Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP)

Khabbouchi, Imed; Said, Dhaou; Oukaira, Aziz; Mellal, Idir; Khoukhi, Lyes

doi:10.3390/en16052179

Cited by 13 publications

(4 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The huge adoption of electric vehicles (EVs) and renewable energy sources (RESs), particularly wind power, is required to achieve carbon neutrality by 2050 and reduce reliance on fossil fuels. To operate, schedule, maintain, and trade energy in the modern power system, an effective and trustworthy energy management system (EMS) is necessary due to the integration of a significant amount of intermittent wind power into the grid as well as the variability of the load on the demand side [30]. Implementing a secured power grid protocol involves integrating AI systems with existing infrastructure and technologies.…”

Section: Related Workmentioning

confidence: 99%

Artificial Intelligence-Based Secured Power Grid Protocol for Smart City

Sulaiman,

Nagu,

Kaur

et al. 2023

Sensors

View full text Add to dashboard Cite

Due to the modern power system’s rapid development, more scattered smart grid components are securely linked into the power system by encircling a wide electrical power network with the underpinning communication system. By enabling a wide range of applications, such as distributed energy management, system state forecasting, and cyberattack security, these components generate vast amounts of data that automate and improve the efficiency of the smart grid. Due to traditional computer technologies’ inability to handle the massive amount of data that smart grid systems generate, AI-based alternatives have received a lot of interest. Long Short-Term Memory (LSTM) and recurrent Neural Networks (RNN) will be specifically developed in this study to address this issue by incorporating the adaptively time-developing energy system’s attributes to enhance the model of the dynamic properties of contemporary Smart Grid (SG) that are impacted by Revised Encoding Scheme (RES) or system reconfiguration to differentiate LSTM changes & real-time threats. More specifically, we provide a federated instructional strategy for consumer sharing of power data to Power Grid (PG) that is supported by edge clouds, protects consumer privacy, and is communication-efficient. They then design two optimization problems for Energy Data Owners (EDO) and energy service operations, as well as a local information assessment method in Federated Learning (FL) by taking non-independent and identically distributed (IID) effects into consideration. The test results revealed that LSTM had a longer training duration, four hidden levels, and higher training loss than other models. The provided method works incredibly well in several situations to identify FDIA. The suggested approach may successfully induce EDOs to employ high-quality local models, increase the payout of the ESP, and decrease task latencies, according to extensive simulations, which are the last points. According to the verification results, every assault sample could be effectively recognized utilizing the current detection methods and the LSTM RNN-based structure created by Smart.

show abstract

Section: Related Workmentioning

confidence: 99%

Artificial Intelligence-Based Secured Power Grid Protocol for Smart City

Sulaiman,

Nagu,

Kaur

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…This method utilizes EVs' flexible and adaptable nature and provides a pragmatic approach to stabilizing the power grid's frequency. In [50], an innovative energy management protocol (EMP) that integrates renewable energy sources and electric vehicles (EVs) into the power grid is presented. The EMP efficiently manages EV charging and discharging from a wind-powered energy storage system using advanced machine learning (ML) and game-theoretic (GT) algorithms.…”

Section: Centralized and Distributed Control Techniquesmentioning

confidence: 99%

Wind Farms and Flexible Loads Contribution in Automatic Generation Control: An Extensive Review and Simulation

Ullah

Aslam

et al. 2023

Energies

View full text Add to dashboard Cite

With the increasing integration of wind energy sources into conventional power systems, the demand for reserve power has risen due to associated forecasting errors. Consequently, developing innovative operating strategies for automatic generation control (AGC) has become crucial. These strategies ensure a real-time balance between load and generation while minimizing the reliance on operating reserves from conventional power plant units. Wind farms exhibit a strong interest in participating in AGC operations, especially when AGC is organized into different regulation areas encompassing various generation units. Further, the integration of flexible loads, such as electric vehicles and thermostatically controlled loads, is considered indispensable in modern power systems, which can have the capability to offer ancillary services to the grid through the AGC systems. This study initially presents the fundamental concepts of wind power plants and flexible load units, highlighting their significant contribution to load frequency control (LFC) as an important aspect of AGC. Subsequently, a real-time dynamic dispatch strategy for the AGC model is proposed, integrating reserve power from wind farms and flexible load units. For simulations, a future Pakistan power system model is developed using Dig SILENT Power Factory software (2020 SP3), and the obtained results are presented. The results demonstrate that wind farms and flexible loads can effectively contribute to power-balancing operations. However, given its cost-effectiveness, wind power should be operated at maximum capacity and only be utilized when there is a need to reduce power generation. Additionally, integrating reserves from these sources ensures power system security, reduces dependence on conventional sources, and enhances economic efficiency.

show abstract

“…The operational flexibility of hydroelectric stations, in tandem with the auxiliary regulation capacity of pumped-storage facilities, can effectively regulate the output from photovoltaic power stations [8]. The integrated dispatch and management of new energy grid connections can enhance the grid accommodation rate of renewable energy generation, thereby improving the safety and stability of the electrical power system [9].…”

Section: Introductionmentioning

confidence: 99%

Research on the Short-Term Economic Dispatch Method of Power System Involving a Hydropower-Photovoltaic-Pumped Storage Plant

Guo,

Liu,

et al. 2024

Electronics

View full text Add to dashboard Cite

The auxiliary regulation capacity of pumped-storage power stations can be utilized as an effective method to regulate the output of a hydro-photovoltaic complementary system, further mitigating the power fluctuations of the system and enhancing the photovoltaic absorption. This study aims to minimize power fluctuations and maximize the economic benefits of electricity generation in a hydropower-photovoltaic-pumped-storage complementary system (HPPCS), which are treated as the objective functions. It explores the participation of the HPPCS in grid active power balance auxiliary services. By modulating the participation ratio of the HPPCS in the grid’s active balance service, the system output is aligned to fluctuate proportionally with the daily load curve trend. Consequently, a short-term economic dispatch model for the integrated HPPCS is developed. The case study focuses on the considerable impact of weather conditions on photovoltaic (PV) power generation. In this model, the outputs of cascading hydro-power stations and pumped-storage power stations are considered as the decision variables. A decomposition-based multi-objective evolutionary algorithm is applied to derive an optimized intra-day dispatch Pareto solution set for the cascading HPPCS in each of these scenarios. Additionally, this study compares the Pareto solution sets for the HPPCS in various extents of its participation in grid auxiliary services. The results of the case study suggest that the system is capable of timely adjustments during the peak and trough periods of load demand. Considering the economic benefits, it enables the pumped-storage station to generate electricity for the grid during periods of high electricity prices and to store energy by pumping water when prices are low.

show abstract

Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP)

Cited by 13 publications

References 34 publications

Artificial Intelligence-Based Secured Power Grid Protocol for Smart City

Artificial Intelligence-Based Secured Power Grid Protocol for Smart City

Wind Farms and Flexible Loads Contribution in Automatic Generation Control: An Extensive Review and Simulation

Research on the Short-Term Economic Dispatch Method of Power System Involving a Hydropower-Photovoltaic-Pumped Storage Plant

Contact Info

Product

Resources

About