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15 pages, 3558 KiB

Open AccessArticle

The Coordinated Operation of Vertically Structured Power Systems for Electric Vehicle Charge Scheduling

by Yuana Adianto, Craig Baguley, Udaya Madawala, Nanang Hariyanto, Suwarno Suwarno and Teguh Kurniawan

Energies 2022, 15(1), 27; https://doi.org/10.3390/en15010027 - 21 Dec 2021

Cited by 10 | Viewed by 3282

Abstract

Charge scheduling can mitigate against issues arising from excessive electric vehicle (EV) charging loads and is commonly implemented using time-of-use pricing. A charge scheduling strategy to suit vertically structured power systems without relying on time-of-use pricing has not yet been reported, despite being [...] Read more.

Charge scheduling can mitigate against issues arising from excessive electric vehicle (EV) charging loads and is commonly implemented using time-of-use pricing. A charge scheduling strategy to suit vertically structured power systems without relying on time-of-use pricing has not yet been reported, despite being needed by industry. Therefore, a novel charge scheduling strategy to meet this need is proposed in this paper. Key aspects include the provision of a decision-making framework that accommodates for the considerations of transmission and distribution network operators, and the allowance for dynamically changing charging loads through timely forecast updates with reduced communication requirements. A case study based on the Indonesian Java-Bali power system is undertaken to demonstrate the strategy’s effectiveness. Different and realistic EV uptake scenarios are considered, using probabilistic modeling, survey work, and a Monte Carlo modeling approach. Even under slow EV charging conditions case study results show assets are overloaded and high electricity production costs are incurred. These are alleviated through adopting the proposed strategy. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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21 pages, 2992 KiB

Open AccessArticle

Marginal Value of Vehicle-to-Grid Ancillary Service in a Power System with Variable Renewable Energy Penetration and Grid Side Flexibility

by Ryosuke Kataoka, Kazuhiko Ogimoto and Yumiko Iwafune

Energies 2021, 14(22), 7577; https://doi.org/10.3390/en14227577 - 12 Nov 2021

Cited by 6 | Viewed by 2148

Abstract

Regulating the frequencies of power grids by controlling electric vehicle charging and discharging, known as vehicle-to-grid (V2G) ancillary services, is a promising and profitable means of providing flexibility that integrates variable renewable energy (VRE) into traditional power systems. However, the ancillary services market [...] Read more.

Regulating the frequencies of power grids by controlling electric vehicle charging and discharging, known as vehicle-to-grid (V2G) ancillary services, is a promising and profitable means of providing flexibility that integrates variable renewable energy (VRE) into traditional power systems. However, the ancillary services market is a niche, and the scale, saturation, and time-dependency are unclear when assuming future changes in the power system structure. We studied the marginal value of V2G ancillary services as a balancing capacity of the power system operation on the load-frequency control (LFC) timescale and evaluated the reasonable maximum capacity of the LFC provided by V2G. As a case study, we assumed that the Japanese power system would be used under various VRE penetration scenarios and considered the limited availability time of V2G, based on the daily commuter cycle. The power system operation was modeled by considering pumped storage, interconnection lines, and thermal power–partial load operations. The results show that the marginal value of V2G was greater during the daytime than overnight, and the maximum cost saving (USD 705.6/EV/year) occurred during the daytime under the high-VRE scenario. Improving the value and size of V2G ancillary services required coordination with energy storage and excess VRE generation. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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19 pages, 4367 KiB

Open AccessArticle

Economic Impacts of the Demand Response of Electric Vehicles Considering Battery Degradation

by Yumiko Iwafune and Kazuhiko Ogimoto

Energies 2020, 13(21), 5771; https://doi.org/10.3390/en13215771 - 4 Nov 2020

Cited by 8 | Viewed by 2308

Abstract

The increase in the number of electric vehicles (EVs) has led to increased global expectations that the application of this technology may result in the reduction of CO₂ emissions through the replacement of conventional petrol vehicles and ensure the flexibility of power [...] Read more.

The increase in the number of electric vehicles (EVs) has led to increased global expectations that the application of this technology may result in the reduction of CO₂ emissions through the replacement of conventional petrol vehicles and ensure the flexibility of power systems such as batteries. In this paper, we propose a residential demand response (DR) evaluation model that considers the degradation mechanism of the EV battery and examines the effective battery operation. We adopted the already-proposed NiMnCo battery degradation model to develop an EV DR evaluation model. In this model, the battery operation is optimized to minimize the electricity and degradation costs affected by ambient temperature, battery state of charge (SOC), and depth of discharge. In this study, we evaluated the impact of the relevant parameters on the economics of the DR of EV batteries for 10 all-electric detached houses with photovoltaic system assuming multiple EV driving patterns and battery (dis)charging constraints. The results indicated that the degradation costs are greatly affected by the SOC condition. If a low SOC can be managed with a DR strategy, the total cost can be reduced. This is because the sum of the reduction of purchased cost from the utility and calendar degradation costs are higher than the increase of the cycle degradation cost. In addition, an analysis was conducted considering different driving patterns. The results showed that the cost reduction was highest when a driving pattern was employed in which the mileage was low and the staying at home time was large. When degradation costs are included, the value of optimized charging and discharging operations is more apparent than when degradation costs are not considered. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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17 pages, 2721 KiB

Open AccessArticle

Game-Theory Based V2G Coordination Strategy for Providing Ramping Flexibility in Power Systems

by Jin Zhang, Liang Che, Lei Wang and Udaya K. Madawala

Energies 2020, 13(19), 5008; https://doi.org/10.3390/en13195008 - 23 Sep 2020

Cited by 11 | Viewed by 2997

Abstract

Large-scale integration of renewable generation into power systems invariably affects the system ramping capability. However, the vehicle-to-grid (V2G) concept that allows for using electric vehicles (EVs) as energy storages with the capability of bidirectional energy transfer between the EVs and the grid, can [...] Read more.

Large-scale integration of renewable generation into power systems invariably affects the system ramping capability. However, the vehicle-to-grid (V2G) concept that allows for using electric vehicles (EVs) as energy storages with the capability of bidirectional energy transfer between the EVs and the grid, can be employed to mitigate the above adverse effect. This paper proposes a game-theory-based V2G coordination strategy that uses EV clusters to improve ramping flexibility in power systems. In the proposed strategy, the V2G concept, representing the interactions between the distribution system operator (DSO) and EV clusters, is formulated as a Stackelberg game. The DSO acts as a leader who decides the charging prices for the buses to which the EV clusters are connected, while the EV clusters simply serve as followers, scheduling their own charging and discharging. This bi-level model is further reduced to a single-level, mixed-integer second-order cone programming (MISOCP) problem based on the Karush-Kuhn-Tucker (KKT) conditions, the strong duality theorem and second-order cone (SOC) relaxation. The performance of the proposed V2G coordination strategy on a modified IEEE 33-bus system connecting EV clusters and PV generations is investigated through simulations, and the results demonstrate that the largest ramp of the system can be reduced by up to 39% when EV clusters are providing flexibility, while the EV clusters can also have greatly reduced charging costs. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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13 pages, 4136 KiB

Open AccessEditor’s ChoiceArticle

An Electric Vehicle Charge Scheduling Approach Suited to Local and Supplying Distribution Transformers

by Teguh Kurniawan, Craig A. Baguley, Udaya K. Madawala, Suwarno, Nanang Hariyanto and Yuana Adianto

Energies 2020, 13(13), 3486; https://doi.org/10.3390/en13133486 - 6 Jul 2020

Cited by 7 | Viewed by 3353

Abstract

Distribution networks with high electric vehicle (EV) penetration levels can experience transformer overloading and voltage instability issues. A charge scheduling approach is proposed to mitigate against these issues that suits smart home settings in residential areas. It comprises measurement systems located at distribution [...] Read more.

Distribution networks with high electric vehicle (EV) penetration levels can experience transformer overloading and voltage instability issues. A charge scheduling approach is proposed to mitigate against these issues that suits smart home settings in residential areas. It comprises measurement systems located at distribution transformers that communicate directly with fuzzy logic controller (FLC) systems embedded within EV supply equipment (EVSE). This realizes a reduction in data processing requirements compared to more centralized control approaches, which is advantageous for distribution networks with large numbers of transformers and EV scheduling requests. A case study employing the proposed approach is presented. Realistic driver behavior patterns, EV types, and multivariate probabilistic modeling were used to estimate EV charging demands, daily travel mileage, and plug-in times. A Monte Carlo simulation approach was developed to obtain EV charging loads. The effectiveness of mitigation in terms of reducing distribution transformer peak load levels and losses, as well as improving voltage stability is demonstrated for a distribution network in Jakarta, Indonesia. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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16 pages, 4386 KiB

Open AccessArticle

Plug-In Electric Bus Depot Charging with PV and ESS and Their Impact on LV Feeder

by Syed Muhammad Arif, Tek Tjing Lie, Boon Chong Seet, Syed Muhammad Ahsan and Hassan Abbas Khan

Energies 2020, 13(9), 2139; https://doi.org/10.3390/en13092139 - 29 Apr 2020

Cited by 39 | Viewed by 4979

Abstract

Plug-in electric buses (PEBs) are a promising alternative to conventional buses to provide a sustainable, economical, and efficient mode of transportation. However, electrification of public transportation leads to a phenomenon of peak load that impacts the stability of low voltage (LV) feeders. In [...] Read more.

Plug-in electric buses (PEBs) are a promising alternative to conventional buses to provide a sustainable, economical, and efficient mode of transportation. However, electrification of public transportation leads to a phenomenon of peak load that impacts the stability of low voltage (LV) feeders. In this context, the effective integration of an energy storage system (ESS) and photovoltaic (PV) in a bus depot charging ecosystem can lead to i) peak load reduction and ii) charging cost reduction with low carbon emission. Therefore, a limited PEB charge scheduling algorithm is proposed for: i) bus depot operator (BDO) profit maximization and ii) grid stability enhancement considering the constraints of PEB charging and grids. A mixed integer linear programming (MILP) model for BDO profit maximization has been formulated and analyzed using IBM ILOG studio with CPLEX solver. Simulation has been performed for SkyBus electric fleet using real-world data such as actual bus arrival and departure schedules under diverse traffic, number of passengers, trip duration, daily load profile, solar radiation profile, and benchmark storage price. The charging impact of PEBs was tested on one of the distribution feeders in Auckland, New Zealand. The BDO generates revenue by performing energy trading among PV, ESS, PEBs, and buildings after incorporating capital investment, operation and maintenance, and depreciation costs. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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26 pages, 3733 KiB

Open AccessArticle

Multi-Agent Reinforcement Learning Approach for Residential Microgrid Energy Scheduling

by Xiaohan Fang, Jinkuan Wang, Guanru Song, Yinghua Han, Qiang Zhao and Zhiao Cao

Energies 2020, 13(1), 123; https://doi.org/10.3390/en13010123 - 25 Dec 2019

Cited by 43 | Viewed by 6363

Abstract

Residential microgrid is widely considered as a new paradigm of the home energy management system. The complexity of Microgrid Energy Scheduling (MES) is increasing with the integration of Electric Vehicles (EVs) and Renewable Generations (RGs). Moreover, it is challenging to determine optimal scheduling [...] Read more.

Residential microgrid is widely considered as a new paradigm of the home energy management system. The complexity of Microgrid Energy Scheduling (MES) is increasing with the integration of Electric Vehicles (EVs) and Renewable Generations (RGs). Moreover, it is challenging to determine optimal scheduling strategies to guarantee the efficiency of the microgrid market and to balance all market participants’ benefits. In this paper, a Multi-Agent Reinforcement Learning (MARL) approach for residential MES is proposed to promote the autonomy and fairness of microgrid market operation. First, a multi-agent based residential microgrid model including Vehicle-to-Grid (V2G) and RGs is constructed and an auction-based microgrid market is built. Then, distinguish from Single-Agent Reinforcement Learning (SARL), MARL can achieve distributed autonomous learning for each agent and realize the equilibrium of all agents’ benefits, therefore, we formulate an equilibrium-based MARL framework according to each participant’ market orientation. Finally, to guarantee the fairness and privacy of the MARL process, we proposed an improved optimal Equilibrium Selection-MARL (ES-MARL) algorithm based on two mechanisms, private negotiation and maximum average reward. Simulation results demonstrate the overall performance and efficiency of proposed MARL are superior to that of SARL. Besides, it is verified that the improved ES-MARL can get higher average profit to balance all agents. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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23 pages, 9630 KiB

Open AccessArticle

Investigating the Impact of E-Mobility on the Electrical Power Grid Using a Simplified Grid Modelling Approach

by Julia Vopava, Christian Koczwara, Anna Traupmann and Thomas Kienberger

Energies 2020, 13(1), 39; https://doi.org/10.3390/en13010039 - 19 Dec 2019

Cited by 12 | Viewed by 2735

Abstract

To achieve climate goals, it is necessary to decarbonise the transport sector, which requires an immediate changeover to alternative power sources (e.g., battery powered vehicles). This change will lead to an increase in the demand for electrical energy, which will cause additional stress [...] Read more.

To achieve climate goals, it is necessary to decarbonise the transport sector, which requires an immediate changeover to alternative power sources (e.g., battery powered vehicles). This change will lead to an increase in the demand for electrical energy, which will cause additional stress on power grids. It is therefore necessary to evaluate energy and power requirements of a future society using e-mobility. Therefore, we present a new approach to investigate the influence of increasing e-mobility on a distribution grid level. This includes the development of a power grid model based on a cellular approach, reducing computation efforts, and allowing time and spatially resolved grid stress analysis based on different load and renewable energy source scenarios. The results show that by using the simplified grid model at least seven times, more scenarios can be calculated in the same time. In addition, we demonstrate the capability of this novel approach by analysing the influence of different penetrations of e-mobility on the grid load using a case study, which is calculated using synthetic charging load profiles based on a real-life mobility data. The results from this case study show an increase on line utilisations with increasing e-mobility and the influence of producers at the same connection point as e-mobility. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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16 pages, 1262 KiB

Open AccessFeature PaperArticle

Evaluation of Optimization-Based EV Charging Scheduling with Load Limit in a Realistic Scenario

by Steffen Limmer

Energies 2019, 12(24), 4730; https://doi.org/10.3390/en12244730 - 11 Dec 2019

Cited by 5 | Viewed by 2136

Abstract

In the literature, optimization-based approaches are frequently proposed for the control of electric vehicle charging. However, they are usually evaluated under simplifying assumptions and are not compared to more simple approaches. The present work compares optimization-based approaches with rule-based ones in a simple [...] Read more.

In the literature, optimization-based approaches are frequently proposed for the control of electric vehicle charging. However, they are usually evaluated under simplifying assumptions and are not compared to more simple approaches. The present work compares optimization-based approaches with rule-based ones in a simple but realistic scenario, in which a certain limit for the total load has to be satisfied. The scenario is based on the situation at an office building in Germany. In simulation experiments, different control approaches are evaluated not only in terms of pure performance but also from an economic perspective. The results indicate that, although the optimization-based approaches outperform the rule-based approaches, they are not always the right choice from an economic point of view. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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Review

Jump to: Research

13 pages, 1084 KiB

Open AccessReview

An Insight into Practical Solutions for Electric Vehicle Charging in Smart Grid

by Sara Deilami and S. M. Muyeen

Energies 2020, 13(7), 1545; https://doi.org/10.3390/en13071545 - 26 Mar 2020

Cited by 35 | Viewed by 5577

Abstract

The electrification of transportation has been developed to support energy efficiency and CO₂ reduction. As a result, electric vehicles (EVs) have become more popular in the current transport system to create more efficient energy. In recent years, this increase in EVs as [...] Read more.

The electrification of transportation has been developed to support energy efficiency and CO₂ reduction. As a result, electric vehicles (EVs) have become more popular in the current transport system to create more efficient energy. In recent years, this increase in EVs as well as renewable energy resources (RERs) has led to a major issue for power system networks. This paper studies electrical vehicles (EVs) and their applications in the smart grid and provides practical solutions for EV charging strategies in a smart power system to overcome the issues associated with large-scale EV penetrations. The research first reviews the EV battery infrastructure and charging strategies and introduces the main impacts of uncontrolled charging on the power grid. Then, it provides a practical overview of the existing and future solutions to manage the large-scale integration of EVs into the network. The simulation results for two controlled strategies of maximum sensitivity selection (MSS) and genetic algorithm (GA) optimization are presented and reviewed. A comparative analysis was performed to prove the application and validity of the solution approaches. This also helps researchers with the application of the optimization approaches on EV charging strategies. These two algorithms were implemented on a modified IEEE 23 kV medium voltage distribution system with switched shunt capacitors (SSCs) and a low voltage residential network, including EVs and nonlinear EV battery chargers. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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