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Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 26384

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Prof. Dr. João Soares

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GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, LASI—Intelligent Systems Associate Laboratory, Polytechnic of Porto, 4200-072 Porto, Portugal
Interests: energy resource management; energy systems simulation; electric vehicles; metaheuristic optimization; smart grid; swarm intelligence
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Dr. Bruno Canizes

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GECAD–Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Institute of Engineering, Polytechnic of Porto (ISEP/IPP), 4200-072 Porto, Portugal
Interests: distribution network planning; operation and reconfiguration; smart grids; smart cities; electric mobility; distributed energy resources management; power systems reliability; future power systems; optimization; electricity markets and intelligent house management systems
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Prof. Dr. Zita Vale

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GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Polytechnic of Porto (P.PORTO), P-4200-465 Porto, Portugal
Interests: artificial intelligence; demand response; electric vehicles; electricity markets; power and energy systems; renewable and sustainable energy; smart grids
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Special Issue Information

Dear Colleagues,

At present, sustainability is a key point in many research fields and domains. Rethinking policies, strategies, and developing new technology to keep the world growing at a fast pace in the different domains in a sustainable way is a challenging task. Power systems are no different, and in the last few years, new technologies have established a new paradigm to create and develop a future sustainable grid.

The European Union (EU) commission fixed a binding renewable energy target of at least 32% in the EU for 2030. As a consequence, huge investments have been made in renewable-based electricity generation plants and equipment in parallel with several smart grid initiatives to support this target achievement.

Power systems, namely at the distribution level, are facing new challenges to deal with the integration of intermittent renewable-based energy sources. Further, the expected mass penetration of electric vehicles will bring more complexity to the operation and planning tasks, but if properly undertaken, it can also allow unique opportunities. This Special Issue focuses on planning and operation of distribution power networks under smart grid paradigm where prosumers, electric vehicles, and other typical loads are usually connected. Topics of interest for publication include but are not limited to the following:

Planning of smart grid considering uncertainty factors and/or multistage investments (e.g., renewable generation and electric vehicles growth in the mid-long term);
Proposal for lowering grid operation cost and increasing the sustainability of smart grids (e.g., methods dealing with big data or smart metering to retrieve valuable information for grid operation);
Renewable energy, demand-response, smart distribution grids;
Energy management system in smart distribution grids;
Advanced flexibility strategies for smart distribution grids;
Electric vehicles planning and operation in smart grid (including behavior models for simulation and optimization of EVs in the grid).

Dr. João Soares
Dr. Bruno Canizes
Prof. Zita Vale
Guest Editors

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.

Published Papers (9 papers)

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Editorial

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4 pages, 175 KiB

Open AccessEditorial

Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation

by Joao Soares, Bruno Canizes and Zita Vale

Energies 2021, 14(23), 7931; https://0-doi-org.brum.beds.ac.uk/10.3390/en14237931 - 26 Nov 2021

Cited by 2 | Viewed by 1350

Abstract

This editorial document provides the main motivations and a brief description of each paper published in the “Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation” Special Issue. This Special Issue aims to present several innovative solutions on planning and operation of distribution power networks under smart grid paradigm where prosumers, electric vehicles, and other typical loads are usually connected. Some of those solutions and computational applications were covered in this Special Issue, namely probabilistic power flow, voltage and power factor control, agent-based simulation, digital twin, resilient energy scheduling, and uncertainty modeling are among the contributions. The published works are very timely and are of great interest, which will certainly drive the impact of future researchers in the near term concerning the field of this Special Issue. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

Research

Jump to: Editorial

12 pages, 1191 KiB

Open AccessArticle

Voltage Control Strategy for Energy Storage System in Sustainable Distribution System Operation

by Yue Zhang and Anurag Srivastava

Energies 2021, 14(4), 832; https://0-doi-org.brum.beds.ac.uk/10.3390/en14040832 - 05 Feb 2021

Cited by 19 | Viewed by 2635

Abstract

Due to the increasing penetration of distributed energy resources (DERs) required for the sustainable distribution system, new voltage control strategy is needed by utilities. Traditional voltage control strategy can not support the increasing number of DERs in a coordinated and scalable manner to meet the operational voltage regulation requirement. Supported by the power electronics converter, the energy storage system can provide fast, smooth, and flexible voltage control services. In this paper, an effective and easy to implement sensitivity-based voltage control strategy is developed for the energy storage system. The developed control strategy is validated using an industrial feeder data in Northwest Washington. The proposed strategy can mitigate the voltage unbalance issue, improve the voltage profile, and correct power factors while supporting sustainable distribution system operation. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

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17 pages, 3248 KiB

Open AccessArticle

Voltage Reduction in Medium Voltage Distribution Systems Using Constant Power Factor Control of PV PCS

by Daisuke Iioka, Takahiro Fujii, Toshio Tanaka, Tsuyoshi Harimoto and Junpei Motoyama

Energies 2020, 13(20), 5430; https://0-doi-org.brum.beds.ac.uk/10.3390/en13205430 - 17 Oct 2020

Cited by 8 | Viewed by 1890

Abstract

Reverse power flow from a photovoltaic (PV) system in a distribution system causes a voltage rise. A relative study regarding the reduction in the distribution feeder voltage depending on system conditions and the magnitude of reverse power flow has been conducted. Several methods for mitigating voltage rise have been proposed; however, the influence of these methods on the voltage in the distribution system, where the voltage is reduced due to reverse power flow, remains to be determined. In this study, the effect of constant power factor control in low-voltage PV systems, which are widely used as voltage rise countermeasures in distribution systems, was analyzed under the condition that the distribution line voltage decreases due to reverse power flow. Consequently, the constant power factor control of the low-voltage distribution system was found to adversely reduce voltage in the medium voltage distribution system due to the consumption of lagging reactive power by the PV systems. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

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13 pages, 1773 KiB

Open AccessArticle

An Agent-Based Approach for the Planning of Distribution Grids as a Socio-Technical System

by Luciano Cavalcante Siebert, Alexandre Rasi Aoki, Germano Lambert-Torres, Nelson Lambert-de-Andrade and Nikolaos G. Paterakis

Energies 2020, 13(18), 4837; https://0-doi-org.brum.beds.ac.uk/10.3390/en13184837 - 16 Sep 2020

Cited by 8 | Viewed by 1883

Abstract

Recent developments, such as smart metering, distributed energy resources, microgrids, and energy storage, have led to an exponential increase in system complexity and have emphasized the need to include customer behavior and social and cultural backgrounds in planning activities. This paper analyzes how emergent behavior in electricity consumption can affect the planning of distribution grids with a smart grid vision. For this, an agent-based model that uses insights from the field of behavioral economics to differentiate four consumer categories (high income, low income, middle class, and early adopters) was used. The model was coupled with a real distribution feeder and customer load curve data, and the results showed that heterogeneity of customer’s preferences, values, and behavior led to very distinct load growth patterns. The results emphasize the relevance of modeling customer’s behavioral aspects in planning increasingly complex power systems. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

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21 pages, 4335 KiB

Open AccessArticle

IoT-Based Digital Twin for Energy Cyber-Physical Systems: Design and Implementation

by Ahmed Saad, Samy Faddel and Osama Mohammed

Energies 2020, 13(18), 4762; https://0-doi-org.brum.beds.ac.uk/10.3390/en13184762 - 12 Sep 2020

Cited by 66 | Viewed by 5804

Abstract

With the emergence of distributed energy resources (DERs), with their associated communication and control complexities, there is a need for an efficient platform that can digest all the incoming data and ensure the reliable operation of the power system. The digital twin (DT) is a new concept that can unleash tremendous opportunities and can be used at the different control and security levels of power systems. This paper provides a methodology for the modelling of the implementation of energy cyber-physical systems (ECPSs) that can be used for multiple applications. Two DT types are introduced to cover the high-bandwidth and the low-bandwidth applications that need centric oversight decision making. The concept of the digital twin is validated and tested using Amazon Web Services (AWS) as a cloud host that can incorporate physical and data models as well as being able to receive live measurements from the different actual power and control entities. The experimental results demonstrate the feasibility of the real-time implementation of the DT for the ECPS based on internet of things (IoT) and cloud computing technologies. The normalized mean-square error for the low-bandwidth DT case was 3.7%. In the case of a high-bandwidth DT, the proposed method showed superior performance in reconstructing the voltage estimates, with 98.2% accuracy from only the controllers’ states. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

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19 pages, 8324 KiB

Open AccessArticle

Schedule Optimization in a Smart Microgrid Considering Demand Response Constraints

by Julian Garcia-Guarin, David Alvarez, Arturo Bretas and Sergio Rivera

Energies 2020, 13(17), 4567; https://0-doi-org.brum.beds.ac.uk/10.3390/en13174567 - 03 Sep 2020

Cited by 11 | Viewed by 2373

Abstract

Smart microgrids (SMGs) may face energy rationing due to unavailability of energy resources. Demand response (DR) in SMGs is useful not only in emergencies, since load cuts might be planned with a reduction in consumption but also in normal operation. SMG energy resources include storage systems, dispatchable units, and resources with uncertainty, such as residential demand, renewable generation, electric vehicle traffic, and electricity markets. An aggregator can optimize the scheduling of these resources, however, load demand can completely curtail until being neglected to increase the profits. The DR function (DRF) is developed as a constraint of minimum size to supply the demand and contributes solving of the 0-1 knapsack problem (KP), which involves a combinatorial optimization. The 0-1 KP stores limited energy capacity and is successful in disconnecting loads. Both constraints, the 0-1 KP and DRF, are compared in the ranking index, load reduction percentage, and execution time. Both functions turn out to be very similar according to the performance of these indicators, unlike the ranking index, in which the DRF has better performance. The DRF reduces to 25% the minimum demand to avoid non-optimal situations, such as non-supplying the demand and has potential benefits, such as the elimination of finite combinations and easy implementation. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

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22 pages, 6607 KiB

Open AccessArticle

Enhanced Coordination Strategy for an Aggregator of Distributed Energy Resources Participating in the Day-Ahead Reserve Market

by Cindy Paola Guzman, Nataly Bañol Arias, John Fredy Franco, Marcos J. Rider and Rubén Romero

Energies 2020, 13(8), 1965; https://0-doi-org.brum.beds.ac.uk/10.3390/en13081965 - 16 Apr 2020

Cited by 11 | Viewed by 2483

Abstract

The integration of distributed energy resources (DERs), e.g., electric vehicles (EVs) and renewable distributed generation (DG), in the electrical distribution system (EDS) brings advantages to society, but also introduces technical challenges (e.g., overloading and voltage issues). A DER aggregator, which has agreements with DERs to manage their consumption/generation, could collaborate with the EDS operator to mitigate those technical challenges. Previous approaches have mainly focused on the aggregator’s strategy to manage demand, aiming at the maximization of profits. Therefore, methods to support the aggregator’s strategy need to be extended to facilitate the integration of renewable DG, leading to an enhanced coordination of DERs. This paper proposes a linear programming model for the aggregator’s coordination strategy to maximize its profit through the management of DERs and the participation in the day-ahead reserve market. The model uses EV charging control to provide up/down reserve and reduces its cost taking advantage of DG. The proposed mathematical model represents the daily EDS operation (hourly resolution) to enforce voltage and current magnitude constraints. A case study carried out in an unbalanced 34-bus EDS with 660 EVs, demonstrates that the application of the proposed method enhances the DER aggregator’s strategy, leading to better outcomes in both profits and EDS operation. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

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16 pages, 1904 KiB

Open AccessArticle

A Mixed Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

by Zahra Foroozandeh, Sérgio Ramos, João Soares, Fernando Lezama, Zita Vale, António Gomes and Rodrigo L. Joench

Energies 2020, 13(7), 1719; https://0-doi-org.brum.beds.ac.uk/10.3390/en13071719 - 04 Apr 2020

Cited by 24 | Viewed by 3925

Abstract

Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs charge and discharge processes and also those of BESS, in which the binary decision variables represent the charging and discharging of EVs/BESS in each period. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis are considered. The results point to a 65% reduction in peak load consumption supplied by an external power grid and a 28.4% reduction in electricity consumption costs. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

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24 pages, 4598 KiB

Open AccessArticle

Probabilistic Load Flow Algorithm of Distribution Networks with Distributed Generators and Electric Vehicles Integration

by Bowen Zhou, Xiao Yang, Dongsheng Yang, Zhile Yang, Tim Littler and Hua Li

Energies 2019, 12(22), 4234; https://0-doi-org.brum.beds.ac.uk/10.3390/en12224234 - 06 Nov 2019

Cited by 9 | Viewed by 2209

Abstract

Probabilistic Load Flow (PLF) calculations are important tools for analysis of the steady-state operation of electrical energy networks, especially for electrical energy distribution networks with large-scale distributed generators (DGs) and electric vehicle (EV) integration. Traditional PLF has used the Cumulant Method (CM) and Latin Hypercube Sampling (LHS) method. However, traditional CM requires that each input variable be independent of one another, and the Cholesky decomposition adopted by the traditional LHS has limitations in that it is only applicable for positive definite matrices. To solve these problems, taking into account the Q-MCS theory of LHS, this paper proposes a CM PLF algorithm based on improved LHS (ILHS-CM). The cumulants of the input variables are obtained based on sampling results. The probability distribution of the output variables is obtained according to the Gram-Charlier series expansion. Moreover, DGs, such as wind turbines, photovoltaic (PV) arrays, and EVs integrated into the electrical energy distribution networks are comprehensively considered, including correlation analysis and dynamic load flow analysis for EV-coordinated charging. Four scenarios are analyzed based on the IEEE-30 node network, including with/without DGs and EVs, error analysis and performance evaluation of the proposed algorithm, correlation analysis of DGs and EVs, and dynamic load flow analysis with EV integration. The results presented in this paper demonstrate the effectiveness, accuracy, and practicability of the proposed algorithm. Full article

(This article belongs to the Special Issue Rethinking the Distribution Power Network Planning and Operation for a Sustainable Smart Grid and Smooth Interaction with Electrified Transportation)

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