Special Issue "Progress in Virtual Power Plant Design and Applications"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy".

Deadline for manuscript submissions: closed (31 December 2018).

Special Issue Editors

Dr. Stefano Rinaldi
Website
Guest Editor
University of Brescia, Department of Information Engineering (DII)
Interests: instrumentation and measurement; industrial real-time network; wireless sensor network; smart sensors; communication systems for smart grids; time synchronization; Linux-embedded programming; embedded systems; power quality; smart grids; energy systems; smart building; energy management system
Special Issues and Collections in MDPI journals
Dr. Marco Pasetti
Website
Guest Editor
Department of Information Engineering, University of Brescia, Via Branze, 38, 25123 Brescia, Italy
Interests: energy systems; distributed generation; renewable energy sources; solar engineering; photovoltaics; energy storage; energy management systems; supervisory control systems; energy policies; smart grids and microgrids
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The progressive paradigm shift from the centralized generation based on fossil fuels to the Distributed Generation (DG) based on Renewable Energy Sources (RESs) is posing relevant challenges to all energy stakeholders, particularly concerning the unreliability and scarce flexibility of heterogeneous systems made up of several—and typically intermittent—Distributed Energy Resources (DERs). To overcome these drawbacks, different technologies and strategies have been proposed and are going to be adopted at distinct stages of the energy supply-chain, from energy balancing assets (such as distributed energy storage and controllable loads), to advanced ancillary services and active demand-side schemes. The successful implementation of such measures would however require their proper integration and harmonization at various aggregation levels, from end-users to the grid management and control. The aim of this Special Issue is to assess how the recent advances in the design and implementation of the Virtual Power Plant (VPP) concept would help to face this challenge, by allowing improved observability, reliability and enhanced control capabilities. This Special Issue welcomes theoretical papers, methodological studies and empirical research (or combination thereof) on the design and implementation of the VPP concept, concerning (but not limited to) the application of: Active demand-side response, energy management, control and optimization, improved flexibility, reliability, and cyber-security, including the related key enabling information and communication technologies.

Dr. Stefano Rinaldi
Dr. Marco Pasetti
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

The progressive paradigm shift from the centralized generation based on fossil fuels to the Distributed Generation (DG) based on Renewable Energy Sources (RESs) is posing relevant challenges to all energy stakeholders, particularly concerning the unreliability and scarce flexibility of heterogeneous systems made up of several—and typically intermittent—Distributed Energy Resources (DERs). To overcome these drawbacks, different technologies and strategies have been proposed and are going to be adopted at distinct stages of the energy supply-chain, from energy balancing assets (such as distributed energy storage and controllable loads), to advanced ancillary services and active demand-side schemes. The successful implementation of such measures would however require their proper integration and harmonization at various aggregation levels, from end-users to the grid management and control. The aim of this Special Issue is to assess how the recent advances in the design and implementation of the Virtual Power Plant (VPP) concept would help to face this challenge, by allowing improved observability, reliability and enhanced control capabilities. This Special Issue welcomes theoretical papers, methodological studies and empirical research (or combination thereof) on the design and implementation of the VPP concept, concerning (but not limited to) the application of: Active demand-side response, energy management, control and optimization, improved flexibility, reliability, and cyber-security, including the related key enabling information and communication technologies.

Published Papers (3 papers)

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Research

Open AccessArticle
Bi-Objective Dispatch of Multi-Energy Virtual Power Plant: Deep-Learning-Based Prediction and Particle Swarm Optimization
Appl. Sci. 2019, 9(2), 292; https://doi.org/10.3390/app9020292 - 15 Jan 2019
Cited by 3
Abstract
This paper addresses the coordinative operation problem of multi-energy virtual power plant (ME-VPP) in the context of energy internet. A bi-objective dispatch model is established to optimize the performance of ME-VPP in terms of economic cost (EC) and power quality (PQ). Various realistic [...] Read more.
This paper addresses the coordinative operation problem of multi-energy virtual power plant (ME-VPP) in the context of energy internet. A bi-objective dispatch model is established to optimize the performance of ME-VPP in terms of economic cost (EC) and power quality (PQ). Various realistic factors are considered, which include environmental governance, transmission ratings, output limits, etc. Long short-term memory (LSTM), a deep learning method, is applied to the promotion of the accuracy of wind prediction. An improved multi-objective particle swarm optimization (MOPSO) is utilized as the solving algorithm. A practical case study is performed on Hongfeng Eco-town in Southwestern China. Simulation results of three scenarios verify the advantages of bi-objective optimization over solely saving EC and enhancing PQ. The Pareto frontier also provides a visible and flexible way for decision-making of ME-VPP operator. Two strategies, “improvisational” and “foresighted”, are compared by testing on the Institute of Electrical and Electronic Engineers (IEEE) 118-bus benchmark system. It is revealed that “foresighted” strategy, which incorporates LSTM prediction and bi-objective optimization over a 5-h receding horizon, takes 10 Pareto dominances in 24 h. Full article
(This article belongs to the Special Issue Progress in Virtual Power Plant Design and Applications)
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Open AccessArticle
Multi-Objective Virtual Power Plant Construction Model Based on Decision Area Division
Appl. Sci. 2018, 8(9), 1484; https://doi.org/10.3390/app8091484 - 30 Aug 2018
Cited by 2
Abstract
Virtual power plant (VPP) is an effective technology form to aggregate the distributed energy resources (DERs), which include distributed generation (DG), energy storage (ES) and demand response (DR). The establishment of a unified and coordinated control of VPP is an important means to [...] Read more.
Virtual power plant (VPP) is an effective technology form to aggregate the distributed energy resources (DERs), which include distributed generation (DG), energy storage (ES) and demand response (DR). The establishment of a unified and coordinated control of VPP is an important means to achieve the interconnection of energy internet. Therefore, this paper focuses on the research of VPP construction model. Firstly, a preliminary introduction on all kinds of the DERs is carried out. According to the relevant guidelines, the decision area of the VPP is carefully divided, and the decision variables representing the various resources in the area are determined. Then, in order to get a VPP with low daily average cost, good load characteristics, high degree of DG consumption and high degree of resource aggregation, a multi-objective VPP construction model based on decision area division is established, and various constraints including geographic information are considered. The improved bat algorithm based on priority selection is used to solve this model. Finally, the correctness and effectiveness of the model are verified by an example. Full article
(This article belongs to the Special Issue Progress in Virtual Power Plant Design and Applications)
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Open AccessArticle
A Virtual Power Plant Architecture for the Demand-Side Management of Smart Prosumers
Appl. Sci. 2018, 8(3), 432; https://doi.org/10.3390/app8030432 - 13 Mar 2018
Cited by 42
Abstract
In this paper, we present a conceptual study on a Virtual Power Plant (VPP) architecture for the optimal management of Distributed Energy Resources (DERs) owned by prosumers participating in Demand-Side Management (DSM) programs. Compared to classical VPP architectures, which aim to aggregate several [...] Read more.
In this paper, we present a conceptual study on a Virtual Power Plant (VPP) architecture for the optimal management of Distributed Energy Resources (DERs) owned by prosumers participating in Demand-Side Management (DSM) programs. Compared to classical VPP architectures, which aim to aggregate several DERs dispersed throughout the electrical grid, in the proposed VPP architecture the supervised physical domain is limited to single users, i.e., to single Points of Delivery (PODs) of the distribution network. The VPP architecture is based on a service-oriented approach, where multiple agents cooperate to implement the optimal management of the prosumer’s assets, by also considering different forms of Demand Response (DR) requests. The considered DR schemes range from Price-Based DRs to Event-Based DRs, covering both the normal operating functions and the emergency control requests applied in modern distribution networks. With respect to centralized approaches, in this study the control perspective is moved from the system level to the single prosumer’s level, who is allowed to independently provide flexible power profiles through the aggregation of multiple DERs. A generalized optimization model, formulated as a Mixed-Integer Linear Programming (MILP) problem, is also introduced. Such a model is able to compute the optimal scheduling of a prosumer’s assets by considering both DR requests and end-users’ requirements in terms of comfort levels while minimizing the costs. Full article
(This article belongs to the Special Issue Progress in Virtual Power Plant Design and Applications)
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