A step toward cleaner energy production: A water saving-based optimization approach for economic dispatch in modern power systems

Naderi, Ehsan; Azizivahed, Ali; Asrari, Arash

doi:10.1016/j.epsr.2021.107689

Cited by 23 publications

(9 citation statements)

References 38 publications

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“…At the same time, the demand for power trading and consumption by each electric power company is increasingly prominent. The selection of suitable power trading methods to meet the requirements of economic efficiency targets under current technical conditions has become a topic of discussion among scholars [10][11][12][13][14]. A novel approach to discovering an optimal multi-area dynamic economic dispatch solution integrated with wind power and pumped hydroelectric storage was proposed in [10].…”

Section: Literature Reviewmentioning

confidence: 99%

Blockchain-Based Decentralized Power Dispatching Model for Power Grids Integrated with Renewable Energy and Flexible Load

Dong

Jing-lun

et al. 2023

Processes

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To cope with the energy crisis and environmental pollution, the future development of the power system has to change towards a clean, low-carbon, flexible, and diversified direction. This paper proposes a decentralized power dispatching model based on blockchain technology to address the problems of uncertainty, privacy, security, and reliability in power dispatching systems containing renewable energy and flexible loads. Considering the uncertainty of wind, photovoltaic, and flexible load integration into the power grid, the total generation costs of the system are established, and the smart contracts of the decentralized power dispatching are proposed. The proof of work (PoW) consensus mechanism is improved in this paper. The hash operation that must be repeated in the PoW algorithm is replaced by an optimized computation process using a blockchain-based genetic algorithm (BD-GA). The proof of work-load-genetic algorithm-based (PoW-GAD) consensus algorithm is proposed. The decentralized power dispatching model and improved consensus algorithms’ effectiveness was confirmed by simulation. The power dispatching method in this paper reduces the system cost and increases wind and photovoltaic usage. The improved PoW-GAD algorithm, while inheriting the security features of the PoW algorithm, adapts to the blockchain-based decentralized dispatching structure and enhances system security.

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Section: Literature Reviewmentioning

confidence: 99%

Blockchain-Based Decentralized Power Dispatching Model for Power Grids Integrated with Renewable Energy and Flexible Load

Dong

Jing-lun

et al. 2023

Processes

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“…It examines efficiency improvements through a bi-directional DC/DC converter, contrasts various maximum power point tracking (MPPT) techniques, and reports the results of stability analysis using the Lyapunov function, discussing a variety of controllers including fuzzy, MPC, and Robust [11]. Recent studies have increasingly focused on fuzzy logic, PSO, and their combination [12][13][14]. The study explains how DERs like diesel engines, micro turbines, fuel cells, photovoltaics (PVs), and small wind turbines are utilized in microgrids.…”

Section: Introductionmentioning

confidence: 99%

Minimizing Voltage Ripple of a DC Microgrid via a Particle-Swarm-Optimization-Based Fuzzy Controller

Zolfaghari,

Karimi,

Ramezani

et al. 2024

Algorithms

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DC microgrids play a crucial role in both industrial and residential applications. This study focuses on minimizing output voltage ripple in a DC microgrid, including power supply resources, a stochastic load, a ballast load, and a stabilizer. The solar cell serves as the power supply, and the stochastic load represents customer demand, whereas the ballast load includes a load to safeguard the boost circuits against the overvoltage in no-load periods. The stabilizer integrates components such as electrical vehicle batteries for energy storage and controlling long-time ripples, supercapacitors for controlling transient ripples, and an over-voltage discharge mechanism to prevent overcharging in the storage. To optimize the charging and discharging for batteries and supercapacitors, a multi-objective cost function is defined, consisting of two parts—one for ripple minimization and the other for reducing battery usage. The battery charge and discharge are considered in the objective function to limit its usage during transient periods, providing a mechanism to rely on the supercapacitor and protect the battery. Particle swarm optimization is employed to fine-tune the fuzzy membership function. Various operational scenarios are designed to showcase the DC microgrid’s functionality under different conditions, including scenarios where production exceeds and falls below consumption. The study demonstrates the improved performance and efficiency achieved by integrating a PSO-based fuzzy controller to minimize voltage ripple in a DC microgrid and reduce battery wear. Results indicate a 42% enhancement in the integral of absolute error of battery current with our proposed PSO-based fuzzy controller compared to a conventional fuzzy controller and a 78% improvement compared to a PI controller. This translates to a respective reduction in battery activity by 42% and 78%.

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“…In recent years, there has been a proliferation of swarm-based algorithms for various situations due to the massive adoption of swarm intelligence in engineering applications [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. Authors in [ 37 ] proposed a novel meta-heuristic algorithm named Artificial Hummingbird Algorithm (AHA), influenced by the flight skills and hunting strategies of hummingbirds.…”

Section: Introductionmentioning

confidence: 99%

Egret Swarm Optimization Algorithm: An Evolutionary Computation Approach for Model Free Optimization

Chen

Francis

et al. 2022

Biomimetics

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A novel meta-heuristic algorithm named Egret Swarm Optimization Algorithm (ESOA) is proposed in this paper, which is inspired by two egret species’ hunting behavior (Great Egret and Snowy Egret). ESOA consists of three primary components: a sit-and-wait strategy, aggressive strategy as well as discriminant conditions. The learnable sit-and-wait strategy guides the egret to the most probable solution by applying a pseudo gradient estimator. The aggressive strategy uses random wandering and encirclement mechanisms to allow for optimal solution exploration. The discriminant model is utilized to balance the two strategies. The proposed approach provides a parallel framework and a strategy for parameter learning through historical information that can be adapted to most scenarios and has well stability. The performance of ESOA on 36 benchmark functions as well as 3 engineering problems are compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Harris Hawks Optimization (HHO). The result proves the superior effectiveness and robustness of ESOA. ESOA acquires the winner in all unimodal functions and reaches statistic scores all above 9.9, while the scores are better in complex functions as 10.96 and 11.92.

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A step toward cleaner energy production: A water saving-based optimization approach for economic dispatch in modern power systems

Cited by 23 publications

References 38 publications

Blockchain-Based Decentralized Power Dispatching Model for Power Grids Integrated with Renewable Energy and Flexible Load

Blockchain-Based Decentralized Power Dispatching Model for Power Grids Integrated with Renewable Energy and Flexible Load

Minimizing Voltage Ripple of a DC Microgrid via a Particle-Swarm-Optimization-Based Fuzzy Controller

Egret Swarm Optimization Algorithm: An Evolutionary Computation Approach for Model Free Optimization

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