A new Optimal reactive power planning based on Differential Search Algorithm

Amrane, Y.; Boudour, Mohamed; Belazzoug, Messaoud

doi:10.1016/j.ijepes.2014.07.060

Cited by 33 publications

(9 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The significance of voltage stability index estimation is to ascertain the weak nodes and lines on the power system network. 22 It signifies the extreme stability index value when the index oscillates around unity. An above unity index implies the possibility of voltage collapse and consequent system failure.…”

Section: Voltage Stability Index Estimationmentioning

confidence: 99%

Real‐time multiperiod voltage control algorithm with OLTC and switched capacitors for smart distribution networks in the presence of energy storage system

Olatunde

Hassan

Abdullah

et al. 2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary Conventionally, voltage profile are regulated by controllers that are not operational flexible to the system dynamism and challenges offered by the integration of renewable energy sources. Consequently, there is a need for the adaptive coordinating mechanism as an interface between the passive network and the new active network. This will provide a platform for the smooth integration of distributed energy resources in most developing countries where traditional network is still operational. This paper proposes an algorithm for real‐time multiperiod adaptive compensation of network reactive power support based on hierarchical structure and decentralized layered multiagent system voltage coordinating scheme. A multiperiod voltage control algorithm replicates the daily load flow evaluation aiming at ameliorating voltage fluctuation over a 24‐hour simulation period. The algorithm applies the decentralized voltage control mechanism to monitor the network parameters and dynamically evaluate the capacity of the capacitor banks (CBs) to be injected for voltage compensation. This mitigates the challenges associated with under and over reactive power compensation experienced in the day‐ahead programming and manual switching operation. The algorithm works in conjunction with an on‐load tap changing transformer (OLTC) and energy storage system (ESS). The ESS complements the OLTC during switching delay, dip in its output root mean square and voltage fluctuation as network loading condition varies. The effectiveness of the proposed method is verified on standard IEEE 33 and 118‐bus distribution systems. The results show an improved voltage performance and reduction in stress/complexity associated with load and renewable generation forecast in manual switching operations.

show abstract

Section: Voltage Stability Index Estimationmentioning

confidence: 99%

Real‐time multiperiod voltage control algorithm with OLTC and switched capacitors for smart distribution networks in the presence of energy storage system

Olatunde

Hassan

Abdullah

et al. 2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…Since the generator reactive power, generator voltages, the transformer ratios and reactive power sources are continuous, the optimization problem is a nonconvex nonlinear programming problem (NLP). To solve such problem many conventional methods [3][4][5], like stochastic search methods [5][6][7][8][9][10][11] and hybrid conventional-stochastic methods [1], have been proposed.To insure the power system security, the OPRPP problem is associated with the contingency analysis problem. The contingency analysis, which is a well-known function in power system planning and operation [11][12][13][14][15], is used later to predict the contingencies which make system violated and rank the contingencies according to their relative severity.…”

mentioning

confidence: 99%

Voltage stability analysis based on multi - objective optimal reactive power dispatch under various contingency

Amrane¹,

Elmaouhab²,

Boudour³

et al. 2017

ijeei

Self Cite

View full text Add to dashboard Cite

An effective allocation of the reactive power in an electrical network aims generally to improve the voltage profile and to control transmission power losses. The present paper proposes the application of an efficient hybrid method combining two evolutionary search techniques. The technique is based on Particle Swarm Optimization (PSO) algorithm and Gravitational Search Algorithm (GSA) to solve the Optimal Reactive Power Planning (ORPP) problem for energy losses cost minimization of Algerian electric power system using the static Var Compensator devices (SVC). To ensure viability of the power system in contingency cases, various critical situations are simulated in order to prevent and prepare the power system to face such situations. The proposed program handles most changes that can occur in to the power system (heavy load, losing a large generator, losing a critical line …etc.). The proposed method is applied to solve the ORPP problem on the equivalent Algerian electric power system 114-bus. Moreover, the obtained results are compared, with PSO and GSA, separately. The results obtained by the proposed method show it's effectiveness for improving the reactive power planning problem. Index Terms: Optimal reactive power planning, Hybrid PSO-GSA, Stability Index, Equivalent Algerian electric power system. IntroductionThrough adjusting voltage generator, reactive power generator, transformer taps, and reactive power sources (capacitive or inductive banks, FACTS devices, etc.), the reactive power planning can reduce voltage deviations and active power losses. And in the same time maximizing voltage stability margin [1][2]. Since the generator reactive power, generator voltages, the transformer ratios and reactive power sources are continuous, the optimization problem is a nonconvex nonlinear programming problem (NLP). To solve such problem many conventional methods [3][4][5], like stochastic search methods [5][6][7][8][9][10][11] and hybrid conventional-stochastic methods [1], have been proposed.To insure the power system security, the OPRPP problem is associated with the contingency analysis problem. The contingency analysis, which is a well-known function in power system planning and operation [11][12][13][14][15], is used later to predict the contingencies which make system violated and rank the contingencies according to their relative severity. An outage of a transmission line, capacitor bank or transformer may lead to over loads in other branches and sudden system voltage rise or drop. This may lead to complete blackout. In this paper, three critical contingency cases are studied, these are: 1) Heavy load, 2) Lose a large Generator, 3) Lose a critical line. These cases are studied in a way to guarantee: i) The system stability after the increase of the power system load (voltage level, active and reactive power and load tap changer value are in the secure range), ii) The stability system maintainability after the outage of a large generator and a critical line, iii) a better location choice of the S...

show abstract

“…Its advantages consists in i) ability to search for solutions of multimodal functions; ii) has only two control parameters; iii) is easy to program [4]. The research reported in literature related to this algorithm indicates that it is robust and flexible and can generate high quality solutions within short calculation time [5].…”

Section: Introductionmentioning

confidence: 99%

Random Number Generator Influence on Differential Search Performance

Alhalabi¹,

Alsaadi²,

Drăgoi³

2016

Modelling, Simulation and Identification / 841: Intelligent Systems and Control

View full text Add to dashboard Cite

Differential Search is an optimization approach that simulates the Brownian like random walk movement of migration organisms. Its inner workings relay on Random Number Generators (RNG) to emulate the probability of the natural driven process and therefore, the properties and performance of the RNG used has an influence on the overall algorithm performance. This study focuses on assessing this influence and on the manner in which the best suited RNG must be selected in order to achieve the optimal results for different types of problems. The results showed that depending on the properties of the problem, different RNGs provide the best solutions. However, as the number of function evaluation rises in report to the problem dimensionality, the influence on the RNG becomes smaller.

show abstract

A new Optimal reactive power planning based on Differential Search Algorithm

Cited by 33 publications

References 21 publications

Real‐time multiperiod voltage control algorithm with OLTC and switched capacitors for smart distribution networks in the presence of energy storage system

Real‐time multiperiod voltage control algorithm with OLTC and switched capacitors for smart distribution networks in the presence of energy storage system

Voltage stability analysis based on multi - objective optimal reactive power dispatch under various contingency

Random Number Generator Influence on Differential Search Performance

Contact Info

Product

Resources

About