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Special Issue "Integration of Electric Vehicles and Battery Storage Systems"

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

Deadline for manuscript submissions: closed (20 October 2020) | Viewed by 12169

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Special Issue Editor

Prof. Dr. Hrvoje Pandžić
E-Mail Website
Guest Editor
Department of Energy and Power Systems, Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia
Interests: power markets, smart grid, optimization and control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Applications of batteries range from use in electric vehicles to large-scale installations, making them active and important elements in modern power systems. For this Special Issue of Energies, we invite authors to submit novel research on the integration of battery energy storage in power systems at all levels including their use in electric vehicles, stationary behind-the-meter, and independent installations. Relevant topics include system-wide applications of batteries, e.g. independent or aggregated bidding in energy and/or flexibility markets; locational services for system operators, e.g., congestion management, voltage support, or black start service; or services to network users, e.g., energy management in microgrids or energy communities. We are specifically interested in the following areas:

  • Battery models that go beyond state-of-the-art technology;
  • Market participation models for (distributed) batteries;
  • Battery investment planning models;
  • Models that include an electric vehicle and/or home user-behavior;
  • Stacking of battery services to maximize profit;
  • Voltage control models;
  • Role of batteries at the distribution-level AC OPF;
  • Batteries ensuring the N-1 criterion;
  • Batteries used in industry facilities to provide demand management and retail arbitrage;
  • New methods or applications of treating uncertainty.

Prof. Dr. Hrvoje Pandžić
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 2200 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

  • electric vehicles
  • energy storage
  • aggregation
  • power system flexibility
  • energy markets
  • ancillary services

Published Papers (10 papers)

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Research

Article
Optimal Battery Storage Participation in European Energy and Reserves Markets
Energies 2020, 13(24), 6629; https://doi.org/10.3390/en13246629 - 15 Dec 2020
Cited by 5 | Viewed by 1039
Abstract
Battery energy storage is becoming an important asset in modern power systems. Considering the market prices and battery storage characteristics, reserve provision is a tempting play fields for such assets. This paper aims at filling the gap by developing a mathematically rigorous model [...] Read more.
Battery energy storage is becoming an important asset in modern power systems. Considering the market prices and battery storage characteristics, reserve provision is a tempting play fields for such assets. This paper aims at filling the gap by developing a mathematically rigorous model and applying it to the existing and future electricity market design in Europe. The paper presents a bilevel model for optimal battery storage participation in day-ahead energy market as a price taker, and reserve capacity and activation market as a price maker. It uses an accurate battery charging model to reliably represent the behavior of real-life lithium-ion battery storage. The proposed bilevel model is converted into a mixed-integer linear program by using the Karush–Kuhn–Tucker optimality conditions. The case study uses real-life data on reserve capacity and activation costs and quantities in German markets. The reserves activation quantities and activation prices are modeled by a set of credible scenarios in the lower-level problem. Finally, a sensitivity analysis is conducted to comprehend to what extent do battery storage bidding prices affect its overall profit. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Optimal Capacity Sizing for the Integration of a Battery and Photovoltaic Microgrid to Supply Auxiliary Services in Substations under a Contingency
Energies 2020, 13(22), 6037; https://doi.org/10.3390/en13226037 - 19 Nov 2020
Cited by 4 | Viewed by 657
Abstract
Auxiliary services are vital for the operation of a substation. If a contingency affects the distribution feeder that provides energy for the auxiliary services, it could lead to the unavailability of the substation’s service. Therefore, backup systems such as diesel generators are used. [...] Read more.
Auxiliary services are vital for the operation of a substation. If a contingency affects the distribution feeder that provides energy for the auxiliary services, it could lead to the unavailability of the substation’s service. Therefore, backup systems such as diesel generators are used. Another alternative is the adoption of a microgrid with batteries and photovoltaic generation to supply substation auxiliary services during a contingency. Nevertheless, high battery costs and the intermittence of photovoltaic generation requires a careful analysis so the microgrid capacity is defined in a compromise between the investment and the unavailability reduction of auxiliary services. This paper proposes a method for the capacity sizing of a microgrid with batteries, photovoltaic generation, and bidirectional inverters to supply auxiliary services in substations under a contingency. A set of alternatives is assessed through exhaustive search and Monte Carlo simulations to cater for uncertainties of contingencies and variation of solar irradiation. An unavailability index is proposed to measure the contribution of the integrated hybrid microgrid to reduce the time that the substation is not in operation. Simulations carried out showed that the proposed method identifies the microgrid capacity with the lowest investment that satisfies a goal for the unavailability of the substation service. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Operating and Investment Models for Energy Storage Systems
Energies 2020, 13(18), 4600; https://doi.org/10.3390/en13184600 - 04 Sep 2020
Cited by 5 | Viewed by 1123
Abstract
In the context of climate changes and the rapid growth of energy consumption, intermittent renewable energy sources (RES) are being predominantly installed in power systems. It has been largely elucidated that challenges that RES present to the system can be mitigated with energy [...] Read more.
In the context of climate changes and the rapid growth of energy consumption, intermittent renewable energy sources (RES) are being predominantly installed in power systems. It has been largely elucidated that challenges that RES present to the system can be mitigated with energy storage systems (ESS). However, besides providing flexibility to intermittent RES, ESS have other sources of revenue, such as price arbitrage in the markets, balancing services, and reducing the cost of electricity procurement to end consumers. In order to operate the ESS in the most profitable way, it is often necessary to make optimal siting and sizing decisions, and to determine optimal ways for the ESS to participate in a variety of energy and ancillary service markets. As a result, many publications on ESS models with various goals and operating environments are available. This paper aims at presenting the results of these papers in a structured way. A standard ESS model is first outlined, and that is followed by a literature review on operational and investment ESS models at the transmission and distribution levels. Both the price taking and price making models are elaborated on and presented in detail. Based on the examined body of work, the paper is concluded with recommendations for future research paths in the analysis of ESS. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Real-Time Processor-in-Loop Investigation of a Modified Non-Linear State Observer Using Sliding Modes for Speed Sensorless Induction Motor Drive in Electric Vehicles
Energies 2020, 13(16), 4212; https://doi.org/10.3390/en13164212 - 14 Aug 2020
Cited by 4 | Viewed by 1208
Abstract
Tracking performance and stability play a major role in observer design for speed estimation purpose in motor drives used in vehicles. It is all the more prevalent at lower speed ranges. There was a need to have a tradeoff between these parameters ensuring [...] Read more.
Tracking performance and stability play a major role in observer design for speed estimation purpose in motor drives used in vehicles. It is all the more prevalent at lower speed ranges. There was a need to have a tradeoff between these parameters ensuring the speed bandwidth remains as wide as possible. This work demonstrates an improved static and dynamic performance of a sliding mode state observer used for speed sensorless 3 phase induction motor drive employed in electric vehicles (EVs). The estimated torque is treated as a model disturbance and integrated into the state observer while the error is constrained in the sliding hyperplane. Two state observers with different disturbance handling mechanisms have been designed. Depending on, how they reject disturbances, based on their structure, their performance is studied and analyzed with respect to speed bandwidth, tracking and disturbance handling capability. The proposed observer with superior disturbance handling capabilities is able to provide a wider speed range, which is a main issue in EV. Here, a new dimension of model based design strategy is employed namely the Processor-in-Loop. The concept is validated in a real-time model based design test bench powered by RT-lab. The plant and the controller are built in a Simulink environment and made compatible with real-time blocksets and the system is executed in real-time targets OP4500/OP5600 (Opal-RT). Additionally, the Processor-in-Loop hardware verification is performed by using two adapters, which are used to loop-back analog and digital input and outputs. It is done to include a real-world signal routing between the plant and the controller thereby, ensuring a real-time interaction between the plant and the controller. Results validated portray better disturbance handling, steady state and a dynamic tracking profile, higher speed bandwidth and lesser torque pulsations compared to the conventional observer. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Electric Vehicles Plug-In Duration Forecasting Using Machine Learning for Battery Optimization
Energies 2020, 13(16), 4208; https://doi.org/10.3390/en13164208 - 14 Aug 2020
Cited by 2 | Viewed by 1151
Abstract
The aging of rechargeable batteries, with its associated replacement costs, is one of the main issues limiting the diffusion of electric vehicles (EVs) as the future transportation infrastructure. An effective way to mitigate battery aging is to act on its charge cycles, more [...] Read more.
The aging of rechargeable batteries, with its associated replacement costs, is one of the main issues limiting the diffusion of electric vehicles (EVs) as the future transportation infrastructure. An effective way to mitigate battery aging is to act on its charge cycles, more controllable than discharge ones, implementing so-called battery-aware charging protocols. Since one of the main factors affecting battery aging is its average state of charge (SOC), these protocols try to minimize the standby time, i.e., the time interval between the end of the actual charge and the moment when the EV is unplugged from the charging station. Doing so while still ensuring that the EV is fully charged when needed (in order to achieve a satisfying user experience) requires a “just-in-time” charging protocol, which completes exactly at the plug-out time. This type of protocol can only be achieved if an estimate of the expected plug-in duration is available. While many previous works have stressed the importance of having this estimate, they have either used straightforward forecasting methods, or assumed that the plug-in duration was directly indicated by the user, which could lead to sub-optimal results. In this paper, we evaluate the effectiveness of a more advanced forecasting based on machine learning (ML). With experiments on a public dataset containing data from domestic EV charge points, we show that a simple tree-based ML model, trained on each charge station based on its users’ behaviour, can reduce the forecasting error by up to 4× compared to the simple predictors used in previous works. This, in turn, leads to an improvement of up to 50% in a combined aging-quality of service metric. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Integration of Electric Vehicles in Low-Voltage Distribution Networks Considering Voltage Management
Energies 2020, 13(16), 4125; https://doi.org/10.3390/en13164125 - 10 Aug 2020
Cited by 4 | Viewed by 660
Abstract
The expected growth of the number of electric vehicles can be challenging for planning and operating power systems. In this sense, distribution networks are considered the Achilles’ heel of the process of adapting current power systems for a high presence of electric vehicles. [...] Read more.
The expected growth of the number of electric vehicles can be challenging for planning and operating power systems. In this sense, distribution networks are considered the Achilles’ heel of the process of adapting current power systems for a high presence of electric vehicles. This paper aims at deciding the maximum number of three-phase high-power charging points that can be installed in a low-voltage residential distribution grid. In order to increase the number of installed charging points, a mixed-integer formulation is proposed to model the provision of decentralized voltage support by electric vehicle chargers. This formulation is afterwards integrated into a modified AC optimal power flow formulation to characterize the steady-state operation of the distribution network during a given planning horizon. The performance of the proposed formulations have been tested in a case study based on the distribution network of La Graciosa island in Spain. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Network and Market-Aware Bidding to Maximize Local RES Usage and Minimize Cost in Energy Islands with Weak Grid Connections
Energies 2020, 13(16), 4043; https://doi.org/10.3390/en13164043 - 05 Aug 2020
Viewed by 1147
Abstract
The increasing renewable energy sources RES penetration in today’s energy islands and rural energy communities with weak grid connections is expected to incur severe distribution network stability problems (i.e., congestion, voltage issues). Tackling these problems is even more challenging since RES spillage minimization [...] Read more.
The increasing renewable energy sources RES penetration in today’s energy islands and rural energy communities with weak grid connections is expected to incur severe distribution network stability problems (i.e., congestion, voltage issues). Tackling these problems is even more challenging since RES spillage minimization and energy cost minimization for the local energy community are set as major pre-requisites. In this paper, we consider a Microgrid Operator (MGO) that: (i) gradually decides the optimal mix of its RES and flexibility assets’ (FlexAsset) sizing, siting and operation, (ii) respects the physical distribution network constraints in high RES penetration contexts, and (iii) is able to bid strategically in the existing day-ahead energy market. We model this problem as a Stackelberg game, expressed as a Mathematical Problem with Equilibrium Constraints (MPEC), which is finally transformed into a tractable Mixed Integer Linear Program (MILP). The performance evaluation results show that the MGO can lower its costs when bidding strategically, while the coordinated planning and scheduling of its FlexAssets result in higher RES utilization, as well as distribution network aware and cost-effective RES and FlexAsset operation. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Fuzzy Logic Weight Based Charging Scheme for Optimal Distribution of Charging Power among Electric Vehicles in a Parking Lot
Energies 2020, 13(12), 3119; https://doi.org/10.3390/en13123119 - 16 Jun 2020
Cited by 23 | Viewed by 1309
Abstract
Electric vehicles (EVs) parking lots are representing significant charging loads for relatively a long period of time. Therefore, the aggregated charging load of EVs may coincide with the peak demand of the distribution power system and can greatly stress the power grid. The [...] Read more.
Electric vehicles (EVs) parking lots are representing significant charging loads for relatively a long period of time. Therefore, the aggregated charging load of EVs may coincide with the peak demand of the distribution power system and can greatly stress the power grid. The stress on the power grid can be characterized by the additional electricity demand and the introduction of a new peak load that may overwhelm both the substations and transmission systems. In order to avoid the stress on the power grid, the parking lot operators are required to limit the penetration level of EVs and optimally distribute the available power among them. This affects the EV owner’s quality of experience (QoE) and thereby reducing the quality of performance (QoP) for the parking lot operators. The QoE is represents the satisfaction level of EV owners; whereas, the QoP is a measurement representing the ratio of EVs with QoE to the total number of EVs. This study proposes a fuzzy logic weight-based charging scheme (FLWCS) to optimally distribute the charging power among the most appropriate EVs in such a way that maximizes the QoP for the parking lot operators under the operational constraints of the power grid. The developed fuzzy inference mechanism resolves the uncertainties and correlates the independent inputs such as state-of-charge, the remaining parking duration and the available power into weighted values for the EVs in each time slot. Once the weight values for all EVs are known, their charging operations are controlled such that the operational constraints of the power grid are respected in each time slot. The proposed FLWCS is applied to a parking lot with different capacities. The simulation results reveal an improved QoP comparing to the conventional first-come-first-served (FCFS) based scheme. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Study of a Bidirectional Power Converter Integrated with Battery/Ultracapacitor Dual-Energy Storage
Energies 2020, 13(5), 1234; https://doi.org/10.3390/en13051234 - 06 Mar 2020
Cited by 6 | Viewed by 1622
Abstract
A patented bidirectional power converter was studied as an interface to connect the DC-bus of driving inverter, battery energy storage (BES), and ultracapacitor (UC) to solve the problem that the driving motor damages the battery life during acceleration and deceleration in electric vehicles [...] Read more.
A patented bidirectional power converter was studied as an interface to connect the DC-bus of driving inverter, battery energy storage (BES), and ultracapacitor (UC) to solve the problem that the driving motor damages the battery life during acceleration and deceleration in electric vehicles (EVs). The proposed concept was to adopt a multiport switch to control the power flow and achieve the different operating mode transitions for the better utilization of energy. In addition, in order to improve the conversion efficiency, the proposed converter used a coupled inductor and interleaved-pulse-width-modulation (IPWM) control to achieve a high voltage conversion ratio (i.e., bidirectional high step-up/down conversion characteristics). This study discussed the steady-state operation and characteristic analysis of the proposed converter. Finally, a 500 W power converter prototype with specifications of 72 V DC-bus, 24 V BES, and 48 V UC was built, and the feasibility was verified by simulation and experiment results. The highest efficiency points of the realized prototype were 97.4%, 95.5%, 97.2%, 97.1%, and 95.3% for the UC charge, battery charge, UC discharge, the dual-energy in series discharge, and battery discharge modes, respectively. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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Article
Logistics Design for Mobile Battery Energy Storage Systems
Energies 2020, 13(5), 1157; https://doi.org/10.3390/en13051157 - 04 Mar 2020
Cited by 8 | Viewed by 1661
Abstract
Currently, there are three major barriers toward a greener energy landscape in the future: (a) Curtailed grid integration of energy from renewable sources like wind and solar; (b) The low investment attractiveness of large-scale battery energy storage systems; and, (c) Constraints from the [...] Read more.
Currently, there are three major barriers toward a greener energy landscape in the future: (a) Curtailed grid integration of energy from renewable sources like wind and solar; (b) The low investment attractiveness of large-scale battery energy storage systems; and, (c) Constraints from the existing electric infrastructure on the development of charging station networks to meet the increasing electrical transportation demands. A new conceptual design of mobile battery energy storage systems has been proposed in recent studies to reduce the curtailment of renewable energy while limiting the public costs of battery energy storage systems. This work designs a logistics system in which electric semi-trucks ship batteries between the battery energy storage system and electric vehicle charging stations, enabling the planning and operation of power grid independent electric vehicle charging station networks. This solution could be viable in many regions in the United States (e.g., Texas) where there are plenty of renewable resources and little congestion pressure on the road networks. With Corpus Christi, Texas and the neighboring Chapman Ranch wind farm as the test case, this work implement such a design and analyze its performance based on the simulation of its operational processes. Further, we formulate an optimization problem to find design parameters that minimize the total costs. The main design parameters include the number of trucks and batteries. The results in this work, although preliminary, will be instrumental for potential stakeholders to make investment or policy decisions. Full article
(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)
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