Energy and spinning reserve scheduling for a wind-thermal power system using CMA-ES with mean learning technique

Reddy, S. Surender; Panigrahi, Bijaya Ketan; Kundu, Rupam; Mukherjee, Rajarshi; Debchoudhury, Shantanab

doi:10.1016/j.ijepes.2013.03.032

Cited by 73 publications

(52 citation statements)

References 25 publications

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“…[24]. Nowadays, CMA-ES is becoming very popular for solving nonconvex/non-smooth optimization problems in various engineering applications due to its self learning behavior [26][27][28][29][30][31][32]. CMA-ES is a class of continuous evolutionary algorithm, which generates new population members by sampling from a probability distribution that is constructed during the optimization process [26].…”

Section: Robust Controlmentioning

confidence: 99%

“…Recently, in EC literature, it is reported that CMA-ES has better efficiency in solving different kind of engineering problems due to its self learning behavior as compared to other ECs [28][29][30][31][32][33][34]. The CMA-ES based fixed structure H ∞ loop shaping controller is compared with the traditional H ∞ loop shaping controller, non-smooth optimization and HKA based fixed structure H ∞ loop shaping controllers.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Covariance matrix adaptation evolution strategy based design of fixed structure robust H∞ loop shaping controller

Kadhar¹,

Baskar²

2015

Applied Soft Computing

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Section: Robust Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Covariance matrix adaptation evolution strategy based design of fixed structure robust H∞ loop shaping controller

Kadhar¹,

Baskar²

2015

Applied Soft Computing

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“…The use of renewable energy such as wind power and hydropower can reduce greenhouse gas emissions from fossil fuels. Wind power is one of the fastest-growing sources, however it is uncertain and cannot be scheduled due to its intrinsic dependence on varying weather conditions over many years [2,3]. Solar power is less uncertain, but has higher variability compared to wind power [4].…”

Section: Introductionmentioning

confidence: 99%

A Gradient-Based Cuckoo Search Algorithm for a Reservoir-Generation Scheduling Problem

Yang

Zhou

et al. 2018

Algorithms

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Abstract:In this paper, a gradient-based cuckoo search algorithm (GCS) is proposed to solve a reservoir-scheduling problem. The classical cuckoo search (CS) is first improved by a self-adaptive solution-generation technique, together with a differential strategy for Lévy flight. This improved CS is then employed to solve the reservoir-scheduling problem, and a two-way solution-correction strategy is introduced to handle variants' constraints. Moreover, a gradient-based search strategy is developed to improve the search speed and accuracy. Finally, the proposed GCS is used to obtain optimal schemes for cascade reservoirs in the Jinsha River, China. Results show that the mean and standard deviation of power generation obtained by GCS are much better than other methods. The converging speed of GCS is also faster. In the optimal results, the fluctuation of the water level obtained by GCS is small, indicating the proposed GCS's effectiveness in dealing with reservoir-scheduling problems.

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“…RES involves efficiency and economical issues. Among reported solutions, ensuring spinning reserve [9][10][11][12] and suitable storage unit facilities [13][14][15][16] have been considered as the most effective ones.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Autonomous Hybrid Renewable Power Generation

Kumar

Palwalia

2015

Journal of Renewable Energy

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Power extension of grid to isolated regions is associated with technical and economical issues. It has encouraged exploration and exploitation of decentralized power generation using renewable energy sources (RES). RES based power generation involves uncertain availability of power source round the clock. This problem has been overcome to certain extent by installing appropriate integrated energy storage unit (ESU). This paper presents technical review of hybrid wind and photovoltaic (PV) generation in standalone mode. Associated components like converters, storage unit, controllers, and optimization techniques affect overall generation. Wind and PV energy are readily available, omnipresent, and expected to contribute major future energy market. It can serve to overcome global warming problem arising due to emissions in fossil fuel based thermal generation units. This paper includes the study of progressive development of standalone renewable generation units based on wind and PV microgrids.

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Energy and spinning reserve scheduling for a wind-thermal power system using CMA-ES with mean learning technique

Cited by 73 publications

References 25 publications

Covariance matrix adaptation evolution strategy based design of fixed structure robust H∞ loop shaping controller

Covariance matrix adaptation evolution strategy based design of fixed structure robust H∞ loop shaping controller

A Gradient-Based Cuckoo Search Algorithm for a Reservoir-Generation Scheduling Problem

Decentralized Autonomous Hybrid Renewable Power Generation

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