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The unpredictability of battery degradation behavior is a challenging issue impeding the development of battery applications, due to the complexity of the degradation and the limitation of state measurement methods. Nowadays, with accessible battery aging datasets and machine learning algorithms, there are opportunities for data-driven battery health prognosis. However, most of the previous work is restricted in the scope of full-discharge capacity records extrapolation, which has insufficient prospects in real-life applications. In this work, we propose using partial discharge information for degradation estimation and prediction. Our Gaussian process regression model achieves good performance by limited partial discharge information without requirements of feature selection. The accurate battery health prognosis in 300 cycles can be carried out by one partial-discharge cycle at any degradation stage. The capacity estimation gives around 1 % root mean square error (RMSE) when using 30 % information on the discharge process. As full-cycle discharge is not required, the proposed model can diagnose the battery state of health (SOH) with a limited portion of battery operation information extracted during the discharge process and reduce the effort of capacity tests. Further development of this method brings opportunities for battery state evaluation and prediction in real applications with better applicability and accuracy.

Battery energy storage system (BESS) has been applied extensively to provide grid services such as frequency regulation, voltage support, energy arbitrage, etc. Advanced control and optimization algorithms are implemented to meet operational requirements and to preserve battery lifetime. While fundamental research has improved the understanding of battery characteristics, a lack of insights into BESS applications and low data transparency limit the understanding of battery usage. This work reviews recent advancements in BESS grid services, with a focus on use cases and synergies with other components. After reviewing the parameters to describe the hardware features, a quantitative framework is proposed to assess the usage pattern of BESS applications in long term, which is further implemented for an overview of the BESS duty profiles in grid applications. Specifically, the frequency regulation service is emphasized, and the cross-cutting integrations with energy storage, energy production, and energy consumption components are summarized. Additionally, an elaborate survey of BESS grid applications in the recent 10 years is used to evaluate the advancement of the state of charge, state of health, and technical and economic research. With a comprehensive review of the BESS grid application and integration, this work introduces a new perspective on analyzing the duty cycle of BESS applications, which enhances communication of BESS operations and connects with technical and economic operations, including battery usage optimization and degradation research. It provides an overview of the BESS use cases in grid applications and paves the way for further application-oriented battery research.

Battery energy storage systems (BESSs) have the potential to become providers of frequency regulation services in future energy systems. In this case, the reliable operation of BESS has a significant impact on system stability. One of the tools that ensures the secure BESS operation is applying a digital twin to forecast the BESS state of charge (SOC). It allows to predict BESS behavior and identify potential failures or cyberattacks in BESS. In this article, we compare multiple data-driven approaches to forecast the SOC of a BESS based on realistic dataset and real battery operation. Recurrent neural networks, e.g., feedforward neural network, gated recurrent unit, long short-term memory, support vector regression, random forest, and AdaBoost methods are applied to evaluate each method's performance. We compare the methods based on the maximum and average forecast errors, the required computational capacity, as well as expected training speed. To validate the results, in addition to the data gathered from simulations, we used experimental setup with a BESS of 79 kWh providing containment reserve for normal operation, which is a BESS service with a high economical potential in Nordic Region. Furthermore, we provide recommendations for the methods that are suitable to be applied for modeling the digital twin of a utility-scale battery digital twin.

Made available in DSpace on 2021-06-25T10:18:28Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-05-01 The deployment of battery energy storage systems (BESS) is rapidly increasing as a prominent option to support future renewable-based energy systems. However, despite its benefits from a technical perspective, there are still challenges related to its economic viability. On the other hand, sizing BESS considering only their economic viability can be impractical because financial objectives could be in conflict with other aspects, such as battery degradation and grid impact. This article proposes a multi-objective approach to determine the optimal size of BESS providing stackable services, such as frequency regulation and peak shaving. The proposed optimization method comprises financial and technical aspects represented by the payback period, battery life span, and grid impact. Given a set of market rules, a cost-benefit function, a regulation signal, consumption profiles and grid data, an enumerative approach is adopted to provide a set of Pareto optimal solutions. The performance of the proposed method is validated using the regulation market structure from PJM interconnection. Furthermore, a real 240-node distribution grid is used to assess the grid impact via OpenDSS. Simulations demonstrate that the proposed approach is a flexible and practical decision-making tool that investors can exploit when designing new BESS. Department of Energy Systems School of Electrical and Computing of Engineering University of Campinas Department of Electrical Engineering Center for Electric and Energy Technical University of Denmark School of Energy Engineering São Paulo State University (UNESP) School of Energy Engineering São Paulo State University (UNESP)

Electric vehicles (EVs) appear to offer a promising solution to support sustainable transportation and the reduction of CO2 emissions in the metropolitan areas. To satisfy the EV load demand of the new EV models with larger battery capacities, public direct-current fast-charging stations (DCFCSs) are essential to recharge EVs rapidly. A stochastic planning method of the DCFCSs is presented considering user behaviour and the probabilistic driving patterns in order to predict EVs charging demand. According to the stochastic method, a coordinated charging demand and storage charging demand are proposed with the objective of minimising peak load from EVs and charging-infrastructure costs. The proposed planning method can prevent additional grid reinforcement costs due to EV demand during the peak hours. In the coordinated charging demand, the peak load from EVs is managed by controlling the DCFCSs. Instead, in the battery energy storage (BES) charging demand, an optimal BES is proposed as an alternative solution to reduce the peak demand of EVs as well as DCFCSs operational costs. Finally, an economic analysis is carried out to evaluate the technical and economic aspects related to DCFCSs, the BES lifecycle costs as well as the financial performance of BES costs versus grid reinforcement costs.

Battery degradation is the main uncertainty that hedges the development of battery projects. In this work, we build a data-driven battery degradation model assessing the impact of the complex state of charge (SOC) operation condition. Both cycle life and calendar life are incorporated, based on the available lab testing data of battery cells. Various degradation modeling functions are compared to acquire the best fitting results under different depths of discharge (DOD) ranges calculated by rainflow counting algorithm. The statistical relation between shallow cycles and calendar time is used to address the calendar degradation in the cycling scope. A battery frequency regulation service case study is carried out based on a one-year frequency record in the Nordic synchronous area. Our work bridges the battery cell testing datasets to the battery degradation modeling in grid applications and proposes a new perspective to address the calendar life by the analysis of the shallow cycles for the state of health (SOH) estimation, which improves applicability and accuracy.

Battery energy storage systems (BESSs) are gaining potential recognition in renewable-based power systems. To maintain the stability of such systems, BESSs units are being deployed for the provision of ancillary services (ASs). For BESS owners, it is vital to assess the business value of providing ASs to engage in a profitable trade. However, studies so far have mainly focused on the operational control of BESS units in ancillary services markets (ASMs) while ignoring investigations from a business viewpoint. Therefore, in this paper, we analyse the BESS-based provision of Nordic ASs from a BESS-business perspective. To this aim, we identify the profitable bidding hours for the BESS units by investigating hourly patterns in the market prices of the past six years. We also analyse the monthly and yearly trends in historic price datasets of ASs to help BESS owners develop long-term business plans. Moreover, for the BESS owners to choose between different markets, we investigate the revenue streams associated with each ASs and determine the yearly income from their availability and capacity payments. Our findings imply that BESS business viability in the Nordic ASMs can be increased by stacking ASs based on their availability payments, energy content, and activation requirements.

Made available in DSpace on 2020-12-12T02:25:45Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-12-01 Trend-setting countries have promoted or even employed an increased number of electric vehicles (EVs) and other distributed energy resources (DERs) in their power systems. This development has triggered new and increasing challenges in the distribution system planning and operation, whereby the distribution systems must adapt to the increased share of DERs. However, EVs may also offer new opportunities and can be used to support the grid by providing several local and global power- and energy-based services. This paper presents a review and classification of the services potentially available from EVs for distribution systems, referred to as EV distribution system services (EV-DSS). A detailed description of recent services and approaches is given, and an assessment of the maturity of EV-DSS is provided. Moreover, challenges and prospects for future research are identified, considering key topics, such as the design of the market framework, economic assessment, battery degradation, and the impacts of the transmission system operator service provision by EVs on distribution networks. Thus, this paper offers a tool for stakeholders concerning services available from EVs and provides a broad literature framework that can be used as a base for further investigations. It is aligned with the current requirements to move toward the realistic implementations of EV-DSS. Electrical Engineering Department UNESP-São Paulo State University Electrical Engineering Department UNESP-São Paulo State University

Battery energy storage system (BESS) is an important component of a modern power system since it allows seamless integration of renewable energy sources (RES) into the grid. A BESS is vulnerable to various cyber threats that may influence its proper operation, which in turn impacts negatively the BESS and the electric grid. The potential failure of a BESS can cause economic issues and physical damage to its components. To ensure cyber-secure and reliable BESS operation in grid-connected or islanded modes of the BESS operation, a cyber-defense strategy is needed. However, a comprehensive review on the requirements for the BESS design as well as the attack detection and mitigation methods is lacking. In this paper, we review state-of-the-art attack detection and mitigation methods for various BESS applications focusing on machine learning (ML) and artificial intelligence (AI)-based methods. In addition, the state-of-the-art methods for designing and operating a cyber-secure BESS are investigated. Based on the literature review, we identified gaps in the current research, defined the possible cyberattacks against the BESS that have not been considered before, and suggested the potential approaches to detect them.

Battery energy storage systems (BESSs) are gaining potential recognition in modern power systems. They enable higher renewable shares in power networks by overcoming issues introduced by the intermittent nature of renewable resources. BESSs also provide various grid services such as frequency regulation, voltage support, energy management, and black start. Choosing an appropriate BESS location plays a key role in maximizing benefits from its services. This paper aims at investigating BESS placement for providing grid services at the point of installation. The previous studies extended in this direction have not considered the requirements of a real project under which BESS is being deployed and have mainly proposed solutions for standard IEEE bus systems. Also, the focus has not been on providing ancillary services using BESS, but mainly on loss minimization. This paper, on the other hand, presents a case study on the BESS placement problem by investigating various potential locations in Bornholm Island for fulfilling the objectives of a BESS-related industrial project, namely BOSS. This is achieved by considering factors like stackability of BESS-services, integration of large-scale renewable resources, and viability of business models.

The promotion of electric vehicles (EVs), triggered by environmental concerns, can also increase the flexibility of power systems through ancillary services, such as frequency regulation among others. Nevertheless, EV penetration has increased the concern regarding voltage drops in distribution grids. This concern has motivated researchers to examine EV reactive power provision to mitigate such problems. This work proposes a local market perspective to promote EV reactive power provision, enabling distribution system operators to control the voltage level using cost-effective solutions. The authors propose the extension of a centralised control framework that schedules EV frequency regulation to optimise the reactive power provided by the same EVs. Additionally, extra power losses in chargers while EVs provide reactive power were investigated, and the associated cost in the economic evaluations were considered. A test-case with the IEEE 33-node distribution grid is used to assess the market potential of EV reactive power provision. This new service extends EV penetration in a cost-efficient way without causing voltage problems. The simulation concludes that it is economically feasible to use EVs for reactive local provision with efficient chargers. These outcomes sustain the potential of promoting such new EV services through a proper market in distribution grids.

Battery energy storage system (BESS) is key for future renewable energy systems, as it can provide various grid support functionalities, facilitate the participation of renewable energy sources in electricity markets, and increase grid stability. However, battery degradation is a major factor hindering the BESS implementation for grid applications. Battery state of health (SOH) is a key performance indicator of the BESS, and data-driven models powered by machine learning techniques are among the most promising solutions for the BESS degradation estimation. In this paper, a novel taxonomy of BESS services is proposed based on battery usage. Besides, the data-driven techniques for battery SOH modeling and data-driven SOH estimation applications for BESS providing grid services are reviewed and discussed. Further, a comprehensive discussion is presented regarding the challenges in the area of data-driven SOH modeling methods for the BESS providing grid services in practical applications.

Battery energy storage systems (BESSs) are gaining increasing importance in the low carbon transformation of power systems. Their deployment in the power grid, however, is currently challenged by the economic viability of BESS projects. To drive the growth of the BESS industry, private, commercial, and institutional investments in large-scale BESS projects are needed. For financiers and investors, choosing an appropriate BESS installation location is a crucial task that requires important considerations. However, so far, studies targeting the BESS placement problem have mainly focused on minimizing operational losses, solving power quality issues, and improving the voltage profile of the system. Implementing such approaches only considers the operational feasibility of BESS at the installation site while ignoring its business feasibility. Therefore, in this paper, we approach the BESS placement problem from a business viewpoint by conducting a stage-level investigation of BESS projects. First, we identify the factors impacting the business feasibility of placement decisions in projects’ construction, connection, operation, and disposal stages and propose cost and time effective measures for making them business friendly. We investigate several factors such as profitability of grid services, integrability of renewable resources, affordability of connection charges, and the usability of BESS capacity. Second, we investigate the business potential of placing BESSs in different grid-levels of the power system and examine BESS connection procedures at those levels. Third, we implement the proposed approach for installing a BESS in the Danish island of Bornholm, for which, we investigate multiple locations of the Bornholm power system.

Environmental concerns and urban air pollution are major drivers for the transition from combustion engines to electric vehicles. To support a large-scale adoption of electric vehicles an efficient charging infrastructure roll-out is required. However, the optimal planning of charging stations is a non-trivial task, as it requires coordination between planning activities in the transportation and the power distribution network. Historically, the modeling of these two networks has been approached from different research areas and with the use of different methodologies. As a result, few papers embrace the combined problem to its full extent and the literature is highly scattered and represents different model perspectives and the targeting of many different objectives. In the paper, we present a systematic review of the literature that considers the combined investigation of transportation and distribution networks, with a focus on objectives, methodology and scope. It allows us to describe the current state of the art, to highlight research gaps and to propose directions for future work of the research community. The identified research gaps include, but are not limited to: 1) a general lack of integrated modeling approaches, 2) the need for increasingly detailed modeling of charging demand that accounts for randomness and variability in space and time rather than averages to support power grid planning, 3) the need to consider a mix of different types of charging options rather than only fast charging and 4) the need to shift from standard test networks and theoretical based planning approaches to large-scale and real-world case studies.

Battery energy storage systems (BESSs) have gained potential recognition for the grid services they can offer to power systems. Choosing an appropriate BESS location plays a key role in maximizing benefits from those services. This paper aims at analyzing the significance of site selection for placement of BESS in a power grid by providing a techno-economic evaluation with respect to specific grid services it can deliver, and benefits that can be extracted from those services in the form of revenue streams. The focus of the previous studies extended in this direction has been limited to the optimization techniques and software tools being used for BESS siting. However, questions around the benefits that stakeholders can derive from BESSs located at different levels of power network still remain unanswered. This paper handles those questions by drawing a link between technical considerations essential for BESS placement and their economicevaluations.

With the rapid development of energy storage systems (ESS), their integration with renewable energy systems are increasing and research on the application of ESS performing various grid services is a recent trend. In this paper, different types of ESS are reviewed, including chemical, mechanical, electrical and electrochemical storage systems, and the right choice of ESS is evaluated for performing grid applications and services, focusing on the possibility of performing multiple or stacked grid services. Various grid services are evaluated, including energy arbitrage, peak shaving, spinning reserves, frequency regulation and renewable energy integration. The analyses confirm that certain types of ESS such as compressed air ESS, electrochemical batteries and redox flow batteries are able to provide multiple grid applications, although lithium-ion batteries are proven the most suitable energy storage technology given the recent technical and market maturity.

Widespread use of electric vehicles (EVs) requires investigating impacts of vehicles' charging on power systems. This study focuses on the design of a new DC fast-charging station (DCFCS) for EVs combined with local battery energy storages (BESs). Owing to the BESs, the DCFCS is able to decouple the peak load demand caused by multiple EVs and decrease the installation costs as well as the connection fees. The charging system is equipped with a bidirectional alternating current/direct current (DC) converter, two lithium-ion batteries and a DC/DC converter. The introduction of BES within the DCFCSs is investigated with regard to operational costs of the CSs as well as the ability of a BES to mitigate negative impacts on the power grid during congestion hours. The proposed solution is shown to reduce not only the installation costs, but also the charging time and it facilitates the integration of fast chargers in existing low-voltage grids. A cost-benefit analysis is performed to evaluate the financial feasibility of BES within the DCFCSs by considering the installation costs, grid connection costs and battery life cycle costs.

The increased penetration of grid-connected photovoltaic (PV) systems in low voltage (LV) grids creates concerns about overvoltage in these grids. The proposed methods to prevent overvoltage, such as reactive power absorption by PV inverters and active power management of customers, focus on decreasing the voltage rise along LV feeders, and the potential of active medium voltage to low voltage (MV/LV) transformers for overvoltage prevention has not been thoroughly investigated. This paper presents the application of active MV/LV transformers for increasing the PV hosting capacity of LV grids. The potential interferences between the operation of active transformers and the reactive power absorption by PV inverters are investigated, and a voltage droop control approach is proposed for the efficient control of these transformers during high PV generation periods. The proposed method can potentially increase the PV hosting capacity of the grid, while eliminating the need for a complex and centralized controller. The voltages of specific locations or the grid state estimations provide adequate data for adjustments of the droop parameters. The simulations and field test results associated with the implementation of the proposed method to a newly developed active LV grid with high PV penetration in Felsberg, Germany, confirm the efficiency of the proposed method.

The integration of battery energy storage systems (BESSs) into electric power grids is increasing, and frequency reserve provision is one of the most economic services suggested for these units. This paper investigates the economic benefit of providing Frequency-Controlled Normal operation Reserve (FCR-N) using a BESS under Eastern Denmark’s (DK2) regulations. The main influencing factors, including the legal framework, energy tariffs and taxation, and battery degradation, are investigated, and the one-year operation of a 1MW/1MWh BESS providing FCR-N is simulated using second-based frequency data. Simulations show that provision of FCR-N using BESS is economic in certain future scenarios.

Made available in DSpace on 2020-12-12T01:59:48Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-09-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Transportation electrification plays an important role in developing more sustainable systems. As a result, the adoption of electric vehicles (EVs) is increasingly endorsed by governmental policies. It can be even more encouraged by promoting the provision of different ancillary services using vehicle-to-grid (V2G) enabled EVs, since EV owners may obtain additional profit by market participation. This paper presents an assessment of the economic benefits of using EVs to participate in the primary frequency regulation markets from the EV owner perspective. A heuristic method is proposed to optimize the power bid that maximizes the EV owners’ revenue along with a set of operational strategies that facilitates the service provision, which is evaluated using a simulation-based approach. A comparison analysis is performed to individually demonstrate the economic potential that four EVs with different battery capacities may offer to the owner when providing frequency-controlled normal operation reserves (FCR-N) in the Nord Pool market. The assessment of the power bid is performed considering the influence of the operation strategies and customer preferences. In addition, the effect of FCR-N on EV battery degradation and the grid impact caused by the service provision are considered in the economic evaluation. The results estimate annual benefits ranging between €100 and €1100 per vehicle, which demonstrates that EV owners can obtain substantial revenues by providing FCR-N. Department of Systems and Energy School of Electrical and Computing Engineering University of Campinas (UNICAMP) Center for Electric Power and Energy Department of Electrical Engineering Technical University of Denmark School of Engineering of Ilha Solteira Electrical Engineering Department Sao Paulo State University (UNESP) School of Engineering of Ilha Solteira Electrical Engineering Department Sao Paulo State University (UNESP) FAPESP: 2018/23617-7 CAPES: 88881.135226/2016-01

With the increasing number of electric vehicles (EVs) in use, concern about their impact on the power quality of local distribution grids is also increasing. However, efficient control of state-of-the-art EVs and their supply equipment has a great potential not only to minimize the grid impact from EV integration, but also to provide desired services for system operators in renewable-based energy systems. This paper presents and analyzes the results from the demonstration of frequency-controlled normal operation reserve (FCR-N) that is among the primary frequency regulation services in the Nord Pool energy market. EVs from different EV manufacturers as well as advanced bidirectional DC chargers are implemented in the demonstration, which is the first vehicle-to-grid (V2G) demonstration in the Nordic area with commercially available components and cross-brand EVs. A centralized control method is implemented, and two-way communications links are established to send the control signals and receive the measured data on a second-by-second basis. The results associated with the operation of EVs with different battery capacities providing FCR-N are presented, and several parameters required for validating the quality of support for FCR-N are discussed based on the demonstration outcomes. The results confirm that V2G-enabled EVs are able to provide high quality and very fast responses, and pave the way for future renewable-based energy systems.

Solar energy from photovoltaic (PV) is among the fastest developing renewable energy systems worldwide. Driven by governmental subsidies and technological development, Europe has seen a fast expansion of solar PV in the last few years. Among the installed PV plants, most of them are situated at the distribution systems and bring various operational challenges such as power quality and power flow management. The paper discusses the modelling requirements for PV system integration studies, as well as the possible techniques for voltage rise mitigation at low voltage (LV) grids for increasing PV penetration. Potential solutions are listed and preliminary results are presented.

Electric Vehicles (EVs) are representing a great opportunity for major car manufacturers to invest resources in new technologies in order to support sustainable transportation and the reduction of CO 2 emissions, in particular in the metropolitan areas. In recent years, the increasing penetration of EVs and their charging systems are going through a series of changes. This paper addresses the design of a new DC Fast Charging Station (DCFCS) for EVs coupled with a local Battery Energy Storage (BES) by using the IEC 15118, which provides a communication interface among different actors. DCFCS is equipped with a bidirectional AC/DC converter for feeding power back to the grid, two lithium batteries and a DC/DC converter. The proposed solution decreases the charging time of EVs and facilitates the integration of fast chargers in existing low voltage (LV) grids. The charging station can also be used as a multifunctional grid-utility for ancillary services such as primary frequency control, load levelling and congestion management.

Adoption of Battery Energy Storage Systems (BESSs) for provision of grid services is increasing. This paper investigates the applications of BESS for the grid upgrade deferral and voltage support of Medium Voltage (MV) distribution systems. A BESS is modelled in Matlab/Simulink to perform peak load shaving and voltage support service from the perspective of Distribution System Operators (DSOs). An active power support algorithm is implemented and the effects of various load profiles as well as different Photovoltaic (PV) penetration scenarios on the operation of BESS and the optimal BESS converter size for peak load shaving are investigated. The BESS annual lifetime degradation is also estimated using a rainflow counting algorithm. A reactive power support algorithm embedded with Q-U droop control is proposed in order to reduce the voltage drop in a part of 10 kV distribution network of Nordhavn in Copenhagen, and the effects of active and reactive power support by BESS on the grid voltage are investigated.

The increasing penetration of Electric Vehicles (EVs) and their charging systems is representing new high-power consumption loads for the distribution system operators (DSOs). To solve the problem of the EV range in terms of driving kilometers, the car manufacturers have invested resources on new EV models by increasing the size of the batteries. To satisfy EV load demand of the new EV models in urban areas the public DC Fast-Charging Station (DCFCS) is indispensable to recharge EVs rapidly. The introduction of the Battery Energy Storage within the DCFCSs is considered in this paper an alternative solution to reduce the operational costs of the charging stations as well as the ability to mitigate negative impacts during the congestion on the power grids. An accurate description of the DCFCS and its design system has been implemented, which is able to decouple the peak load demand caused by EVs on the main grid and decrease the connection fees. Finally, an economic evaluation is done to evaluate the feasibility and the cost-benefit analysis (CBA) of the DCFCSs. The proposed approach considers various technical and economic issues, such as cost of installation, connection fees and life cycle cost of the batteries. The proposed cost-benefit analysis can be used to verify the effectiveness and applicability of DCFCS in large scale.

DC Fast Charging Station (DCFCS) is essential for widespread use of Electric Vehicle (EVs). It can recharge EVs in direct current in a short period of time. In recent years, the increasing penetration of EVs and their charging systems are going through a series of changes. This paper addresses the design of a new DCFCS for EVs coupled with a local Battery Energy Storage (BES). DCFCS is equipped with a bidirectional AC/DC converter for feeding power back to the grid, two lithium batteriesand a DC/DC converter. This paper proposes an optimal size of the BES to reduce the negative impacts on the power grid through the application of electrical storage systems within the DC fast charging stations. The proposed solution decreases the charging time and the impact on the low voltage (LV) grid significantly. The charger can be used as a multifunctional grid-utility such as congestion management and load levelling. Finally, an optimal design of the DCFSC has been done to evaluate the feasibility and the operability of the system in different EVs load conditions.

In this paper a new method is proposed to determine the minimum energy storage required to be installed at different locations of a low voltage (LV) grid in order to prevent the overvoltage due to high residential photovoltaic (PV) penetration. The method is based on the voltage sensitivity analysis of feasible scenarios associated with the net injected power into the grid by customers. A new concept is defined based on the remaining power curve (RPC) associated with the local generation and consumption, and the uncertainties related to PV output and load consumption are modeled in some RPCs with different occurrence probabilities without involving the time-series studies problems. The proposed method is capable of modeling output power of PV panels with different orientations as well as different electric vehicle (EV) charging patterns.

The Parker project sought to experimentally validate that contemporary series-produced electric vehicles (EVs), capable of V2G, are ready to participate in a number of advanced grid services. In such services, the timing, size and direction of power and energy exchanged between the EV battery and grid is controlled as to support either a single building, the local neighborhood or the regional power system. Vehicles purposely designed for such services are referred to as grid integrated electric vehicles (GIVs). The field of research, describing how GIVs may be used to actively support the power system, is called Vehicle&ndash, Grid Integration (VGI).The purpose of this paper is to present how the Danish Parker project has systematically categorized a range of grid services, collected in a service catalog, and then illustrate state-of-the-art EVs ability to support such services through experimental validation. Results are presented for three different tests performed in Parker, marginal emission factor charging, frequency containment reserves and a performance test for controlling power setpoints. The ultimate aim of this paper, and the Parker project, is to promote the GIV concept so that it may inform the design and capabilities of present and future EVs, EV supply equipment (EVSE) and communication standards.

Photovoltaic (PV) systems are among the renewable sources that electrical energy systems are adopting with increasing frequency. The majority of already-installed PV systems are decentralized units that are usually connected to low voltage (LV) distribution grids. The PV hosting capacity of an LV grid is usually limited by overvoltage, and the efficient control of distributed electrical energy storage systems (EESSs) can considerably increase this capacity. In this paper, a new control approach based on the voltage sensitivity analysis is proposed to prevent overvoltage and increase the PV hosting capacity of LV grids by determining dynamic set points for EESS management. The method has the effectiveness of central control methods and can effectively decrease the energy storage required for overvoltage prevention, yet it eliminates the need for a broadband and fast communication. The net power injected into the grid and the amount of reactive power absorbed by PV inverters are estimated using the PV generation forecast and load consumption forecast, and the dynamic operating points for energy storage management are determined for a specific period of time by solving a linear optimization problem. Simulations performed on a realistic LV feeder of the Danish island Bornholm verify the performance of the proposed method.

The rapid development of photovoltaic (PV) systems in electrical grids brings new challenges in the control and operation of power systems. A considerable share of already installed PV units are small-scale units, usually connected to low voltage (LV) distribution systems that were not designed to handle a high share of PV power. This paper provides an in-depth review of methods and strategies proposed to prevent overvoltage in LV grids with PV, and discusses the effectiveness, advantages, and disadvantages of them in detail. Based on the mathematical framework presented in the paper, the overvoltage caused by high PV penetration is described, solutions to facilitate higher PV penetration are classified, and their effectiveness, advantages, and disadvantages are illustrated. The investigated solutionsinclude the grid reinforcement, electrical energy storage application, reactive power absorption by PV inverters, application of active medium voltage to low voltage (MV/LV) transformers, active power curtailment, and demand response (DR). Coordination between voltage control units by localized, distributed, and centralized voltage control methods is compared using the voltage sensitivity analysis. Based on the analysis, a combination of overvoltage prevention methods and coordination between voltage control units can provide an efficient and reliable solution to increase the PV hosting capacity of LV grids. ½½

Sustainable management of precious groundwater resources is vital to growth, especially in arid areas which they heavily depend on. In this study, monthly groundwater level time series of 322 observation wells in Sistan and Balouchestan province of Iran in the period 2002 to 2012 were used as a measure of sustainable development. Results show that 95.6% of areas of the province aquifers are non-stationary. In addition, 5.5%, 13.7% and 80.8% of studied wells show no increasing and decreasing trend at 5% significance level. Spatial analysis reveals that the groundwater levels of 7.3%, 11.3% and 81.6% area of groundwater resources have increased, sustained or decreased, respectively. According to calculated slope of trends, the province has experienced –69.72 (MCM) decline in groundwater resources per year in past ten years. It means that sustainable development criteria were totally neglected. Increasing in water use efficiency in the agriculture sector by 6% and of water reuse by 78% will solve the issue.

By increasing in the penetration level of wind turbines, the influence of these new added generation units on the power system oscillations specifically inter-area oscillations has to be thoroughly investigated. In this paper, the impact of increasing in the penetration of full rate converter wind turbines (FRC-WTs) on the inter-area oscillations of power system is examined. In order to have a comprehensive evaluation of the effects of FRC-WT on the inter-area oscillations, different scenarios associated with the wind power penetration levels, wind farm locations, strength of interconnection line, and different operating conditions of synchronous generators are investigated. The synchronous generators, exciter systems and power system stabilizers (PSSs) as well as the FRC-WT grid-side converter and its related controllers are modelled in detail in Matlab in order to evaluate the effects of FRC-WTs on the inter-area mode oscillations precisely. The results show that FRC-WTs can affect the inter-area oscillations considerably in some simulation scenarios.

In this paper a new method is proposed to mitigate voltage unbalance caused by single-phase solar inverters in low voltage (LV) networks. The method is based on uneven reactive power absorption and injection by three-phase solar inverters. Independent control of each phase is performed to achieve this uneven injection. The average values of phase voltages at the connection points of the photovoltaic (PV) inverters are used as the references for the balancing algorithm. Voltage unbalance mitigation is achieved by use of this method in different scenarios with variable three-phase and single-phase inverters penetration in a realistic LV grid. In addition, the overvoltage is reduced by using this method.