The diffusion of electric vehicles will be strongly related to the capacity to charge them in short times. To do so, the necessity of widespread fast charging stations arises. However, their intermittent demand represents a challenging load for grid operators. In order to relieve their impact on the electrical grid operation, integrating storage systems in the charging stations represents a potential solution, although it complicates the overall system management. Moreover, standard converter architectures for the MV grid interface require the installation of bulky transformers and filters. In order to cope with the mentioned problems, this paper proposes an ultra-fast charging station topology based on a modular multilevel converter (MMC) structure and dual-active bridge (DAB) converters. Thanks to the multilevel converter properties, the proposed charging station can be directly interfaced with the MV grid without requiring transformers or filters. Additionally, exploiting the degree... [more]

Based on the unique ubiquity of similar solvate structures found in solvate crystals and superconcentrated electrolytes, we performed a systematic study of four reported solvate crystals which consist of different lithium salts (i.e., LiMPSA, LiTFSI, LiDFOB, and LiBOB) solvated by acetonitrile (MeCN) based on first principles calculations. Based on the calculations, these solvate crystals are predicted to be electronic insulators and are expected to be similar to their insulating liquid counterpart (e.g., 4 M superconcentrated LiTFSI-MeCN electrolyte), which has been confirmed to be a promising electrolyte in lithium batteries. Although the MeCN molecule is highly unstable during the reduction process, it is found that the salt-MeCN solvate molecules (e.g., LiTFSI-(MeCN)2, LiDFOB-(MeCN)2) and their charged counterparts (anions and cations) are both thermodynamically and electrochemically stable, which can be confirmed by Raman vibrational modes through the unique characteristic variati... [more]

The increasing limitations in the use of fossil fuels due to their limited availability and pollution have increased the use of renewable energies and storage systems for electricity generation. To achieve the goals of the integration of renewable energy, sizing and management methods for hybrid plants are needed to make investments profitable and attractive in these resources. This work presents an optimization method for the sizing and operation of hybrid plants with storage, choosing the best combination of technologies based on resource availability, installation costs and market prices, maximizing an economic index such as the net present value. One of the main contributions of this work is to reduce the oversizing that occurs in traditional methods through a penalty term for lost energy, encouraging investment in batteries to store excess energy above the point of interconnection (POI). In addition, it is intended to cover gaps such as the operation in coupled markets with differ... [more]

Further increases in the number of photovoltaic installations in industry and residential buildings will require technologically and economically flexible energy storage solutions. Some countries utilize net-metering strategies, which use national networks as “virtual batteries.” Despite the financial attractiveness, net-metering faces many technological and economical challenges. It could also lead to the negative tendencies in prosumer behavior, such as a decrease in motivation for the self-consumption of photovoltaic (PV)-generated electricity. Batteries, which are installed on the prosumer’s premises, could be a solution in a particular case. However, the price for battery-based storage solutions is currently sufficiently unattractive for the average prosumer. This paper aimed to present a comparison of the economic and energy related aspects between net-metering and batteries for a single case study by considering the Lithuanian context. The net present value, degree of self-suffi... [more]

An important revenue stream for electric battery operators is often arbitraging the hourly price spreads in the day-ahead auction. The optimal approach to this is challenging if risk is a consideration as this requires the estimation of density functions. Since the hourly prices are not normal and not independent, creating spread densities from the difference of separately estimated price densities is generally intractable. Thus, forecasts of all intraday hourly spreads were directly specified as an upper triangular matrix containing densities. The model was a flexible four-parameter distribution used to produce dynamic parameter estimates conditional upon exogenous factors, most importantly wind, solar and the day-ahead demand forecasts. These forecasts supported the optimal daily scheduling of a storage facility, operating on single and multiple cycles per day. The optimization is innovative in its use of spread trades rather than hourly prices, which this paper argues, is more attra... [more]

The degradation of lithium-ion cells is an important aspect, not only for quality management, but also for the customer of the application like, e.g., scooters or electric vehicles. During the lifetime of the system, the overall health on the battery plays a key role in its depreciation. Therefore, it is necessary to monitor the health of the battery during operation, i.e., cycle life, but also during stationary conditions, i.e., calendar aging. In this work, the degradation due to calendar aging is analyzed for six different cell chemistries in terms of capacity degradation and impedance increase and their performance are being compared. In a new proposed metric, the relative deviations between various cells with the exact identical aging history are being analyzed for their degradation effects and their differences, which stands out in comparison to similar research. The capacity loss was found to be most drastic at 60 °C and at higher storage voltages, even for titanate-oxide cells.... [more]

Energy storage systems are expected to play a fundamental part in the integration of increasing renewable energy sources into the electric system. They are already used in power plants for different purposes, such as absorbing the effect of intermittent energy sources or providing ancillary services. For this reason, it is imperative to research managing and sizing methods that make power plants with storage viable and profitable projects. In this paper, a managing method is presented, where particle swarm optimisation is used to reach maximum profits. This method is compared to expert systems, proving that the former achieves better results, while respecting similar rules. The paper further presents a sizing method which uses the previous one to make the power plant as profitable as possible. Finally, both methods are tested through simulations to show their potential.

This paper presents a user-friendly design method for accurately sizing the distributed energy resources of a stand-alone microgrid to meet the critical load demands of a military, commercial, industrial, or residential facility when utility power is not available. The microgrid combines renewable resources such as photovoltaics (PV) with an energy-storage system to increase energy security for facilities with critical loads. The design method’s novelty complies with IEEE Standards 1562 and 1013, and addresses resilience, which is not taken into account in existing design methods. Several case studies simulated with a physics-based model validate the proposed design method and demonstrate how resilience can be included in the design process. Additionally, the design and the simulations were validated by 24 h laboratory experiments conducted on a microgrid assembled using commercial off-the-shelf components.

This paper presents an electrical infrastructure planning method for transit systems that operate with partially grid-connected vehicles incorporating on-board batteries. First, the state-of-the-art of electric transit systems that combine grid-connected and battery-based operation is briefly described. Second, the benefits of combining a grid connection and battery supply in Bus Rapid Transit (BRT) systems are introduced. Finally, the planning method is explained and tested in a BRT route in Medellin, Colombia, using computational simulations in combination with real operational data from electric buses that are currently operating in this transit line. Unlike other methods and approaches for Battery Electric Bus (BEB) infrastructure planning, the proposed technique is system-focused, rather than solely limited to the vehicles. The objective of the technique, from the vehicle’s side, is to assist the planner in the correct sizing of batteries and power train capacity, whereas from the... [more]

Photovoltaic water pumping systems (PVWPS) are a promising solution to improve domestic water access in low-income rural areas. It is challenging, however, to make them more affordable for the local communities. We develop here a comparative methodology to assess relevant features of both widely employed PVWPS architecture with water tank storage, and hardly used PVWPS architecture with a battery bank instead of tank storage. The quantitative comparison is carried out through techno-economic optimization, with the goal of minimizing the life cycle cost of PVWPS with constraints on the satisfaction of the water demand of local inhabitants and on the groundwater resource sustainability. It is aimed to support decision-makers in selecting most appropriate storage for domestic water supply projects. We applied the methodology in the rural village of Gogma, Burkina Faso. Results indicate that the life-cycle cost of an optimized PVWPS with batteries is $24.1k while it is $31.1k if a tank is... [more]

The online estimation of battery state of health (SOH) is crucial to ensure the reliability of the energy supply in electric and hybrid vehicles. An approach for enhancing the generalization of SOH estimation using a parallel layer extreme learning machine (PL-ELM) algorithm is analyzed in this paper. The deterministic and stable PL-ELM model is designed to overcome the drift problem that is associated with some conventional machine learning algorithms; hence, extending the application of a single SOH estimation model over a large set of batteries of the same type. The PL-ELM model was trained with selected features that characterize the SOH. These features are acquired as the discrete variation of indicator variables including voltage, state of charge (SOC), and energy releasable by the battery. The model training was performed with an experimental battery dataset collected at room temperature under a constant current load condition at discharge phases. Model validation was performed... [more]

Renewable integration into the electricity system of Great Britain (GB) is causing considerable demand for additional flexibility from plants. In particular, a considerable share of this flexibility may be dispatched to secure post-fault transient frequency dynamics. Pursuant to the unprecedented changes to the traditional portfolio of generation sources, this work presents a detailed analysis of the potential system-level value of unlocking flexibility from nuclear electricity production. A rigorous enhanced mixed integer linear programming (MILP) unit commitment formulation is adopted to simulate several generation-demand scenarios where different layers of flexibility are associated to the operation of nuclear power plants. Moreover, the proposed optimisation model is able to assess the benefit of the large contribution to the system inertial response provided by nuclear power plants. This is made possible by considering a set of linearised inertia-dependent and multi-speed constrai... [more]

This paper shows a preliminary study about the output voltage modulation of a modular battery system based on a seven-level cascaded H-bridge inverter used for vehicle propulsion. Two generally known modulation techniques, pulse width modulation (PWM) and fundamental selective harmonic elimination (FSHE), are extensively compared for such an innovative modular battery system inverter considering EVs’ broad torque-speed range. The inverter and the battery losses, as well as the inverter-induced current THD, are modeled and quantified using simulations. At low speeds, if the modulation index M is below 0.3, FSHE induces a high current THD (>>5%) and, thus, cannot be used. At medium speeds, FSHE reduces the drivetrain losses (including the battery losses), while operating at higher speeds, it even reduces the current THD. Thus, an individual boundary between multilevel PWM and FSHE can be determined using weightings for efficiency and current quality. Based on this, a simple hybrid modula... [more]

Full-electric boats are an expression of recent advancements in the area of vessel electrification. The installed batteries can suffer from poor cold-start performance, especially in the frigid season and at higher latitudes, leading to driving power limitations immediately after startup. At state, the leading solution is to adopt a dedicated heater placed on the common cooling/heating circuit; this implies poor volume, weight, and cost figures, given the very limited duty cycle of such a part. The Heater-in-Converter (HiC) technology allows removing this specialized component, exploiting the power electronics converters already available on board: HiC modulates their efficiency to produce valuable heat (pseudo-cogeneration). In this work, we use the model-based approach to design this system, which requires heating power minimization to fulfill power electronics limitations, while guaranteeing the user-expected startup time to full power. A multistage model is used to get the yearly v... [more]

With the increasing penetration of renewable resources into the low-voltage distribution grid, the demand for alternatives to grid reinforcement measures has risen. One possible solution is the use of battery systems to balance the power flow at crucial locations in the grid. Hereby, the optimal location and size of the system have to be determined in regard to investment and its effect on grid stability. In this paper, the optimal placement and sizing of battery storage systems for grid stabilization in a small low-voltage distribution grid in southern Germany with high PV penetration are investigated and compared to a grid heuristic reinforcement strategy.

The purpose of this paper is to describe the upcoming changes that will bring the transition from piston engines to all-electric aircrafts. The article focuses on the differences in operation of small general aviation aircrafts. This topic is timely, as the first all-electric aircraft was certified by the European Union Aviation Safety Agency (EASA) in 2019. As there are no data concerning this new type of operation available, the data have been derived from other applicable sources. At first, we compared the energy consumption of the same aircraft with the piston engine, and then afterwards with the retrofitted all-electric variant. Our results focus on the difference in fuel price, which is discussed in the context of electricity price comparison with AVGAS prices. Moreover, we discuss the environmental impacts, especially concerning electricity source mix and emissions produced (we estimate both with and without life-cycle assessment). In the discussion, we compare the results and i... [more]

An important aspect of the off-grid utilization of hybrid generation systems is the integration of energy storage facilities into their structures, which allows for improved power supply reliability. However, this results in a significant increase in the cost of such systems. Therefore, it is justified to use optimization resulting in the minimization of the selected economic indicator taking into account the most important technical constraints. For this reason, this work proposes an algorithm to optimize the structure of a hybrid off-grid power distribution system (with electrochemical energy storage), designed to supply a load with known daily energy demand. The authors recommend genetic algorithm utilization as well as a modified criterion for evaluating the quality of solutions based on the Levelized Cost of Energy (LCOE) index. Several technical and economic analyses were presented, including unit costs, power distribution of the wind and solar sections, nominal battery capacity,... [more]

The internet of things (IoT) manages a large infrastructure of web-enabled smart devices, small devices that use embedded systems, such as processors, sensors, and communication hardware to collect, send, and elaborate on data acquired from their environment. Thus, from a practical point of view, such devices are composed of power-efficient storage, scalable, and lightweight nodes needing power and batteries to operate. From the above reason, it appears clear that energy harvesting plays an important role in increasing the efficiency and lifetime of IoT devices. Moreover, from acquiring energy by the surrounding operational environment, energy harvesting is important to make the IoT device network more sustainable from the environmental point of view. Different state-of-the-art energy harvesters based on mechanical, aeroelastic, wind, solar, radiofrequency, and pyroelectric mechanisms are discussed in this review article. To reduce the power consumption of the batteries, a vital role i... [more]

Generally, the State-of-Health (SOH) monitoring and Remaining Useful Life (RUL) prediction and assessment of lithium-ion (Li-ion) batteries need to use sensors to obtain the degradation test data of the same type of batteries and establish the degradation model for reference. However, when the battery type is unknown, a usable reference model cannot be obtained, so its prediction and evaluation may be relatively inconvenient. In this paper, the State of-Health prediction for lithium-ion batteries based on a novel hybrid scheme is proposed. Firstly, historical charge/discharge time series and capacity series are extracted to analyze and construct Health Indicators, then using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) to decompose the Health Indicator series into the trend and non-trend terms. Among them, the relatively smooth trend item data series uses the Autoregressive Integrated Moving Average model (ARIMA) for prediction; when dealing with the dat... [more]

The increasing popularity of electric vehicles (EVs) has been attributed to their low-carbon and environmentally friendly attributes. Extensive research has been undertaken in view of the depletion of fossil fuels, changes in climatic conditions due to air pollution, and the goal of developing EVs capable of matching or exceeding the performance of today’s internal combustion engines (ICEs). The transition from ICE vehicles to EVs can reduce greenhouse gases significantly over a vehicle’s lifetime. Across the different types of EVs, the widespread usage of batteries is due to their high power density and steady output voltage, making them an excellent energy storage device (ESD). The current downsides of battery-powered electric vehicles include long recharge times, the impact of additional strain on the grid, poor societal acceptance due to high initial costs, and a lack of adequate charging infrastructure. Even more problematic is their short driving range when compared to standard I... [more]

The decarbonization of the power sector involves electrification and a massive deployment of variable renewable energy sources, leading to an increase of local transmission congestion and ramping challenges. A possible solution to secure grid stability is local flexibility markets, in which prosumers can offer demand-side flexibility to the distribution system operator or other flexibility buyers through an aggregator. The purpose of this study was to develop a framework for estimating and offering short-term demand-side flexibility to a flexibility marketplace, with the main focus being baseline estimation and bid generation. The baseline is estimated based on forecasts that have been corrected for effects from earlier flexibility activations and potential planned use of internal flexibility. Available flexibility volumes are then estimated based on the baseline, physical properties of the flexibility asset and agreed constraints for baseline deviation. The estimated available flexibi... [more]

This paper presents an environmental sustainability assessment of residential user-scale energy systems, named solar home systems, encompassing their construction, operation, and end of life. The methodology adopted is composed of three steps, namely a design phase, a simulation of the solar home systems’ performance and a life cycle assessment. The analysis aims to point out the main advantages, features, and challenges of lithium-ion batteries, considered as a benchmark, compared with other innovative devices. As the environmental sustainability of these systems is affected by the solar radiation intensity during the year, a sensitivity analysis is performed varying the latitude of the installation site in Europe. For each site, both isolated and grid-connected solar home systems have been compared considering also the national electricity mix. A general overview of the results shows that, regardless of the installation site, solid state nickel cobalt manganese and nickel cobalt alum... [more]

The energy storage industry has expanded globally as costs continue to fall and opportunities in consumer, transportation, and grid applications are defined. As the rapid evolution of the industry continues, it has become increasingly important to understand how varying technologies compare in terms of cost and performance. This paper defines and evaluates cost and performance parameters of six battery energy storage technologies (BESS)—lithium-ion batteries, lead-acid batteries, redox flow batteries, sodium-sulfur batteries, sodium-metal halide batteries, and zinc-hybrid cathode batteries—four non-BESS storage systems—pumped storage hydropower, flywheels, compressed air energy storage, and ultracapacitors—and combustion turbines. Cost and performance information was compiled based on an extensive literature review, conversations with vendors and stakeholders, and costs of systems procured at sites across the United States. Detailed cost and performance estimates are presented for 2018... [more]

To reduce the dependence on oil and environmental pollution, the development of electric vehicles has been accelerated in many countries. The implementation of EVs, especially battery electric vehicles, is considered a solution to the energy crisis and environmental issues. This paper provides a comprehensive review of the technical development of EVs and emerging technologies for their future application. Key technologies regarding batteries, charging technology, electric motors and control, and charging infrastructure of EVs are summarized. This paper also highlights the technical challenges and emerging technologies for the improvement of efficiency, reliability, and safety of EVs in the coming stages as another contribution.

Proper planning of the installation of Battery Energy Storage Systems (BESSs) in distribution networks is needed to maximize the overall technical and economic benefits. The limited lifetime and relatively high cost of BESSs require appropriate decisions on their installation and deployment, in order to make the best investment. This paper proposes a comprehensive method to fully support the BESS location and sizing in a low-voltage (LV) network, taking into account the characteristics of the local generation and demand connected at the network nodes, and the time-variable generation and demand patterns. The proposed procedure aims to improve the overall network conditions, by considering both technical and economic aspects. An original approach is presented to consider both the planning and scheduling of BESSs in an LV system. This approach combines the properties of metaheuristics for BESS sizing and placement with a greedy algorithm to find viable BESS scheduling in a relatively sho... [more]