Two evolutionary computational approaches for active power losses minimization in Smart Grids

Purpose In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single objective is insufficient to achieve better operation performance of power systems. Multi-objective ORPD (MOORPD) aims to minimize simultaneously either the active power losses and voltage stability index, or the active power losses and the voltage deviation. The purpose of this paper is to propose multi-objective ant lion optimization (MOALO) algorithm to solve multi-objective ORPD problem considering large-scale power system in an effort to achieve a good performance with stable and secure operation of electric power systems. Design/methodology/approach A MOALO algorithm is presented and applied to solve the MOORPD problem. Fuzzy set theory was implemented to identify the best compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were fully verified and discussed. Findings Three test systems – the IEEE 30-bus, IEEE 57-bus and large-scale IEEE 300-bus – were used to examine the efficiency of the proposed algorithm. The findings obtained amply confirmed the superiority of the proposed approach over the multi-objective enhanced PSO and basic version of MOPSO. In addition to that, the algorithm is benefitted from good distributions of the non-dominated solutions and also guarantees the feasibility of solutions. Originality/value The proposed algorithm is applied to solve three versions of ORPD problem, active power losses, voltage deviation and voltage stability index, considering large -scale power system IEEE 300 bus.

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COMPARATIVE ANALYSIS OF ACTIVE POWER LOSSES OF INDUCTION MOTORS WITH CYLINDRICAL AND AXIAL AIR GAPS

Electrical Engineering & Electromechanics ◽

10.20998/2074-272x.2015.5.04 ◽

2015 ◽

Vol 0 (5) ◽

pp. 31-35

Author(s):

A. A. Stavinskii ◽

O. O. Palchykov

Keyword(s):

Comparative Analysis ◽

Induction Motors ◽

Active Power ◽

Power Losses ◽

Air Gaps ◽

Active Power Losses

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Optimal Network Reconfiguration in Presence of Renewable Distributed Generation Using Evolutionary Algorithm

Pakistan Journal of Engineering and Technology ◽

10.51846/vol4iss2pp38-43 ◽

2021 ◽

Vol 4 (2) ◽

pp. 38-43

Author(s):

Linta Khalil ◽

Mughees Riaz ◽

M.Arslan Iqbal Awan ◽

M.Kamran Liaquat Bhatti ◽

Rabbia Siddique ◽

...

Keyword(s):

Renewable Energy ◽

Energy Systems ◽

Active Power ◽

Optimal Size ◽

Network Reconfiguration ◽

Power Losses ◽

Gas Emissions ◽

Renewable Energy Systems ◽

Optimal Network ◽

Active Power Losses

Utilization of new technologies and people lifestyle has greatly affected the world’s electricity market. This demands to design innovative renewable energy systems for efficient use of green energy. In terms of greenhouse gas emissions, electricity from traditional energy supplies has become particularly harmful for the world. To decrease the reliance on fossil fuels, it is need of time to enhance the renewable energy integration in the conventional energy systems. Renewable DGs integration in existing energy systems is not a simple task. To overcome challenges caused by enhanced penetration of renewable energy systems in existing networks, adaptation of smart techniques is essential. DGs Optimal size and selection of their suitable location for integration is crucial for cost effective power delivery to the consumers without compromising the quality of power. This paper presents impartial performance management by optimal network reconfiguration in parallel with renewable DGs and selecting suitable size for reducing active power losses, pollutant gas emissions and costs of annual operation. For analysis of active power losses, Fuzzy and SPEA2 based algorithms are used in MATLAB with IEEE BUS14 acting as load bus. While the cost of power generation and pollutant gases emissions are estimated using HOMER Pro software.

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

Applied Sciences ◽

10.3390/app12010388 ◽

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.

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