni članak Danas se učinkovitost distribucijskog sustava može poboljšati zamjenom funkcionalnih poveznica između elemenata sustava, to jest rekonfiguracijom. Cilj je rada postići takvu optimizaciju rekonfiguracijom distribucijskog sustava uzimajući u obzir različite kriterije. Novina ove metode je u činjenici da se optimizacija procjenjuje na aktivnim sustavima raspodjele energije tj. ugrađivanjem distribuiranih generatora direktno u glavni distribucijski sustav. U radu se predstavlja napredna metoda za rješavanje multi-objektivne rekonfiguracije sustava radijalne distribucije u odnosu na distribuirane generatore. Konformistički promatran problem rekonfiguracije distribucijskog napojnog voda (DFR) ne može zadovoljiti zahtjevima za pouzdanošću. Preporučeni pristup uzima simultano u obzir problem pouzdanosti (neisporučena energija), devijacije u naponu i gubitka energije. Uzimajući u obzir pouzdanost, DFR problem postaje složeniji nego ranije i treba se riješiti preciznim algoritmom. Stoga se u ovom radu koristi Non Dominated Sorted Genetic Algorithm-II (NSGA-II) za DFR i Gravitational Search Algorithm (GSA) za optimalnu lokaciju i veličinu DG-ija jer se tako minimalizira stvarni gubitak energije, neisporučene energije (ENS) i poboljšava profil napona mreže.Ključne riječi: distribuirana proizvodnja; neisporučena energija (ENS); GSA; NSGA-II; rekonfiguracija distribucijskog napojnog voda (DFR)

Tuning of Nonlinear PID Controller for TRMS Using Evolutionary Computation Methods

“…Our research shows the combination of elevation and azimuth i.e., vertical and horizontal which is better than the errors reported in previous researches [15][16][17], where the error values are reported separately (Vertical or Horizontal). Hence from the results it is observed that by optimizing the α and δ, the results are better than in previous researches [12,13] reported without optimizing α and δ. PSO converges faster in the least optimal parameter in all the cases. Hence PSO shows better result with respect to output response and convergence characteristics.…”

“…Also Gravitational Search Algorithm (GSA) is one of the evolutionary algorithms, proposed by Rashedi et al [11]. It is utilized to find optimal location of Distributed Generation [12] and to design passive power filters for industrial power Systems [13] Tuning the PID controller for MIMO systems using EC such as Differential Search Algorithm (DSA), real coded Genetic Algorithm (RGA) with simulated binary crossover (SBX), Particle Swarm optimization (PSO) and Gravitational Search Algorithm (GSA) are taken in this work.…”