Virtual Power Plants Optimization Issue: A Comprehensive Review on Methods, Solutions, and Prospects

Nafkha-Tayari, Wafa; Elghali, Seifeddine Ben; Heydarian‐Forushani, Ehsan; Benbouzid, Mohamed

doi:10.3390/en15103607

Cited by 22 publications

(4 citation statements)

References 113 publications

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“…On the other hand, in a decentralized system, each DER is equipped with a controller that makes decisions independently after receiving data shared by the other resources. It is undeniable that centralized architectures are capable of achieving greater performances [53]; however, they also present scalability issues, limiting the VPP size to a few hundreds of units [54]. Moreover, the protocols and reliability of the communication channels required to transfer all the information to the centralized unit remain critical aspects [55], as the bandwidth of the communication channel, which can range from tens to hundreds of kB/s, and rapidly grows when new DERs, are connected [56].…”

Section: Control Coordination and Planning Strategies For Aggregators...mentioning

confidence: 99%

Opening of Ancillary Service Markets to Distributed Energy Resources: A Review

et al. 2023

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Electric power systems are moving toward more decentralized models, where energy generation is performed by small and distributed power plants, often from renewables. With the gradual phase out from fossil fuels, however, Distribution Energy Resources (DERs) are expected to take over in the provision of all regulation services required to operate the grid. To this purpose, the opening of national Ancillary Service Markets (ASMs) to DERs is considered an essential passage. In order to allow this transition to happen, current opportunities and barriers to market participation of DERs must be clearly identified. In this work, a comprehensive review is provided of the state-of-the-art of research on DER integration into ASMs. The topic at hand is analyzed from different perspectives. First, the current situation and main trends regarding the reformation processes of national ASMs are analyzed to get a clear picture of the evolutions expected and adjustment required in the future, according to the scientific community. Then, the focus is moved to the strategies to be adopted by aggregators for the effective control and coordination of DERs, exploring the challenges posed by the uncertainties affecting the problem. Coordination schemes between transmission and distribution system operators, and the implications on the grid infrastructure operation and planning, are also investigated. Finally, the review deepens the control capabilities required for DER technologies to perform the needed control actions.

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Section: Control Coordination and Planning Strategies For Aggregators...mentioning

confidence: 99%

Opening of Ancillary Service Markets to Distributed Energy Resources: A Review

et al. 2023

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“…Novel technologies such as the distributed energy resources (DERs) also provide many possibilities for smart grids that allow power generation at a local level instead of relying on large and centralized power plants [59,60]. This is an important change that can result in improved environmental performance and increased efficiency from renewable energy sources.…”

Section: Traditional Power Grids and Smart Gridsmentioning

confidence: 99%

Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review

et al. 2023

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The use of machine learning and data-driven methods for predictive analysis of power systems offers the potential to accurately predict and manage the behavior of these systems by utilizing large volumes of data generated from various sources. These methods have gained significant attention in recent years due to their ability to handle large amounts of data and to make accurate predictions. The importance of these methods gained particular momentum with the recent transformation that the traditional power system underwent as they are morphing into the smart power grids of the future. The transition towards the smart grids that embed the high-renewables electricity systems is challenging, as the generation of electricity from renewable sources is intermittent and fluctuates with weather conditions. This transition is facilitated by the Internet of Energy (IoE) that refers to the integration of advanced digital technologies such as the Internet of Things (IoT), blockchain, and artificial intelligence (AI) into the electricity systems. It has been further enhanced by the digitalization caused by the COVID-19 pandemic that also affected the energy and power sector. Our review paper explores the prospects and challenges of using machine learning and data-driven methods in power systems and provides an overview of the ways in which the predictive analysis for constructing these systems can be applied in order to make them more efficient. The paper begins with the description of the power system and the role of the predictive analysis in power system operations. Next, the paper discusses the use of machine learning and data-driven methods for predictive analysis in power systems, including their benefits and limitations. In addition, the paper reviews the existing literature on this topic and highlights the various methods that have been used for predictive analysis of power systems. Furthermore, it identifies the challenges and opportunities associated with using these methods in power systems. The challenges of using these methods, such as data quality and availability, are also discussed. Finally, the review concludes with a discussion of recommendations for further research on the application of machine learning and data-driven methods for the predictive analysis in the future smart grid-driven power systems powered by the IoE.

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“…However, the use of large-scale new energy has greatly affected the safe and stable operation of the power system. Virtual power plants (VPPS) are based on a new type of coordinated control and energy management technology that brings together distributed energy sources (DER), energy storage systems (ESS), and controlled loads (CL) to participate in a variety of markets [1].Literature [2] proposes a coordinated control strategy for a VPP contribution to load frequency control. The considered VPP comprises distributed Battery Energy Storage Systems and Heat Pump Water Heaters [3][4].A technology VPP operation model has been developed to optimize the scheduling of various distributed energy sources operating in the day-ahead energy market [5].Literature [6] focuses on the development and scope of VPP as a strategy to promote the integration of DER in power systems.…”

Section: Introductionmentioning

confidence: 99%

A novel random optimal scheduling of virtual power plant with multiple wind farms

Zhang,

Cui,

Shi

et al. 2024

Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023)

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With the improvement of the reliability and security requirements of the power grid, more and more distributed power sources are integrated into the power grid. There is a huge impact on the power grid to the output of distributed power sources .This paper proposed a random optimal scheduling mechanism for virtual power plants with multiple wind fields. Firstly, the optimal scheduling model of virtual power plant is proposed based on the maximum expected value of virtual power plant economic benefits. Secondly, in order to improve the efficiency of the virtual power plant stochastic optimal scheduling model, a particle swarm optimization algorithm based on ELM was proposed. Thirdly, a population evolution mechanism based on ELM is formed, which greatly improves the global convergence of the algorithm. Finally, the improved particle swarm optimization algorithm based on EIM is proved to have faster convergence speed and better global convergence than standard particle swarm optimization algorithm.

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Virtual Power Plants Optimization Issue: A Comprehensive Review on Methods, Solutions, and Prospects

Cited by 22 publications

References 113 publications

Opening of Ancillary Service Markets to Distributed Energy Resources: A Review

Opening of Ancillary Service Markets to Distributed Energy Resources: A Review

Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review

A novel random optimal scheduling of virtual power plant with multiple wind farms

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