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Smart Management of Distributed Energy Resources

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (30 April 2020) | Viewed by 19477

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Special Issue Editor

Dr. Liana Cipcigan

E-Mail Website1 Website2
Guest Editor

School of Engineering, Cardiff University, Wales, UK
Interests: power systems control; electric vehicles control; distributed generation; renewable energy sources; smart grids; virtual power plants; smart management of charging infrastructure

Special Issue Information

Dear Colleagues,

It is my pleasure to invite submissions to the Special Issue on “Smart Management of Distributed Energy Resources”.

The transition to a low-carbon economy and more stringent environmental targets will involve major changes to the way we supply and use electricity over coming years. There will be a complex mix of technologies for generating, transmitting, distributing, and storing electricity by 2050. Distribution networks are facing significant challenges to accommodate the increasing number of distributed energy resources (DER), including the impacts associated with the electrification of transport and heating sectors. In order to transition into a low carbon and digitised network, a more flexible demand side is required. Therefore, this Special Issue aims to demonstrate how intelligent control and market design, suitable for both current and future needs, can remove barriers to a high level of distributed energy resources integration.

In this Special Issue, we invite original and unpublished research work in areas including (but not limited to)

Distributed energy resources as flexibility service providers
Aggregators, and virtual power plants to facilitate DER integration
Forecasting distributed energy resources
Solutions to use DER for resolving transmission constraints (active and reactive power services)
Advanced data and intelligent control systems for a high level of DER integration
The demonstration of intelligent control systems (centralised, decentralised, and hierarchical) for DER integration
Electric vehicles and vehicle to grid to provide flexibility services
DER trading for ancillary services and balancing markets
Blockchain and distributed ledger solutions for electricity market design
Applications of IoT to combine edge and cloud resources, and local forecast of DER
Improving visibility beyond the meter of energy production, consumption and storage
Multi agent systems for DER management

Dr. Liana Cipcigan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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

distributed energy resources
flexibility services
virtual power plants
intelligent control
ancillary services
electric vehicles
vehicle to grid
blockchain

Published Papers (6 papers)

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Research

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11 pages, 5983 KiB

Open AccessArticle

Development and Verification of Hybrid Power Controller Using Indoor HIL Test for the Solar UAV

by Sunghun Jung

Energies 2020, 13(8), 2110; https://0-doi-org.brum.beds.ac.uk/10.3390/en13082110 - 24 Apr 2020

Cited by 3 | Viewed by 2500

Abstract

A hybrid power system (HPS) is developed for the photovoltaic (PV) powered and tethered multirotor unmanned aerial vehicle (UAV) based on the robot operating system (ROS) and verified using an indoor hardware-in-the-loop (HIL) test. All the processes, including a UAV flight mode change (i.e., takeoff, hovering, and landing) and power flow control (consisting of PV modules, a LiPo battery pack, and a UAV) are completely automated using a combination of Pixhawk 2.1 and the Raspberry Pi 3 Model B (RPi 3B). Once the indoor HIL test starts, (1) the UAV takes off and hovers with a preassigned 10 m altitude at a fixed point and keeps hovering until the voltage drops below 13.4

V

; (2) the UAV lands when the voltage drops below 13.4 V, and the hybrid power controller (HPC) starts to charge the LiPo battery pack using the energy from PV modules; and (3) the UAV takes off when the voltage of the battery pack becomes more than 16.8 V, and the procedure repeats from (1). A PV-powered and tethered multirotor UAV using the proposed HPS can fly more safely for a longer time, particularly in an urban area, and so it is competitive to the traditional multirotor type UAV in the sense of both the flight time and the surveillance mission performance. Full article

(This article belongs to the Special Issue Smart Management of Distributed Energy Resources)

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14 pages, 557 KiB

Open AccessArticle

Penalty Based Control Mechanism for Strategic Prosumers in a Distribution Network

by Arnob Ghosh and Vaneet Aggarwal

Energies 2020, 13(2), 452; https://0-doi-org.brum.beds.ac.uk/10.3390/en13020452 - 17 Jan 2020

Cited by 4 | Viewed by 1785

Abstract

The distribution side of the traditional power grid is changing as the users (known as prosumers) can inject power to the grid. However, uncontrollable injection of power can destabilize the grid. Thus, the stability of the grid must be maintained. Since the prosumers are self-interested entities, they will take their actions to maximize their own pay-offs. We formulate the problem as a non-cooperative game theoretic problem where the magnitude of the voltage must be within an acceptable limit at each node of the power network. Since the power-flow equations must be satisfied at each node, it becomes a coupled constrained game where the constraints are the same across the prosumers. We propose a distributed penalty based algorithm which converges to an equilibrium. In this mechanism, the prosumers are quoted a price based on the active and reactive power drawn or injected to the power grid. The algorithm is easy to implement and it converges to an efficient solution which maximizes the sum of the utilities of the prosumers while maintaining the grid’s stability. Full article

(This article belongs to the Special Issue Smart Management of Distributed Energy Resources)

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20 pages, 2940 KiB

Open AccessArticle

Multi-period Market Operation of Transmission-Distribution Systems Based on Heterogeneous Decomposition and Coordination

by Cong Liu, Jingyang Zhou, Yi Pan, Zhiyi Li, Yifei Wang, Dan Xu, Qiang Ding, Zhiqiang Luo and Mohammad Shahidehpour

Energies 2019, 12(16), 3126; https://0-doi-org.brum.beds.ac.uk/10.3390/en12163126 - 14 Aug 2019

Cited by 4 | Viewed by 2462

Abstract

The integration of shiftable/curtailment distribution generators (DGs) along with quick-response storage has not only increased the transaction’s flexibility but also puzzled the bidding willingness of transmission-connected market players (TMPs). In this paper, the method of heterogeneous decomposition and coordination (HGDC) is applied to decompose the integrated transmission-distribution market framework into a bi-level problem with a transmission wholesale market master problem and several distribution retail market subproblems in a decentralized organization structure. The price-based bidding willingness of demand-side resources’ (DSRs’) aggregator is simulated considering the relation between distribution system operator’s (DSO’s) operation modes and its equivalent market transactive price. Besides the traditional mixed-integer linear programming (MILP) model, the active reconfiguration model of DSOs based on mixed-integer second-order conic programming (MI-SOCP) is proposed to rearrange its operation switch status and elaborate its operation cost according to the market transaction. Multi-period optimal operation modes could be obtained through an HGDC-based iteration process by coordinating the transmission system operator (TSO) with DSOs and considering the market energy equilibrium and reserve requirements for security considerations. Karush-Kuhn-Tucker (KKT) conditions are used to testify the optimality and convergence of the bi-level model in theory. The T5-3D33 case is employed to illustrate the efficiency of the proposed model and method. Full article

(This article belongs to the Special Issue Smart Management of Distributed Energy Resources)

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23 pages, 4088 KiB

Open AccessArticle

Stochastic Adaptive Robust Dispatch for Virtual Power Plants Using the Binding Scenario Identification Approach

by Guoqiang Sun, Weihang Qian, Wenjin Huang, Zheng Xu, Zhongxing Fu, Zhinong Wei and Sheng Chen

Energies 2019, 12(10), 1918; https://0-doi-org.brum.beds.ac.uk/10.3390/en12101918 - 20 May 2019

Cited by 18 | Viewed by 2753

Abstract

The present study establishes a stochastic adaptive robust dispatch model for virtual power plants (VPPs) to address the risks associated with uncertainties in electricity market prices and photovoltaic (PV) power outputs. The model consists of distributed components, such as the central air-conditioning system (CACS) and PV power plant, aggregated by the VPP. The uncertainty in the electricity market price is addressed using a stochastic programming approach, and the uncertainty in PV output is addressed using an adaptive robust approach. The model is decomposed into a master problem and a sub-problem using the binding scenario identification approach. The binding scenario subset is identified in the sub-problem, which greatly reduces the number of iterations required for solving the model, and thereby increases the computational efficiency. Finally, the validity of the VPP model and the solution algorithm is verified using a simulated case study. The simulation results demonstrate that the operating profit of a VPP with a CACS and other aggregated units can be increased effectively by participating in multiple market transactions. In addition, the results demonstrate that the binding scenario identification algorithm is accurate, and its computation time increases slowly with increasing scenario set size, so the approach is adaptable to large-scale scenarios. Full article

(This article belongs to the Special Issue Smart Management of Distributed Energy Resources)

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17 pages, 3300 KiB

Open AccessArticle

Optimizing the Regulation of Aggregated Thermostatically Controlled Loads by Jointly Considering Consumer Comfort and Tracking Error

by Jie Yang, Tongyu Liu, Huaibao Wang, Zhenhua Tian and Shihao Liu

Energies 2019, 12(9), 1757; https://0-doi-org.brum.beds.ac.uk/10.3390/en12091757 - 09 May 2019

Cited by 7 | Viewed by 1847

Abstract

Thermostatically controlled loads (TCLs) are promising to offer demand-side regulation with proper control. In this paper, the aggregate power of TCLs is used to track the automatic generation control (AGC) signal by changing the temperature setpoint. The dynamics of the indoor temperature are described by a Monte Carlo model, and population dissatisfaction is described by the predicted percentage of dissatisfied (PPD). The objective is optimization from two aspects, minimizing both population dissatisfaction and tracking error. We propose an improved active target particle swarm optimization (APSO) algorithm to optimize the model, making it possible to ensure that the user’s dissatisfaction is as small as possible while the aggregate power tracks the AGC signal. The novelty of this paper is to introduce PPD into the model and at the same time establish three models using PPD as the objective function and constraints. The simulation results are shown to verify the efficiency of the designed model. Full article

(This article belongs to the Special Issue Smart Management of Distributed Energy Resources)

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Review

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26 pages, 1192 KiB

Open AccessFeature PaperReview

Review of Voltage and Reactive Power Control Algorithms in Electrical Distribution Networks

by Daiva Stanelyte and Virginijus Radziukynas

Energies 2020, 13(1), 58; https://0-doi-org.brum.beds.ac.uk/10.3390/en13010058 - 20 Dec 2019

Cited by 40 | Viewed by 7608

Abstract

The traditional unidirectional, passive distribution power grids are rapidly developing into bidirectional, interactive, multi-coordinated smart grids that cover distributed power generation along with advanced information communications and electronic power technologies. To better integrate the use of renewable energy resources into the grid, to improve the voltage stability of distribution grids, to improve the grid protection and to reduce harmonics, one needs to select and control devices with adjustable reactive power (capacitor batteries, transformers, and reactors) and provide certain solutions so that the photovoltaic (PV) converters maintain due to voltage. Conventional compensation methods are no longer appropriate, thus developing measures are necessary that would ensure local reactive and harmonic compensation in case an energy quality problem happens in the low voltage distribution grid. Compared to the centralized methods, artificial intelligence (heuristic) methods are able to distribute computing and communication tasks among control devices. Full article

(This article belongs to the Special Issue Smart Management of Distributed Energy Resources)

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