Electrical Storage Systems Research Articles

Decentralized electricity storage evaluation in the Portuguese context

Portugal has made great progress in implementing renewable energy systems (RES) to use its endogenous renewable resources. As the cost of renewable energy generation is decreasing, mainly for photovoltaic energy, a significant increase in its production is expected, in particular at the local and domestic levels. Yet, much investment and development is still needed to fulfil the goals for renewable energy generation defined by the Portuguese government and the European Union, in order to decarbonize energy generation and reduce energy dependence. Besides limitations in the installed capacity, the full potential of existing and future RES is not fulfilled, mainly due to imbalances in supply and demand, resulting from the varying climatic conditions and limited energy storage capacity. Although some investment was made in large scale Energy Storage Systems (ESS), especially pumped hydro, distributed energy storage (DES), in particular for stationary domestic storage appliances, have received little attention from decision makers. When properly defined, designed and implemented, they can contribute to increase the efficiency of existing and future RES and the capacity factor. Thus, in this work the questions regarding the implementation of DES are analysed. The main criteria that have to be considered when selecting the proper storage technology for DES are defined, taking into account information and data from current legislation and/or strategic plans and goals, and the technical and scientific literature, in order to support decision making and policy definition at different levels. The proposed application of the various criteria leads to the conclusion that for DES, electrochemical based ESS are the most adequate, among which Li ion batteries and redox flow batteries, particularly suited for local and/or household applications. The current policies sought out for Portugal are also examined in order to identify which aspects should be improved to promote and increase the relevance of DES in the Portuguese energy mix, and it is concluded that specific policies and support are needed to increase the relevance of decentralized electricity storage systems.

Operation of Solar-Storage-Hydrogen-Charging System by Value Stream Analysis

The topology of the clean energy system is a flexible structure with PV, wind power, hydrogen storage, battery storage. Thus, the construction and operation of the clean energy system should pay more attention to the temporal and spatial variations. This paper discussed a solar-storage-hydrogen-charging demonstration to accommodate the diverse temporal and spatial features of the clean energy system. The present study developed a Modelica library to support the cooperative control of this clean energy system based on value stream analysis. The result shows that the sold electricity profit of the electric storage system can reach 2.3 times than the electricity purchase cost. Though the hydrogen charging demand in the demonstration is small compared with the electric load demand, the hydrogen charging profit can be 1.7 times of the energy cost.

Dynamic Simulation of Pumped Thermal Electricity Storage System Based on Simulink

Dynamic Simulation of Pumped Thermal Electricity Storage System Based on Simulink

Energy and economic analysis of a small hybrid solar-geothermal trigeneration system: A dynamic approach

This work presents a dynamic simulation model of a prototypal renewable plant producing electricity, heat and cool. The hybrid system consists of a 6 kWe Organic Rankine Cycle (ORC), a 17.1 kWf absorption chiller, a geothermal well, a 25 m2 evacuated solar collector field, a 200 kWt biomass heater and a 45.56 kWh electric energy lithium-ion storage system. The geothermal well at 96 °C, in combination with the solar field, supplies the thermal energy driving the ORC. This simulation model is implemented in TRNSYS environment. In order to evaluate the thermoeconomic performance of this renewable trigeneration plant, a suitable case study is analysed: a bar and soccer centre in the area of Campi Flegrei (Naples). By the simulation, interesting results in terms of energy and environmental performance are obtained. The proposed renewable power plant achieves a primary energy saving of 94.54% and a reduction of CO2 emissions equal to 97.36%. The high total capital cost of the plant significantly affects the payback period of 16.7 years. However, in the future European energy scenarios, where a full decarbonization will be achieved and the capital cost of the renewables will significantly decrease, the use of these technologies will be pivotal and significantly profitable.

Power Conversion System for Hybrid Battery-Capacitor Storage

Context: Thanks to the low emissions of CO2 generated by electric systems, those solutions have anincreased attention from industry and academia. However, the electrical storage systems required in alarge amount of applications must to have both high energy and power densities.
 Method: To meet those requirements, this paper proposes an active hybrid energy storage system(HESS), which is formed by a battery, i.e. the device with high energy density, and a capacitor, i.e. the device with high power capability. The proposed power system also protects the battery by limiting the current derivative.
 Results: Two sliding-mode controllers (SMC) are designed to regulate both the battery current and the load voltage. The design process guarantees the global stability and safe battery operation.
 Conclusions: The controller avoids the battery degradation caused by the high-frequency current components since the capacitor assumes those components demanded by the load profile.

Optimal Coordination Strategies for Load Service Entity and Community Energy Systems Based on Centralized and Decentralized Approaches

The energy interaction among a load service entity and community energy systems in neighboring communities leads to a complex energy generation, storage, and transaction problem. A load service entity is formed by a local electricity generation system, storage system, and renewable energy resources, which can provide ancillary services to customers and the utility grid. This paper proposes two coordination schemes for the interaction of community-based energy systems and load service entities based on game-theoretic frameworks. The first one is a centralized coordination scheme with full cooperation, in which the load service entity and community energy systems jointly activate the local resources. The second one is set as a decentralized coordination scheme to obtain a relative balance of interests among the market participants in a Stackelberg framework. Two mathematical models are developed for the day-ahead decision-making of the above energy management schemes. The Shapley value method, Karush-Kuhn-Tucker conditions, and strong dual theory are applied to solve the complex coordination problems. Numerical study shows the effectiveness of the coordination strategies that all stakeholders benefit from the proposed coordination schemes and create a win–win situation. In addition, sensitivity analysis is conducted to study the effects of system configuration, energy demand, and energy prices on the economic performance of all stakeholders. The results can serve as references for business managers of the load service entity.

Distributed Voltage Control in Active Distribution Network Considering Renewable Energy: A Novel Network Partitioning Method

With the increasing integration of distribution generations (DGs), active distribution networks (ADNs) need to address the new challenges in voltage control. Meanwhile, the traditional centralized method in reactive power optimization usually leads to a heavy computational burden for large-scale distribution networks. A distributed voltage control model with a novel network partitioning method is proposed in this study, where the capacity curve of DGs and the regulation of electrical storage systems (ESS) are specially addressed. According to the number of decision variables and the number of constraints in the optimization model, the computational complexity can be utilized in the network partitioning method with the power balance and the electrical distance to automatically partition a distribution network in an optimal manner. Taking the coordination between two boundary sub-areas into consideration, a distributed voltage control strategy is developed and solved by a distributed solution method based on Lagrangian dual relaxation. Finally, numerical studies based on two IEEE test systems and a practical 152-bus system are performed to verify the effectiveness of the proposed method.

A dynamic decision model for energy-efficient scheduling of manufacturing system with renewable energy supply

The climate mitigation and the reduction of energy cost in manufacturing processes drive to expand the electricity generation from renewable sources. Nonetheless, intermittency of renewable energies, especially solar and wind energy, represents one on the main challenge, typically overcome by the installation of electricity storage systems. This issue can be addressed by a new and original approach, consisting in energy-flexibility of the production, in which manufacturing parameters are selected to optimize and to align production planning to the renewable energy availability. The paper deals with a time dependent theoretical and numerical model developed to calculate the time evolution of the electric power required by a manufacturing system, self-consistently coupled with a renewable plant. The aim of the model is to align the power required by the manufacturing system with the renewable energy supply in order to obtain the maximum monthly profit. The model has been applied to a single work center powered by the electric grid and by a photo-voltaic system, performing the machining process over one year of production. The model includes the tool cost, the stocked units, the energy cost and the penalty for the unsatisfied demand. The maximum profit has been calculated with a hourly adaption of manufacturing parameters, i.e. the cutting speed, to the renewable time dependent power profile. The model presents general features and can be applied when production processes are fully characterized.In order to find the maximum profit, the model, inherently nonlinear, has been solved by recurring to the Trust-Region Method. Different scenarios characterized by fluctuations of product demand are considered in order to investigate the sensitivity of the manufacturing system to the uncertainty of the forecast demand. The influence of the photo-voltaic supply has been investigated, comparing results obtained in the case of manufacturing systems powered only by the electric grid. Numerical results show how the proposed method allows to select an optimized production planning, reducing the energy costs and CO2 emissions and finding the maximum profit with the best compromise between the market demand and energy costs.

Competition between simultaneous demand-side flexibility options: the case of community electricity storage systems

Community electricity storage systems for multiple applications promise benefits over household electricity storage systems. More economical flexibility options such as demand response and sector coupling might reduce the market size for storage facilities. This paper assesses the economic performance of community electricity storage systems by taking competitive flexibility options into account. For this purpose, an actor-related, scenario-based optimization framework is applied. The results are in line with the literature and show that community storage systems are economically more efficient than household storage systems. Relative storage capacity reductions of community storage systems over household storage systems are possible, as the demand and generation profiles are balanced out among end users. On average, storage capacity reductions of 9% per household are possible in the base scenario, resulting in lower specific investments. The simultaneous application of demand-side flexibility options such as sector coupling and demand response enable a further capacity reduction of the community storage size by up to 23%. At the same time, the competition between flexibility options leads to smaller benefits regarding the community storage flexibility potential, which reduces the market viability for these applications. In the worst case, the cannibalization effects reach up to 38% between the flexibility measures. The losses of the flexibility benefits outweigh the savings of the capacity reduction whereby sector coupling constitutes a far greater influencing factor than demand response. Overall, in consideration of the stated cost trends, the economies of scale, and the reduction possibilities, a profitable community storage model might be reached between 2025 and 2035. Future work should focus on the analysis of policy frameworks.

Developing an optimization methodology for urban energy resources mix

This paper proposes a methodology to optimize the mixture of renewable and alternative energy resources, according to various neighborhood concepts, renewable energy settings and energy sources employed for the operation of buildings. Two neighborhood concepts are explored- a standalone neighborhood, which is independent from the local grid, and a grid-tied neighborhood, which can supply electricity to the grid as well as draw from it, depending on available energy generation from other sources. Renewable energy sources employed in the study consist of photovoltaic technology as well as wind turbines, while alternative energy sources consist of waste to energy. The proposed methodology is applied to a hypothetical mixed-use neighborhood representing a cold northern climate.The results indicate that an electric storage system is required, to achieve a net-zero energy, standalone neighborhood. This can reduce energy system size, which can be otherwise excessive (photovoltaic area can reach up to 280 times the area available in the neighborhood). For a grid-tied neighborhood, the grid can replace the storage system, reducing thus the size of renewable and alternative energy required to fulfill the energy demand. In such case, photovoltaic size can be reduced by up to 67% as compared to the standalone neighborhood, while wind turbines can be significantly reduced (by 85%) or completely eliminated.

Thermo-Economic Analysis of Hybrid Solar-Geothermal Polygeneration Plants in Different Configurations

This work presents a thermoeconomic comparison between two different solar energy technologies, namely the evacuated flat-plate solar collectors and the photovoltaic panels, integrated as auxiliary systems into two renewable polygeneration plants. Both plants produce electricity, heat and cool, and are based on a 6 kWe organic Rankine cycle (ORC), a 17-kW single-stage H2O/LiBr absorption chiller, a geothermal well at 96 °C, a 200 kWt biomass auxiliary heater, a 45.55 kWh lithium-ion battery and a 25 m2 solar field. In both configurations, electric and thermal storage systems are included to mitigate the fluctuations due to the variability of solar radiation. ORC is mainly supplied by the thermal energy produced by the geothermal well. Additional heat is also provided by solar thermal collectors and by a biomass boiler. In an alternative layout, solar thermal collectors are replaced by photovoltaic panels, producing additional electricity with respect to the one produced by the ORC. To reduce ORC condensation temperature and increase the electric efficiency, a ground-cooled condenser is also adopted. All the components included in both plants were accurately simulated in a TRNSYS environment using dynamic models validated versus literature and experimental data. The ORC is modeled by zero-dimensional energy and mass balances written in Engineering Equation Solver and implemented in TRNSYS. The models of both renewable polygeneration plants are applied to a suitable case study, a commercial area near Campi Flegrei (Naples, South Italy), a location well-known for its geothermal sources and good solar availability. The economic results suggest that for this kind of plant, photovoltaic panels show lower pay back periods than evacuated flat-plate solar collectors, 13 years vs 15 years. The adoption of the electric energy storage system leads to an increase of energy-self-sufficiency equal to 42% and 47% for evacuated flat-plate solar collectors and the photovoltaic panels, respectively.

Flattening the Electricity Demand Profile of Office Buildings for Future-Proof Smart Grids

The built environment has the potential to contribute to maintaining a reliable grid at the demand side by offering flexibility services to a future Smart Grid. In this study, an office building is used to demonstrate forecast-driven building energy flexibility by operating a Battery Electric Storage System (BESS). The objective of this study is, therefore, to stabilize/flatten a building energy demand profile with the operation of a BESS. First, electricity demand forecasting models are developed and assessed for each individual load group of the building based on their characteristics. For each load group, the prediction models show Coefficient of Variation of the Root Mean Square Error (CVRMSE) values below 30%, which indicates that the prediction models are suitable for use in engineering applications. An operational strategy is developed aiming at meeting the flattened electricity load shape objective. Both the simulation and experimental results show that the flattened load shape objective can be met more than 95% of the time for the evaluation period without compromising the thermal comfort of users. Accurate energy demand forecasting is shown to be pivotal for meeting load shape objectives.

High-Throughput Electrochemical Characterization of Aqueous Organic Redox Flow Battery Active Material

Aqueous Organic Redox Flow Batteries (AORFBs) have emerged as promising and potentially disruptive technologies for the storage of energy from intermittent renewable sources. With the goal of cost-effective, safe, and scalable stationary electricity storage systems, AORFBs could eclipse Li-ion batteries due to their inherent non-flammability, lack of materials scarcity fluctuations, and intrinsic decoupling of energy and power capacities. Recent work has demonstrated that calendar life, rather than cycle life, limits molecular lifetimes in AORFBs due to various molecular instabilities that lead to side reactions, thus inhibiting performance. For accurately determining molecular fade rates, the importance has been demonstrated of potentiostatic holds in order to avoid artifacts caused by drifts in internal resistance; additionally the utility of volumetrically unbalanced, compositionally-symmetric cell configurations to distinguish molecular fade from membrane crossover has been demonstrated [1]. However, some reports continue to use purely galvanostatic cycling to characterize molecular stability, leading to unreliable reports of molecular fade rates.An in-depth study comparing previously published redox-active organic molecules [2-8] has been performed using the symmetric cell protocol. True capacity fade rates as functions of concentration and pH are evaluated in a high-throughput setup using high-precision coulometry. Collectively, these results highlight the relevance of electrochemical techniques to understand molecular degradation in AORFBs. By accelerating the screening process of candidate molecules for AORFBs and ensuring rigorous assessment of battery performance, these techniques are expected to more rapidly advance good candidates for long lifetime RFB designs, capable of enabling massive grid penetration of intermittent renewable energy.[1] M.-A. Goulet and M. J. Aziz, “Flow Battery Molecular Reactant Stability Determined by Symmetric Cell Cycling Methods,” Journal of the Electrochemical Society , 165, A1466 (2018).[2] D. G. Kwabi, K. Lin, Y. Ji, E. F. Kerr, M.-A. Goulet, D. De Porcellinis, D. P. Tabor, D. A. Pollack, A. Aspuru-Guzik, R. G. Gordon, and M. J. Aziz, “Alkaline Quinone Flow Battery with Long Lifetime at pH 12,” Joule, 2, 1894 (2018).[3] Y. Ji, M.-A. Goulet, D. A. Pollack, D. G. Kwabi, S. Jin, D. De Porcellinis, E. F. Kerr, R. G. Gordon, and M. J. Aziz, “A Phosphonate-Functionalized Quinone Redox Flow Battery at Near-Neutral pH with Record Capacity Retention Rate,” Advanced Energy Materials, 9, 1900039 (2019).[4] M.-A. Goulet, L. Tong, D. A. Pollack, D. P. Tabor, S. A. Odom, A. Aspuru-Guzik, E. E. Kwan, R. G. Gordon, and M. J. Aziz, “Extending the Lifetime of Organic Flow Batteries via Redox State Management,” Journal of the American Chemical Society, 141, 8014 (2019).[5] E. Drazevic, C. Szabo, D. Konya, T. Lund, K. Wedege, and A. Bentien, “Investigation of Tetramorpholinohydroquinone as a Potential Catholyte in a Flow Battery,” ACS Applied Energy Materials, 2, 4745 (2019).[6] Y. Liu, M.-A. Goulet, L. Tong, Y. Liu, Y. Ji, L. Wu, R. G. Gordon, M. J. Aziz, Z. Yang, and T. Xu, “A Long Lifetime All-Organic Aqueous Flow Battery Utilizing TMAP-TEMPO Radical,” Chem, 5, 1 (2019).[7] J. Luo, W. Wu, C. Debruler, B. Hu, M. Hu, and T. L. Liu, “A 1.51 V pH Neutral Redox Flow Battery towards Scalable Energy Storage,” Journal of Materials Chemistry A, 7, 9130 (2019).[8] J. Luo, B. Hu, M. Hu, Y. Zhao, and T. L. Liu, “Status and Prospects of Organic Redox Flow Batteries toward Sustainable Energy Storage,” ACS Energy Letters, 4, 2220 (2019).

Mosaik and PADE: Multiagents and Co-simulation for smart grids modeling

This paper describes the integration process between two tools in order to perform co-simulation for representation and analysis of dynamic environments in the context of smart grids. The integrated tools are Mosaik, a software to co-simulation management, and PADE, a software to multi-agent systems development. As a study case for demonstrate the integration, a scenary was utilized composed of a low voltage electricity distribution grid with 37 load bus, 20 photo-voltaic distributed generations, randomly connected to load bus, as well as, 20 PADE agents associated to distributed generation, modeling the behavior of electricity storage systems. The simulation results show the integration happening and demonstrate how useful is to model the dynamics of distributed electric resources with multi-agent systems.

Evaluating the Economic Benefits of a Smart-Community Microgrid with Centralized Electrical Storage and Photovoltaic Systems

In this paper, an innovative method for managing a smart-community microgrid (SCM) with a centralized electrical storage system (CESS) is proposed. The method consists of day-ahead optimal power flow (DA–OPF) for day-ahead SCM managing and its subsequent evaluation, considering forecast uncertainties. The DA–OPF is based on a data forecast system that uses a deep learning (DL) long short-term memory (LSTM) network. The OPF problem is formulated as a mathematical mixed-integer nonlinear programming (MINLP) model. Following this, the developed DA–OPF strategy was evaluated under possible operations, using a Monte Carlo simulation (MCS). The MCS allowed us to obtain potential deviations of forecasted data during possible day-ahead operations and to evaluate the impact of the data forecast errors on the SCM, and that of unit limitation and the emergence of critical situations. Simulation results on a real existing rural conventional community endowed with a centralized community renewable generation (CCRG) and CESS, confirmed the effectiveness of the proposed operation method. The economic analysis showed significant benefits and an electricity price reduction for the considered community if compared to a conventional distribution system, as well as the easy applicability of the proposed method due to the CESS and the developed operating systems.

A chance-constrained stochastic model predictive control for building integrated with renewable resources

Efficient operation of a building energy system integrated with renewable energy resources is one of the main challenges associated with economic and flexible discussions. This work focuses on a chance-constrained stochastic model predictive control (c-SMPC) based scheme to optimally schedule heating, ventilating and air conditioning system (HVAC) and electric storage system (ESS) coordinately, to enable the highly efficient utilization of solar power and economic energy conservation in the building. Specifically, adaptive control modes provided for HVAC according to the time-varying occupancy status offer the building more energy flexibility whilst maximally guarantee the inside thermal comfort with no physical constraint violation. In addition, the uncertain factors, e.g., environment condition disturbances, are integrated into the optimization model by using affine disturbance feedback and chance constraints formulation, providing the c-SMPC controller with tractability and tunability in its temporal receding optimization process. The case of an office building integrated with solar panels and ESS is studied to validate the proposed method, and results show that the method enables an efficient and cost-effective mechanism of optimally coordinating the energy usage of the building. Compared with the baseline controller, the proposed c-SMPC controller can achieve up to 46.6% energy cost reduction and less comfort violation.

An Exploratory Agent-Based Modeling Analysis Approach to Test Business Models for Electricity Storage

Electricity storage systems (ESSs) are potential solutions to facilitate renewable energy transition. Lack of viable business models, as well as high levels of uncertainty in technology, economic, and institutional factors, form main barriers for wide implementation of ESSs worldwide and in the Netherlands. Therefore, the design of business models for an ESS is necessary for the development of ESSs. We elaborated on this problem before, and developed a design space for business models of ESSs in the context of the Netherlands. This conceptual paper provides a further view on barriers and uncertainties of ESS development in the Netherlands through the involvement of a business practitioner, elaboration of goals, objectives, and testing of ESS business model designs, suggests and provides a theoretical foundation for combining agent-based modeling and exploratory modeling analysis as a method to test and explore ESS business models, and provides an abstract conceptual agent-based model design thereof. This work can be used as a foundation of detailed design and implementation of models for testing ESS business models in the Netherlands and worldwide.

Experiments-Based Comparison of Different Power Controllers for a Solid Oxide Fuel Cell Against Model Imperfections and Delay Phenomena

Solid oxide fuel cell systems such as those presented in this paper are not only applicable for a pure supply with electric energy, they can typically also be used in decentralized power stations, i.e., as micro-cogeneration systems for houses, where both electric and thermal energy are required. For that application, obviously, the electric power need is not constant but rather changes over time. In such a way, it essentially depends on the user profiles of said houses which can refer to e.g., private households as well as offices. The power use is furthermore not predefined. For an optimal operation of the fuel cell, we want to adjust the power, to match the need with sufficiently small time constants without the implementation of mid- or long-term electrical storage systems such as battery buffers. To adapt the produced electric power a simple, however, sufficiently robust feedback controller regulating the hydrogen mass flow into the cells is necessary. To achieve this goal, four different controllers, namely, a PI output-feedback controller combined with a feedforward control, an internal model control (IMC) approach, a sliding-mode (SM) controller and a state-feedback controller, are developed and compared in this paper. As the challenge is to find a controller ensuring steady-state accuracy and good tracking behavior despite the nonlinearities and uncertainties of the plant, the comparison was done regarding these requirements. Simulations and experiments show that the IMC outperforms the alternatives with respect to steady-state accuracy and tracking behavior.

Electrochemical activity of Samarium on starch-derived porous carbon: rechargeable Li- and Al-ion batteries

Rechargeable metal-ion batteries are considered promising electric storage systems to meet the emerging demand from electric vehicles, electronics, and electric grids. Thus far, secondary Li-ion batteries (LIBs) have seen great advances in terms of both their energy and their power density. However, safety issues remain a challenge. Therefore, rechargeable Al-ion batteries (AIBs) with a highly reliable safety advantage and active electrochemical performances have gathered intensive attention. However, the common issue for these two metal-ion batteries is the lack of cathode materials. Many advanced electrode materials reported provide greatly enhanced electrochemical properties. However, their inherent disadvantages—such as complicated fabrication procedures, restricted manufacturing parameters, and the requirement of expensive instruments—limits their potential for further applications. In this work, we demonstrate the high electrochemical activity of the lanthanide element, Sm, towards storing charges when used in both LIBs and AIBs. Lanthanide elements are often overlooked; however, they generally have attractive electrochemical properties owing to their unpaired electrons. We employed starch as both a low-cost carbon source and as a three-dimensional support for Sm metal nanoparticles. The composite product is fabricated using a one-pot wet-chemical method, followed by a simultaneous carbonization process. As a result, highly improved electrochemical properties are obtained when it is used as a cathode material for both LIBs and AIBs when compared to bare starch-derived C. Our results may introduce a new avenue toward the design of high-performance electrode materials for LIBs and AIBs.

High reliability storage systems for genset cranking

In many applications, like hospitals, the reliability of the emergency electrical supply is a critical issue, since the continuity has to be guaranteed at any time. The backup system usually consists of gensets and electrical starters (DC motors), supplied by lead-acid batteries. It is a fact that the latter are responsible for most genset cranking failures occurring in hospitals. Therefore, the reliability of the storage system should be improved to increase the Overall Mean Time Between Failures (MTBF) of the whole backup system. In this paper, eight different electrical storage systems have been modeled and simulated and they have been analyzed and compared from the point of view of reliability; in particular, the possibility of using supercapacitors (together with batteries or even replacing them) has been investigated. A huge number of real data regarding genset failures have been used, from both the literature and direct measurements made on purpose. An accurate statistical analysis has been performed to evaluate the MTBF for batteries, supercapacitors and other components available in the market, considering their actual characteristics. Finally, an innovative hybrid energy storage system has been proposed, based on both batteries and supercapacitors, allowing to triple the MTBF of the cranking storage system.