Maximization of Reactive Power Reserve in wind integrated power system using CHIO approach

Rani, Nibha; Malakar, Tanmoy

doi:10.1016/j.ifacol.2022.04.025

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…Inspired by the novel coronavirus that is widespread around the world, the algorithm proposes an algorithm update theory that simulates the emergence of herd immunity. Although the algorithm appeared late, it has been verified on multiple functions and engineering optimization problems [19][20][21]. The CHIO algorithm proposed the concept of multi-population evolution for the first time.…”

Section: Introductionmentioning

confidence: 99%

An Efficient and Improved Coronavirus Herd Immunity Algorithm Using Knowledge-Driven Variable Neighborhood Search for Flexible Job-Shop Scheduling Problems

Jiao

et al. 2023

Processes

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By addressing the flexible job shop scheduling problem (FJSP), this paper proposes a new type of algorithm for the FJSP. We named it the hybrid coronavirus population immunity optimization algorithm. Based on the characteristics of the problem, firstly, this paper redefined the discretized two-stage individual encoding and decoding scheme. Secondly, in order to realize the multi-scale search of the solution space, a multi-population update mechanism is designed, and a collaborative learning method is proposed to ensure the diversity of the population. Then, an adaptive mutation operation is introduced to enrich the diversity of the population, relying on the adaptive adjustment of the mutation operator to balance global search and local search capabilities. In order to realize a directional and efficient neighborhood search, this algorithm proposed a knowledge-driven variable neighborhood search strategy. Finally, the algorithm’s performance comparison experiment is carried out. The minimum makespans on the MK06 medium-scale case and MK10 large-scale case are 58 and 201, respectively. The experimental results verify the effectiveness of the hybrid algorithm.

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Section: Introductionmentioning

confidence: 99%

An Efficient and Improved Coronavirus Herd Immunity Algorithm Using Knowledge-Driven Variable Neighborhood Search for Flexible Job-Shop Scheduling Problems

Jiao

et al. 2023

Processes

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“…Similarly, a new optimization technique using the behavior of the coronavirus for optimum reactive power integration and reserve [29]. The results from the simulation proved to be efficient when compared with other methods.…”

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confidence: 96%

Analysis of a new voltage stability pointer for line contingency ranking in a power network

et al. 2022

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Improper management of reactive power in a power network could lead to voltage instability. This paper presents a well-detailed study on voltage instability due to violation of power equilibrium in a power network and introduces a new voltage stability pointer (NVSP). The proposed NVSP is developed from a reduced 2-bus interconnected network to predict the sensistivity of voltage stability to reactive power variation. The simulation results from MATLAB were evaluated on IEEE 14-bus test system. The contingency ranking was achieved by varying the reactive power on the load buses to its maximum loading limit. The maximum reactive power point was taken at each load bus and the critical lines were ranked according to their vulnerability to voltage collapse. The results were compared with other notable voltage stability indices. The results prove that the NVSP is an essential tool in predicting voltage collapse.

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Stochastic Maximization of Reactive Power Reserve in Power Systems with Uncertain Practical Demand and Wind Power Using CHIO Approach

Rani,

Malakar

2024

2024 IEEE 4th International Conference on Sustainable Energy and Future Electric Transportation (SEFET)

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Maximization of Reactive Power Reserve in wind integrated power system using CHIO approach

Cited by 3 publications

References 21 publications

An Efficient and Improved Coronavirus Herd Immunity Algorithm Using Knowledge-Driven Variable Neighborhood Search for Flexible Job-Shop Scheduling Problems

An Efficient and Improved Coronavirus Herd Immunity Algorithm Using Knowledge-Driven Variable Neighborhood Search for Flexible Job-Shop Scheduling Problems

Analysis of a new voltage stability pointer for line contingency ranking in a power network

Stochastic Maximization of Reactive Power Reserve in Power Systems with Uncertain Practical Demand and Wind Power Using CHIO Approach

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