Semi-decentralized and fully decentralized multiarea economic dispatch considering participation of local private aggregators using meta-heuristic method

Adeyanju, Olatunji Matthew; Canha, Luciane Neves; Rangel, Camilo Alberto Sepúlveda; Prado, Josue Campos do

doi:10.1016/j.ijepes.2020.106656

Cited by 12 publications

(13 citation statements)

References 60 publications

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“…In order to prevail these challenges, the researcher developed meta-heuristic algorithms such as genetic algorithm (GA), particle Swarm optimization (PSO), Whale optimization (WOA), 20 quasi-opposition-based Whale Algorithm (QOWOA), 21 Jaya optimization, 22 moth swarm algorithm and electro-search algorithm based on balloon effect. 23 Furthermore, a special emphasis is being placed on the application of various optimization approaches to help in the resolution of engineering difficulties, especially the AGC of the power system problem. This is one of the primary reasons for using the opposition-based Sea-horse optimizer (OSHO) 24 in this article to choose the optimal values for the suggested FIDN-Tilted controller (FIDN-T).…”

Section: Literature Surveymentioning

confidence: 99%

“…However, they have drawbacks such as being computationally time‐consuming, requiring so many iterations, slumping, getting keeps in local minima, and depending on their initial condition for selecting the most suitable parameters. In order to prevail these challenges, the researcher developed meta‐heuristic algorithms such as genetic algorithm (GA), particle Swarm optimization (PSO), Whale optimization (WOA), 20 quasi‐opposition‐based Whale Algorithm (QOWOA), 21 Jaya optimization, 22 moth swarm algorithm and electro‐search algorithm based on balloon effect 23 . Furthermore, a special emphasis is being placed on the application of various optimization approaches to help in the resolution of engineering difficulties, especially the AGC of the power system problem.…”

Section: Introductionmentioning

confidence: 99%

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A modified tilt controller for AGC in hybrid power system integrating forecasting of renewable energy sources

Vidyarthi,

Kumar

2023

Optim Control Appl Methods

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This article emphasizes the intermittent characteristics of renewable energy sources (RESs) and explores the role of forecasting in improving the performance of the automatic generation control (AGC) mechanism of the interconnected power system. Due to hybridization of power system basic AGC controller (PID, TID, and ID‐T) are insufficient to stabilized the system parameters. So, a new type of fractional order integral tilted derivative controller (FIDN‐T) has been proposed, which give better performance in terms of settling time, undershoot and overshoot in case of RESs with real data forecasting also. FIDN‐T has been compared with some existing controller which give the results better than basic controller. In order to optimize the different parameters of the proposed controller, a new modified Opposition‐based Sea‐horse Optimization (OSHO) algorithm has been proposed. The OSHO is compared with a few existing, well‐known meta‐heuristic algorithms to show its superiority. The analysis has been conducted under different operating conditions, including step and random disturbances as well as the IEEE‐39 bus, to verify the robustness as well as adaptability of the suggested controller. The comprehensive results of the studies provide strong evidence in support of the effectiveness and efficacy of the suggested control methods and suggest that it has the potential to be implemented in real‐world power systems for improved performance and stability.

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Section: Literature Surveymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A modified tilt controller for AGC in hybrid power system integrating forecasting of renewable energy sources

Vidyarthi,

Kumar

2023

Optim Control Appl Methods

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“…On the one hand, unlike traditional incentive models in centralized aggregators, DERs in decentralized P2P networks need to take on more functions in terms of information propagation and consensus [20], which should also be reflected. On the other hand, uncertainties in DER outputs are inevitable, so it may not be appropriate to use only this single dimension to evaluate their credits [21].…”

Section: B Related Workmentioning

confidence: 99%

Selection Game for Consensus-Based Decentralized Aggregators of Distributed Energy Resources in a Blockchain Ecosystem

Bao

et al. 2022

IEEE Access

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Aggregators can be effective in organizing distributed energy resources (DERs) for electricity markets and power systems. The recent development of blockchain and peer-to-peer (P2P) networks provides a new ecosystem for aggregating DERs. Initial studies have mainly used off-the-shelf consensuses, which may struggle to balance node sizes and computational intensities. Moreover, the dynamics of DERs changing their selection among multiple aggregators over time are rarely considered in most related literature. This freedom of selection, which is encouraged by the electricity market, can be better activated by a blockchain. In this study, a game-dynamic-based selection framework for multiple aggregators of DERs is proposed in a decentralized blockchain ecosystem. First, a proof-of-dual-credibility (Po2C) protocol is established so that DERs in such an aggregator can reach consensus. At the same time, for one DER node, both an unavoidable objective credit and a malicious subjective credit constitute its credibility with different weights. Then, a function with triple payoffs motivates DERs in terms of both the physical characteristics of being power supply devices and P2P nodes, the latter including consensus winning and data propagation. Third, the selection game of DERs among aggregators is modeled as an evolutionary game under replicator dynamics to find equilibrium. Numerical simulations with two and four aggregators show general stability in the selection game of DERs. Performance achieved with different consensuses and incentives are compared as well. The framework shows its great potential to organize DERs in a decentralized but aggregated mechanism in open electricity markets.INDEX TERMS aggregation, consensus protocol, distributed generator, equilibrium, game dynamics, peerto-peer network

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“…These methods have witnessed an enormous leap forward in terms of effectiveness while solving large-scale and highly complicated optimization problems in both engineering and economics, and RI-ELD is one of them. A considerable number of researches implemented a different meta-heuristic method to successfully solve the ELD and RI-ELD problem, such as the multi-objective multi-verse optimization (MOMVO) [6], Firework algorithm (FWA) [7], Adaptive cuckoo search algorithm (ACSA) [8], Grasshopper optimization algorithm (GOA) [9], one rank cuckoo search algorithm (ORCSA) [10], chaotic teaching-learningbased optimization with Lévy flight (CTLBO) [11], adaptive simulated annealing (ASA) [12], Modified harmony search algorithm (MHSA) [13], Whale optimization algorithm (WOA) [14], tunicate Swarm Optimizer (TSO) [15], interior search algorithm (ISA) [16], differentia evolution immunized ant colony optimization (DEIANT) [17], JAYA algorithm (YA) [18], moth-flame optimization algorithm (MFO) [19], Real-Coded Elitism Genetic Algorithm (RCEGA) [20], slime mould algorithm (SMA) [21], equilibrium optimizer (EO) [22], Turbulent Flow of Water Optimization (TFWO) [23], firefly algorithm (FA) [24], Chaotic whale optimization algorithm (CWOA) [25].…”

Section: Introductionmentioning

confidence: 99%

Optimal renewable-integrated economic load dispatch for a large-scale power system using One-to-One Optimization Algorithm

Nguyen,

Minh,

Nguyen

2024

J. ADV. ENG. COMPUT.

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This study presents the application of a new meta-heuristic algorithm called One-to-One optimization algorithm (OOBO) for solving the renewable-integrated economic load dispatch problem (RI-ELD) with consideration of both wind and solar power plants. The whole study focuses on minimizing the overall expenses of fuel (OEF) for all thermal electric power plants (TEPPs). The considered power system consists of twenty TEPPs with different working limits. OOBO is applied to solve the given problem in three cases of load demand level, including 2500, 2600, and 2700 MW. The results achieved by OOBO in the three cases are compared with other meta-heuristic algorithms called Coati optimization algorithm (COA) in the four aspects, such as Best OEF (Bst.OEF), Average OEF (Aver.OEF), Maximum OEF (Max.OEF). OOBO not only outperforms COA in all comparison aspects but also provides faster convergence speed to the optimal values of OEF at all three cases of load demand. Moreover, OOBO shows its surprising stability over COA regardless of the increase of load demand in Case 2 and Case 3. By observing these results, OOBO deserved the highly effective search tool for solving the large-scale and highly complex RI-ELD problem.

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Semi-decentralized and fully decentralized multiarea economic dispatch considering participation of local private aggregators using meta-heuristic method

Cited by 12 publications

References 60 publications

A modified tilt controller for AGC in hybrid power system integrating forecasting of renewable energy sources

A modified tilt controller for AGC in hybrid power system integrating forecasting of renewable energy sources

Selection Game for Consensus-Based Decentralized Aggregators of Distributed Energy Resources in a Blockchain Ecosystem

Optimal renewable-integrated economic load dispatch for a large-scale power system using One-to-One Optimization Algorithm

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