scholarly journals Secondary and Tertiary Voltage Control of a Multi-Region Power System

Electricity ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 37-59
Author(s):  
Omar H. Abdalla ◽  
Hady H. Fayek ◽  
Abdel Ghany M. Abdel Ghany
Keyword(s):  
Genetic Algorithm ◽  
Power System ◽  
Voltage Control ◽  
Active Power ◽  
Pid Controllers ◽  
Power Losses ◽  
Secondary Voltage ◽  
Pmu Placement ◽  
Active Power Losses ◽  
System Partitioning

This paper presents techniques for the application of tertiary and secondary voltage control through the use of intelligent proportional integral derivative (PID) controllers and the wide area measurement system (WAMS) in the IEEE 39 bus system (New England system). The paper includes power system partitioning, pilot bus selection, phasor measurement unit (PMU) placement, and optimal secondary voltage control parameter calculations to enable the application of the proposed voltage control. The power system simulation and analyses were performed using the DIgSILENT and MATLAB software applications. The optimal PMU placement was performed in order to apply secondary voltage control. The tertiary voltage control was performed through an optimal power flow optimization process in order to minimize the active power losses. Two different methods were used to design the PID secondary voltage control, namely, genetic algorithm (GA) and neural network based on genetic algorithm (NNGA). A comparison of system performances using these two methods under different operating conditions is presented. The results show that NNGA secondary PID controllers are more robust than GA ones. The paper also presents a comparison between system performance with and without secondary voltage control, in terms of voltage deviation index and total active power losses. The graph theory is used in system partitioning, and sensitivity analysis is used in pilot bus selection, the results of which proved their effectiveness.

Transmission Network Expansion Planning Considering Optimal Allocation of Series Capacitive Compensation and Active Power Losses

2021 ◽  
Vol 12 (1) ◽  
pp. 388
Author(s):  
Dany H. Huanca ◽  
Luis A. Gallego ◽  
Jesús M. López-Lezama
Keyword(s):  
Genetic Algorithm ◽  
Test System ◽  
Active Power ◽  
Mixed Integer ◽  
Planning Problem ◽  
Transmission Network ◽  
Power Losses ◽  
Network Expansion ◽  
Expansion Planning ◽  
Active Power Losses

This paper presents a modeling and solution approach to the static and multistage transmission network expansion planning problem considering series capacitive compensation and active power losses. The transmission network expansion planning is formulated as a mixed integer nonlinear programming problem and solved through a highly efficient genetic algorithm. Furthermore, the Villasana Garver’s constructive heuristic algorithm is implemented to render the configurations of the genetic algorithm feasible. The installation of series capacitive compensation devices is carried out with the aim of modifying the reactance of the original circuit. The linearization of active power losses is done through piecewise linear functions. The proposed model was implemented in C++ language programming. To show the applicability and effectiveness of the proposed methodology several tests are performed on the 6-bus Garver system, the IEEE 24-bus test system, and the South Brazilian 46-bus test system, presenting costs reductions in their multi-stage expansion planning of 7.4%, 4.65% and 1.74%, respectively.

scholarly journals Multi-objective optimal placement of distributed generations for dynamic loads

2019 ◽  
Vol 9 (4) ◽  
pp. 2303
Author(s):  
Shah Mohazzem Hossain ◽  
Abdul Hasib Chowdhury
Keyword(s):  
Power System ◽  
Active Power ◽  
Optimal Placement ◽  
Voltage Profile ◽  
Power Losses ◽  
Long Distance ◽  
Utilization Factor ◽  
Distributed Generations ◽  
Multi Objective ◽  
Active Power Losses

<span lang="EN-US">Large amount of active power losses and low voltage profile are the two major issues concerning the integration of distributed generations with existing power system networks. High </span><em><span lang="EN-US">R</span></em><span lang="EN-US">/</span><em><span lang="EN-US">X</span></em><span lang="EN-US"> ratio and long distance of radial network further aggravates the issues. Optimal placement of distributed generators can address these issues significantly by alleviating active power losses and ameliorating voltage profile in a cost effective manner. In this research, multi-objective optimal placement problem is decomposed into minimization of total active power losses, maximization of bus voltage profile enhancement and minimization of total generation cost of a power system network for static and dynamic load characteristics. Optimum utilization factor for installed generators and available loads is scaled by the analysis of yearly load-demand curve of a network. The developed algorithm of N-bus system is implemented in IEEE-14 bus standard test system to demonstrate the efficacy of the proposed method in different loading conditions.</span>

scholarly journals An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Neda Hantash ◽  
Tamer Khatib ◽  
Maher Khammash
Keyword(s):  
Power System ◽  
Electrical Power ◽  
Pso Algorithm ◽  
Active Power ◽  
Power Losses ◽  
Electrical Power System ◽  
Swarm Optimization ◽  
Inertia Weight ◽  
Elapsed Time ◽  
Active Power Losses

In this paper, an improved particle swarm optimization method (PSO) is proposed to optimally size and place a DG unit in an electrical power system so as to improve voltage profile and reduce active power losses in the system. An IEEE 34 distribution bus system is used as a case study for this research. A new equation of weight inertia is proposed so as to improve the performance of the PSO conventional algorithm. This development is done by controlling the inertia weight which affects the updating velocity of particles in the algorithm. Matlab codes are developed for the adapted electrical power system and the improved PSO algorithm. Results show that the proposed PSO algorithm successfully finds the optimal size and location of the desired DG unit with a capacity of 1.6722 MW at bus number 10. This makes the voltage magnitude of the selected bus equal to 1.0055 pu and improves the status of the electrical power system in general. The minimum value of fitness losses using the applied algorithm is found to be 0.0.0406 while the average elapsed time is 62.2325 s. In addition to that, the proposed PSO algorithm reduces the active power losses by 31.6%. This means that the average elapsed time is reduced by 21% by using the proposed PSO algorithm as compared to the conventional PSO algorithm that is based on the liner inertia weight equation.

scholarly journals Simulation of a Power System Considering Active Power Losses and Seasons

2021 ◽  
Vol 18 (1) ◽  
pp. 1-7
Author(s):  
Lucian-Ioan Dulău ◽  
Dorin Bică
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Distributed Generation ◽  
Active Power ◽  
Power Lines ◽  
Power Losses ◽  
Active Power Losses ◽  
Autumn And Winter ◽  
And Storage ◽  
Storage Units

Abstract In this paper is presented the simulation of a power system. The simulations performed are considering the seasons (spring, summer, autumn and winter). The system has 39 buses, 46 power lines, 13 generating units, 19 loads and 2 storage units. Of the 13 generating units, 3 are distributed generation sources based on renewable energy. There are also 2 battery storage units. The simulation considers the active power supplied by the generating and storage units, respectively the active power losses. The results give the power supplied by each generating unit for each season.

REDUCTION OF ACTIVE POWER LOSSES IN LOW VOLTAGE NETWORKS WITH THE RECTIFIER LOAD

2017 ◽  
Vol 2017 (3) ◽  
pp. 65-70
Author(s):  
A.F. Zharkin ◽  
◽  
V.A. Novskyi ◽  
N.N. Kaplychnyi ◽  
A.V. Kozlov ◽  
...  
Keyword(s):  
Low Voltage ◽  
Active Power ◽  
Power Losses ◽  
Active Power Losses

CALCULATION OF ACTIVE POWER LOSSES IN THE GROUNDING WIRE OF OVERHEAD POWER LINES

2016 ◽  
Vol 2016 (4) ◽  
pp. 23-25
Author(s):  
A.V. Krasnozhon ◽  
◽  
R.O. Buinyi ◽  
I.V. Pentegov ◽  
◽  
...  
Keyword(s):  
Active Power ◽  
Power Lines ◽  
Power Losses ◽  
Active Power Losses ◽  
Overhead Power Lines
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