Electric vehicles in Smart Grids: Performance considerations

Distributed power system is the basic architecture of current power systems and demands close cooperation among the generation, transmission and distribution systems. Excessive greenhouse gas emissions over the last decade have driven a move to a more sustainable energy system. This has involved integrating renewable energy sources like wind and solar power into the distributed generation system. Renewable sources offer more opportunities for end users to participate in the power delivery system and to make this distribution system even more efficient, the novel Smart Grid concept has emerged. A Smart Grid: offers a two-way communication between the source and the load; integrates renewable sources into the generation system; and provides reliability and sustainability in the entire power system from generation through to ultimate power consumption. Unreliability in continuous production poses challenges for deploying renewable sources in a real-time power delivery system. Different storage options could address this unreliability issue, but they consume electrical energy and create signifcant costs and carbon emissions. An alternative is using electric vehicles and plug-in electric vehicles, with two-way power transfer capability (Grid-to-Vehicle and Vehicle-to-Grid), as temporary distributed energy storage devices. A perfect fit can be charging the vehicle batteries from the renewable sources and discharging the batteries when the grid needs them the most. This will substantially reduce carbon emissions from both the energy and the transportation sector while enhancing the reliability of using renewables. However, participation of these vehicles into the grid discharge program is understandably limited by the concerns of vehicle owners over the battery lifetime and revenue outcomes. A major challenge is to find ways to make vehicle integration more effective and economic for both the vehicle owners and the utility grid. This research addresses problems such as how to increase the average lifetime of vehicles while discharging to the grid; how to make this two-way power transfer economically viable; how to increase the vehicle participation rate; and how to make the whole system more reliable and sustainable. Different methods and techniques are investigated to successfully integrate the electric vehicles into the power system. This research also investigates the economic benefits of using the vehicle batteries in their second life as energy storage units thus reducing storage energy costs for the grid operators, and creating revenue for the vehicle owners

Challenges and Opportunities for Second-life Batteries: A Review of Key Technologies and Economy

Due to the increasing volume of Electric Vehicles in automotive markets and the limited lifetime of onboard lithium-ion batteries (LIBs), the large-scale retirement of LIBs is imminent. The battery packs retired from Electric Vehicles still own 70%-80% of the initial capacity, thus having the potential to be utilized in scenarios with lower energy and power requirements to maximize the value of LIBs. However, spent batteries are commonly less reliable than fresh batteries due to their degraded performance, thereby necessitating a comprehensive assessment from safety and economic perspectives before further utilization. To this end, this paper reviews the key technological and economic aspects of second-life batteries (SLBs). Firstly, we introduce various degradation models for first-life batteries and identify an opportunity to combine physics-based theories with data-driven methods to establish explainable models with physical laws that can be generalized. However, degradation models specifically tailored to SLBs are currently absent. Therefore, we analyze the applicability of existing battery degradation models developed for first-life batteries in SLB applications. Secondly, we investigate fast screening and regrouping techniques and discuss the regrouping standards for the first time to guide the classification procedure and enhance the performance and safety of SLBs. Thirdly, we scrutinize the economic analysis of SLBs and summarize the potentially profitable applications. Finally, we comprehensively examine and compare power electronics technologies that can substantially improve the performance of SLBs, including high-efficiency energy transformation technologies, active equalization technologies, and technologies to improve reliability and safety

Electric Vehicle (EV)-Assisted Demand-Side Management in Smart Grid

While relieving the dependency on diminishing fossil fuels, Electric Vehicles (EVs) provide a promising opportunity to realise an eco-friendly and cost-effective means of transportation. However, the enormous electricity demand imposed by the wide-scale deployment of EVs can put power infrastructure under critical strain, potentially impacting the efficiency, resilience, and safety of the electric power supply. Interestingly, EVs are deferrable loads with flexible charging requirements, making them an ideal prospect for the optimisation of consumer demand for energy, referred to as demand-side management. Furthermore, with the recent introduction of Vehicle-to-Grid (V2G) technology, EVs are now able to act as residential battery systems, enabling EV customers to store energy and use them as backup power for homes or deliver back to the grid when required. Hence, this thesis studies Electric Vehicle (EV)-assisted demand-side management strategies to manage peak electricity demand, with the long-term objective of transforming to a fully EV-based transportation system without requiring major upgrades in existing grid infrastructure. Specifically, we look at ways to optimise residential EV charging and discharging for smart grid, while addressing numerous requirements from EV customer's perspective and power system's perspective. First, we develop an EV charge scheduling algorithm with the objective of tracking an arbitrary power profile. The design of the algorithm is inspired by water-filling theory in communication systems design, and the algorithm is applied to schedule EV charging following a day-ahead renewable power generation profile. Then we extend that algorithm by incorporating V2G operation to shape the load curve in residential communities via valley-filling and peak-shaving. In the proposed EV charge-discharge algorithm, EVs are distributedly coordinated by implementing a non-cooperative game. Our numerical simulation results demonstrate that the proposed algorithm is effective in flattening the load curve while satisfying all heterogeneous charge requirements across EVs. Next, we propose an algorithm for network-aware EV charging and discharging, with an emphasis on both EV customer economics and distribution network aspects. The core of the algorithm is a Quadratic Program (QP) that is formulated to minimise the operational costs accrued to EV customers while maintaining distribution feeder nodal voltage magnitudes within prescribed thresholds. By means of a receding horizon control approach, the algorithm implements the respective QP-based EV charge-discharge control sequences in near-real-time. Our simulation results demonstrate that the proposed algorithm offers significant reductions in operational costs associated with EV charging and discharging, while also mitigating under-voltage and over-voltage conditions arising from peak power flows and reverse power flows in the distribution network. Moreover, the proposed algorithm is shown to be robust to non-deterministic EV arrivals and departures. While the previous algorithm ensures a stable voltage profile across the entire distribution feeder, it is limited to balanced power distribution networks. Therefore, we next extend that algorithm to facilitate EV charging and discharging in unbalanced distribution networks. The proposed algorithm also supports distributed EV charging and discharging coordination, where EVs determine their charge-discharge profiles in parallel, using an Alternating Direction Method of Multipliers (ADMM)-based approach driven by peer-to-peer EV communication. Our simulation results confirm that the proposed distributed algorithm is computationally efficient when compared to its centralised counterpart. Moreover, the proposed algorithm is shown to be successful in terms of correcting any voltage violations stemming from non-EV load, as well as, satisfying all EV charge requirements without causing any voltage violations

Impact of Second-Life Batteries on Enhancing the Integration of Renewable Energy Resources

The current distribution systems are typically not designed to accommodate a high level of renewable sources. Customer impact assessment studies are usually required by the distribution utility prior to the connection of DG. In these studies, the impacts of Distributed Generator (DG) on the system voltage profile, reverse power flow, short circuit level, and the system voltage unbalance are evaluated. If the DG failed to fulfill the distribution system technical requirement, the DG project application might be rejected. In some cases, the DG capacity may be reduced to fulfill the technical constraints. In other cases, the renewable based DG power may be curtailed (especially at peak generation). The reduction in DG capacity, as well as the DG active power curtailment, will badly affect the DG project investment. In order to eliminate the DG active power curtailment, the investor may connect a battery at the same point of the renewable DG. The battery can dispatch the DG generation; therefore, the peak DG power, that causes the violation to the system technical constraints, is shaved. However, the high capital cost of the batteries may negatively affect the investor profit. In such cases, the usage of second life (SL) batteries represents the most useful solution. SL batteries have significantly cheaper capital costs compared to new batteries. Thereby, the major driver for using SL batteries is the possibility of reducing costs and maximizing the DG investment by avoiding the utilization of new Li-ion batteries. The main aim of this research is to use batteries, which have lost part of their original performance during their first life, with the distribution system applications. The general objective is to utilize the SL batteries for smoothing the photovoltaic based DG power to increase the DG penetration while fulfilling the utility technical constraints. Another objective is to use the SL batteries connected at the same bus of the DG to maximize the DG project investment. Towards the execution of the proposed research work, some ancillary studies are presented in chapter (3); the results of these studies are used to solve the main problems under study presented in chapter (4). The studies presented in Chapter (3) comprises a probabilistic model for the PV DG, a long-term forecasting technique for the system load, a load flow study to determine the maximum allowable injected DG power, and an economic assessment study to determine the best PV DG capacity that increases the net present value of the profit of the PV DG project. The results of the aforementioned studies are integrated with the main problems under study that were formulated and solved in Chapter (4). Two main objectives were presented in this chapter; i.e. the first objective is to obtain the optimal size of the SL batteries that achieve zero curtailment while minimizing the battery cost, the second objective is to obtain the optimal schedule of the batteries that maximize the net present value of the profit. The results obtained show that the SL batteries are adequate for the application, and they have superiority over the brand-new batteries in terms of cost. SLB batteries give a chance to the investor to purchase batteries at low prices at later years of the project rather than purchasing all the required batteries at the beginning of the project. Thus, the SL batteries offer a competitive solution for the cost problems associated with the battery integration with the distribution systems

Impact of electric vehicles on smart grid and future predictions : a survey

Mobility has modernized urban areas using an efficient transportation system. However, mobility demand growth has accelerated the expansion of conventional transportation, which significantly contributes to pollution. The need of Green transportation results in the eminence of electric vehicles (EVs). Besides, green mobility minimizes pollution from transportation systems and conventional power sources when EVs are optimally integrated into the utility grid. Thus, this study assesses different significant optimum possibilities of grid-connected EVs. A review of the critical impacts of grid-tied EVs is presented. Vehicle to the grid (V2G) is the future of electric cars. This uses a bidirectional power flow of the EV’s battery charging to either charge the car or sustain the utility grid. The V2G is highly affected by diverse loading conditions that challenge the network’s acceptable voltage and optimal power-sharing within the electrical network. It is observed that the V2G perspective is based on the 5Ds (decentralisation, de-carbonization, digitalization, deregulation, and democratization) vision to overcome the overall shortcomings in the modern power grid. The 5Ds vision of V2G implementation sustains different stakeholders working on the future of electric cars. Thus, this research is a stronger foundation for the new perspective and vision of V2G development and applications.https://www.tandfonline.com/journals/tjms20hj2024Electrical, Electronic and Computer EngineeringSDG-07:Affordable and clean energ

A decision-making model for retired Li-ion batteries

The growth of electric vehicles (EVs) has raised concerns about the disposition of their batteries once they reach their end of life. Currently, recycling is regarded as the potential solution for retired Li-ion batteries (LIBs). However, these LIBs still retain around 80% of their original capacity, which can be repurposed for other energy storage system (ESS) applications in their "second life" before recycling. Yet, there is no guidance for deciding whether to reuse or recycle them. Here, we propose developing a decision-making model that evaluates retired batteries from both technical and economic perspectives. We develop data-driven models and combine them with an equivalent circuit model (ECM) to build module-level aging models. Simulations show that limiting the State of Charge (SOC) operating range and charge current in second life applications can extend the lifetime of LIBs. Upon when and how to use the battery in second life, the simulated lifetime is between 1-6 years..

Evaluating the Effect of Electric Vehicle Parking Lots in Transmission-Constrained AC Unit Commitment under a Hybrid IGDT-Stochastic Approach

Power network operators have recently faced new challenges due to an increase in the penetration of non-dispatchable renewable energy sources in power grids. Incorporating emerging flexible resources like electric vehicle parking lots (EVPLs) and demand response programs (DRPs) into power systems, could be a good solution to deal with inherent uncertainties imposed by these resources to the power grid. EVPLs can improve power system operating conditions by active and reactive power injection capabilities. The participation of consumers in DRPs can also improve energy consumption management by decreasing or shifting loads to other periods. This paper proposes a hybrid information gap decision theory (IGDT)- stochastic method to solve a transmission-constrained AC unit commitment model integrated with electric vehicle (EV), incentive-based DRP, and wind energy. The behavioural uncertainty related to EV owners is modelled using a scenario-based method. Additionally, an IGDT method is applied to manage wind energy uncertainty under a two-level optimization model. Verification of the proposed model is done under several case studies. Based on the results achieved, the proposed risk-based hybrid model allows the operator to differentiate between the risk level of existing uncertainties and apply a high-flexibility decision-making model to deal with such difficulties. Additionally, the role of the aforementioned flexible resources in the reduction of power system running costs and wind power uncertainty handling are evaluated. Numerical results confirm a 3.7% reduction in the daily operating costs as a consequence of coordinated scheduling of EVPL and DRP. Moreover, Taking advantage of reactive power injection of EVPL provides more cost saving