scholarly journals A graph search algorithm: Optimal placement of passive harmonic filters in a power system

2015 ◽  
Vol 3 (2) ◽  
Keyword(s):  
Power System ◽  
Search Algorithm ◽  
Optimal Placement ◽  
Graph Search

Hybrid Cuckoo Search Algorithm for Optimal Placement and Sizing of Static VAR Compensator

2016 ◽  
pp. 288-326 ◽  
Author(s):  
Khai Phuc Nguyen ◽  
Dieu Ngoc Vo ◽  
Goro Fujita
Keyword(s):  
Power System ◽  
Search Algorithm ◽  
Combinatorial Problem ◽  
Cuckoo Search ◽  
Global Optimum ◽  
Cuckoo Search Algorithm ◽  
Optimal Placement ◽  
Static Var Compensator ◽  
Voltage Deviation ◽  
Teaching Learning

This chapter proposes a Hybrid Cuckoo search algorithm to determine optimal location and sizing of Static VAR Compensator (SVC). Hybrid Cuckoo search algorithm is a simple combination of the Cuckoo search algorithm (CSA) and Teaching-learning-based optimization (TLBO), where the learner phase of TLBO is added to improve performance of Cuckoo eggs. The proposed method is applied for optimizing location and sizing of SVC in electric power system. This problem is a kind of discrete and combinatorial problem. The objective function considers loss power, voltage deviation and operational cost of SVC and other operating constraints in power system. Numerical results from three various tested systems show that the proposed method is better than the conventional CSA and TLBO in finding the global optimum solutions and its performance is also high than others.

scholarly journals Simultaneous placement of FACTS devices using cuckoo search algorithm

2020 ◽  
Vol 11 (3) ◽  
pp. 1344
Author(s):  
Basanagouda N. Patil ◽  
S. B. Karajgi
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Reactive Power Compensation ◽  
Optimal Placement ◽  
Facts Devices ◽  
In Series ◽  
Ac Transmission

The power system deregulation requires thechange in reactive power compensation in the power system. The optimal placement of FACTs (Flexi ble AC transmission system) devices is mandatory to recalculate the reactive power compensation in deregulation case. The FACTs devices generally used in series and shunt conections. Here the various facts devices connected in series & shunt combination simultaneously. The optimal placement and sizing of the devices are done in this paper by formulating the objective function with minimization of cost of the generation and minimizing the cost of Facts devices. MALAB is used for writing the code. IEEE 14 bus system is used to here for testing the system. Placing the FACTs separately and simultaneously are studied in case study. Cuckoo search algorithm is used to identify the solution to the optimization problem.

scholarly journals Generalized optimal placement of PMUs considering power system observability, communication infrastructure, and quality of service requirements

2020 ◽  
Vol 10 (3) ◽  
pp. 2824
Author(s):  
M. M. H. Elroby ◽  
S. F. Mekhamer ◽  
H. E. A. Talaat ◽  
M. A. Moustafa Hassan
Keyword(s):  
Power System ◽  
Minimum Spanning Tree ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Base Station ◽  
Optimal Placement ◽  
Binary Particle Swarm Optimization ◽  
Communication Infrastructure ◽  
Control Center ◽  
System Observability

This paper presents a generalized optimal placement of Phasor Measurement Units (PMUs) considering power system observability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover, the economic study for additional new data transmission paths is considered as well as the availability of predefined locations of some PMUs and the preexisting communication devices (CDs) in some buses. Two cases for the location of the Control Center Base Station (CCBS) are considered; predefined case and free selected case. The PMUs placement and their required communication network topology and channel capacity are co-optimized simultaneously. In this study, two different approaches are applied to optimize the objective function; the first approach is combined from Binary Particle Swarm Optimization-Gravitational Search Algorithm (BPSOGSA) and the Minimum Spanning Tree (MST) algorithm, while the second approach is based only on BPSOGSA. The feasibility of the proposed approaches are examined by applying it to IEEE 14-bus and IEEE 118-bus systems.

Voltage Stability Enhancement with Optimal Placement of IPFC

2019 ◽  
Vol 8 (4) ◽  
pp. 9465-9471
Keyword(s):  
Transmission Line ◽  
Objective Function ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Test System ◽  
Optimal Location ◽  
Optimal Placement ◽  
Utilization Factor ◽  
Location Selection ◽  
Multi Objective

This paper presents a novel technique based on Cuckoo Search Algorithm (CSA) for enhancing the performance of multiline transmission network to reduce congestion in transmission line to huge level. Optimal location selection of IPFC is done using subtracting line utilization factor (SLUF) and CSA-based optimal tuning. The multi objective function consists of real power loss, security margin, bus voltage limit violation and capacity of installed IPFC. The multi objective function is tuned by CSA and the optimal location for minimizing transmission line congestion is obtained. The simulation is performed using MATLAB for IEEE 30-bus test system. The performance of CSA has been considered for various loading conditions. Results shows that the proposed CSA technique performs better by optimal location of IPFC while maintaining power system performance

scholarly journals Optimal Placement and Sizing of an Energy Storage System Using a Power Sensitivity Analysis in a Practical Stand-Alone Microgrid

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1598
Author(s):  
Dongmin Kim ◽  
Kipo Yoon ◽  
Soo Hyoung Lee ◽  
Jung-Wook Park
Keyword(s):  
Sensitivity Analysis ◽  
Energy Storage ◽  
Power System ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Optimization Techniques ◽  
Optimal Placement ◽  
Stable Operation ◽  
Analytical Approaches

The energy storage system (ESS) is developing into a very important element for the stable operation of power systems. An ESS is characterized by rapid control, free charging, and discharging. Because of these characteristics, it can efficiently respond to sudden events that affect the power system and can help to resolve congested lines caused by the excessive output of distributed generators (DGs) using renewable energy sources (RESs). In order to efficiently and economically install new ESSs in the power system, the following two factors must be considered: the optimal installation placements and the optimal sizes of ESSs. Many studies have explored the optimal installation placement and the sizing of ESSs by using analytical approaches, mathematical optimization techniques, and artificial intelligence. This paper presents an algorithm to determine the optimal installation placement and sizing of ESSs for a virtual multi-slack (VMS) operation based on a power sensitivity analysis in a stand-alone microgrid. Through the proposed algorithm, the optimal installation placement can be determined by a simple calculation based on a power sensitivity matrix, and the optimal sizing of the ESS for the determined placement can be obtained at the same time. The algorithm is verified through several case studies in a stand-alone microgrid based on practical power system data. The results of the proposed algorithm show that installing ESSs in the optimal placement could improve the voltage stability of the microgrid. The sizing of the newly installed ESS was also properly determined.

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