Frequency regulation and congestion management by Virtual Storage Plants

Xiao, Wang; Zhao, Tianqiao; Parisio, Alessandra

doi:10.1016/j.segan.2021.100586

Cited by 19 publications

(5 citation statements)

References 30 publications

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“…Wang et al in their research introduced the effective management of the storage devices in muti-area power system context to manage the congestion and frequency through a virtual storage plant. In their research a distributed optimization approach has been adopted for the coordination of the virtual storage plants and mitigating congestion in the tie line power flow while providing frequency support [9]. Zhou et al proposed a CM strategy that consider the determination of the congestion cost sharing in the electricity market, and the other is the procuring of the services in the ancillary service market that aim towards the congestion cost minimization.…”

Section: A Literature Surveymentioning

confidence: 99%

A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network

Paul¹,

Sinha

Bouteraa

et al. 2023

IEEE Access

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This research manuscript proposes an Improved Manta Ray Foraging Optimization (IMRFO) algorithm for the power system congestion cost problem. The goal of the proposed Congestion Management (CM) strategy is twofold: firstly, the Generator Sensitivity Factors (GSF) is determined to select and involve the most influential power system generators that will reschedule their real power to alleviate the excess power flow in congested transmission lines. Secondly, the IMRFO has been developed and applied to attain the minimum possible congestion cost. The IMRFO has been formulated with the inclusion of correction factors in the exploration and exploitation phases to improve the coordination between these phases. The effectiveness of IMRFO has been measured considering its effective performance on the 23 conventional benchmark functions. 39 bus New England and IEEE-118 bus test system has been utilized to authenticate the effectiveness of the CM approach with the application of IMRFO. The outcomes highlight that the congestion cost achieved with IMRFO has been reduced by, of 16.08%, 13.73%, 11.78%, and 4.48 % for the 39-bus system and 14.84%, 12.97%, 9.63%, and 6.85% for 118 bus system when compared to the Bacteria Forge Optimization (BFO), Grey Wolf Optimization (GWO), Sine-Cosine Algorithm (SCA), and Original MRFO. The results gained with the implementation of IMRFO on the CM problem portrays appreciable minimization in the congestion cost, enhancement in the system voltage and losses, generates better convergence profile and computational time when contrasted with the recent optimization methods.INDEX TERMS Manta ray forge optimization, meta-heuristic technique, optimal power flow, optimization, power rescheduling, sensitivity analysis.

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Section: A Literature Surveymentioning

confidence: 99%

A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network

Paul¹,

Sinha

Bouteraa

et al. 2023

IEEE Access

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“…In this section, we propose a bilevel model (Wang et al, 2022), which can maximize WPP's profits, reduce prosumers' costs, and provide WPP with a reasonable trading strategy.…”

Section: Design Goals Of the Bilevel Problemmentioning

confidence: 99%

Blockchain Based Peer-To-Peer Energy Trading Between Wind Power Producer and Prosumers in Short-Term Market

Liu

Huang

et al. 2022

Front. Energy Res.

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With the increase of wind power penetration, the deviation caused by its volatility and intermittency poses a growing threat to the grid. Energy trading in short-term markets for wind power and backup storage helps compensate for the deviations. Furthermore, the introduction of peer-to-peer (P2P) energy trading can effectively reduce the risk of centralized market management. However, the higher cost of energy storage are not conducive to wind power producers (WPPs). And P2P trading also suffers from trust and efficiency problems. This paper provides a blockchain based short-term energy trading market, which resolves generation deviations through efficient and trusted real-time transactions between WPP and prosumers. The blockchain-based energy trading market is a trustless P2P structure, and the trading is triggered by smart contracts to ensure efficiency. Furthermore, a reputation mechanism is designed to incentivize WPP’s generation forecasts to be accurate and prosumers to participate in the market. A bilevel optimization method is designed to increase the revenue of WPP and reduce the costs of prosumers. The market can effectively balance the deviation of wind power generation, increase the revenue of WPP by 9.55%, and reduce the costs for consumers by 5.6%.

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“…RBFNN as a feedforward network can approximate analytic nonlinear relations with arbitrary accuracy (Wang et al, 2022;Yang et al, 2020). It is a powerful tool to deal with complex nonlinear, uncertain, and coupling problems in MIMO systems.…”

Section: Inverse System Design and Decoupling Of Radial Basis Functio...mentioning

confidence: 99%

Intelligent Decoupling Control Study of PMSM Based on the Neural Network Inverse System

Gong

Zhi-Qiang²,

Wang³

et al. 2022

Front. Energy Res.

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This study obtains the analytical inverse system of a permanent magnet synchronous motor (PMSM) model based on the traditional magnetic field orientation decoupling control mode by analyzing the inverse quality of the PMSM. Using the neural network’s excellent approximation ability and well learning functions, a neural network inverse system (NNIS) of the decoupling control system was established by identifying and offline training the back propagation neural network (BPNN) and radial basis function neural network (RBFNN). The data collected from the analytical inverse system of the PMSM model are used to analyze and compare the prediction accuracy and running time of the neural network, so as to optimize the structure and parameters of the neural network. The simulation results of three PMSM decoupling control systems show that the PMSM decoupling control system based on RBF NNIS has good dynamic and static decoupling performance, and robustness.

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Frequency regulation and congestion management by Virtual Storage Plants

Cited by 19 publications

References 30 publications

A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network

A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network

Blockchain Based Peer-To-Peer Energy Trading Between Wind Power Producer and Prosumers in Short-Term Market

Intelligent Decoupling Control Study of PMSM Based on the Neural Network Inverse System

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