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EN
This paper discusses optimal allocation planning of synchronous distributed generation (SDG) on mesh grid power system, using breeder genetic algorithm (BGA) method. This optimization technique was built to allocate SDG units for obtaining the smallest power losses, while all buses voltage awakens in standard value. Furthermore, the proposed method was tested on IEEE 30 bus test system, and the optimal solution was reached for three SDG unit installation on 27.73 MW + j1.502 MVAr total power, with 22.46% power losses reduction.
PL
W artykule omówiono optymalne planowanie alokacji synchronicznej generacji rozproszonej (SDG) w systemie elektroenergetycznym sieci kratowej z wykorzystaniem metody algorytmu genetycznego rozpłodnika (BGA). Ta technika optymalizacji została zbudowana w celu alokacji jednostek SDG dla uzyskania najmniejszych strat mocy, podczas gdy napięcie wszystkich magistrali zawiera się w wartości standardowej. Ponadto zaproponowana metoda została przetestowana na systemie testowym magistrali IEEE 30 i osiągnięto optymalne rozwiązanie dla instalacji trzech jednostek SDG o łącznej mocy 27,73 MW + j 1,502 MVAr, przy obniżeniu strat mocy o 22,46%.
EN
This paper proposes a multiobjective improved particle swarm optimisation (IPSO) for placing and sizing the series modular multilevel converter-based unified power flow controller (MMC-UPFC) FACTS devices to manage the transmission congestion and voltage profile in deregulated electricity markets. The proposed multiobjective IPSO algorithm is perfect for accomplishing the close ideal distributed generation (DG) sizes while conveying smooth assembly qualities contrasted with another existing algorithm. It tends to be reasoned that voltage profile and genuine power misfortunes have generous upgrades along ideal speculation on DGs in both the test frameworks. The proposed system eliminates the congestion and the power system can be easily used to solve complex and non-linear optimisation problems in a real-time manner.
EN
High distribution system power-losses are predominantly due to lack of investments in R&D for improving the efficiency of the system and improper planning during installation. Outcomes of this are un-designed extensions of the distributing power lines, the burden on the system components like transformers and overhead (OH) lines/conductors and deficient reactive power supply leading to drop in a system voltage. Distributed generation affects the line power flow and voltage levels on the system equipment. These impacts of distributed generation (DG) may be to improve system efficiency or reduce it depending on the operating environment/conditions of the distribution system and allocation of capacitors. For this purpose, allocating of distributed generation optimally for a given radial distribution system can be useful for the system outlining and improve efficiency. In this paper, a new method is used for optimally allocating the DG units in the radial distribution system to curtail distribution system losses and improve voltage profile. Also, the variation in active power load in the system is considered for effective utilization of DG units. To evidence the effectiveness of the proposed algorithm, computer simulations are carried out in MATLAB software on the IEEE-33 bus system and Vastare practical 116 bus system.
EN
Due to the increasing need for electricity, insertion of distributed generation (DG) into a distribution system attracts the attention of the deregulated power market. Placing DG in the distribution system inherently reduces the power loss and improves the system voltage profile. The choice of DG, proper placement and sizing of DG all play a vital role. This paper presents an effective methodology to identify the optimum location of multi type DG in the distribution system. The particle swarm optimization (PSO) algorithm and differential evolution (DE) are applied to identify the proper location and size of DG using the distributed generation suitability index (DGSI). The optimum location of DG is identified through DGSI and optimum sizing is done by means of the power loss minimization technique using evolutionary algorithms. The effective power loss reduction and improved system voltage profile are evaluated using sixteen combinations of different types of DGs with the standard IEEE 33-bus test system. The results reveal that power loss reduction and voltage profile improvement are effectively addressed by the DE algorithm.
EN
With Growing Concerns About Voltage Profile And Power Factor At Distribution Networks, The Capacitor Banks Are Invariably Installed For Reactive Power Compensation. The Reactive Power Supplied By Capacitor Banks Is Proportional To Square Of Their Rated Loading Voltage. Capacitor Banks Eventually Increase The Loading Capacity Of Feeders, So As To Supply More Customers Through Same Line Section. Capacitor Banks Can Be Installed Anywhere On The Network. The Idea Of This Paper Is To Reduce Total Power Loss And Ensure Greater Availability Of Capacitor Bank Installed At 132 Kv Grid Station Qasimabad Hyderabad, For Reactive Power Compensation, Even Under Worst Conditions On Distribution System. This Is Achieved By Enhancing Its Location And Size. At Present Capacitor Bank Of Full Size, I.E. Of 1.21 Mvar Is Installed At 11 Kv Bus Of 132 Kv Grid Station Qasimabad Hyderabad. Moreover This Paper Suggests Small Sized Capacitor Banks That Would Be Installed At Different Feeders Instead Of One Large Size Capacitor Bank At 11 Kv Bus. The Voltage Profile And Power Losses With Present Sized Capacitor Bank And The Proposed Small Sized Capacitor Banks Are Compared In This Work. The Distribution Network Has Been Simulated By Using MATLAB .
EN
Static Var Compensator (SVC) is a popular FACTS device for providing reactive power support in power systems and its placement representing the location and size has significant influence on network loss, while keeping the voltage magnitudes within the acceptable range. This paper presents a Firefly algorithm based optimization strategy for placement of SVC in power systems with a view of minimizing the transmission loss besides keeping the voltage magnitude within the acceptable range. The method uses a self-adaptive scheme for tuning the parameters in the Firefly algorithm. The strategy is tested on three IEEE test systems and their results are presented to demonstrate its effectiveness.
EN
This paper presents the application of the improved harmony search (IHS) algorithm for determining the optimal location and sizing of static Var compensator (SVC) to improve the voltage profile and reduce system power losses. A multi-criterion objective function comprising of both operational objectives and investment costs is considered. The results on the 57-bust test system showed that the IHS algorithm give lower power loss and better voltage improvement compared to the particle swarm optimization method in solving the SVC placement and sizing problem.
PL
Artykuł przedstawia zastosowanie algorytmu IHS (Improved harmony search) do określania optymalnej lokalizacji kompensatora mocy biernej. Rezultaty testów wykazały że algorytm zapenia mniejsze straty mocy oraz zniekształcenia w porównaniu do innych metod optymalizacji.
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