Sizing Of Energy Storage System Research Articles

Joint optimization of a Microgrid's structure design and its operation using a two-steps evolutionary algorithm

In this paper a novel problem in MGs (Migrogrids) is analyzed. The problem consists in the joint optimization of the MG structure and operation, by obtaining on the one hand an optimal sizing of its elements and structural parameters, and on the other hand the scheduling for the ESS (energy storage system) in the MG. For this joint problem, a novel two-steps EA (evolutionary algorithm) is proposed. The EA operates in such a way that a first EA obtains the best MG structure, mainly the optimal values for the sizing of generators and ESS, and a second EA determines the operational part of the MG (ESS scheduling). A real scenario of variable electricity prices is considered. In this scenario, power demanded from the main grid has different prices depending on the day and the hour of the day when it is demanded. The MG considered in this paper is formed by wind and photovoltaic generators, different residential and industrial loads, as well as ESS. Moreover, four different settings with different natural resource availabilities have been analyzed, and the results obtained show a significant cost improvement in the MG's performance.

Energy Storage System Sizing for Peak Shaving in Thailand

This paper presents a mathematical model of energy storage systems (ESSs) to minimise daily electrical peak power demand in Thailand. A daily electrical load curve on a peak day obtained from Electricity Generating Authority of Thailand (EGAT) is used to analyse the capability of energy storage system for electrical peak power demand reduction with different ESS sizes. It is found that with power rate of 50 percent of the difference between the minimum and the maximum demands of the daily load curve and with energy capacity of 50 percent of the sum of each time step absolute energy difference between the demand and the average demand of the daily load curve, ESS can decrease daily electrical peak demand approximately 7.4 percent and increase daily load factor approximately 9.9 percent.

Reliability improvement in radial electrical distribution network by optimal planning of energy storage systems

This paper provides an optimal approach to denote the location and size of ESSs (energy storage systems) with the intention of reliability improvement in radial electrical distribution networks. The proposed optimal ESSs planning is addressed as a minimization problem which aims at minimizing the cost of ENS (energy not supplied) as well as ESSs costs at the same time, subject to safe operation of the network; where, the safe operation is guaranteed through satisfying security constraints such as voltage and line-flows limits. The minimization problem is mathematically formulated as a mixed-integer nonlinear programming and solved by PSO (particle swarm optimization) algorithm. A comprehensive sensitivity analysis is carried out on the results such as ESSs numbers, ESSs cost and reliability parameters. Simulation results demonstrate the viability of the proposed method in the real networks. Results also indicate the positive impact of ESSs on the network reliability. The proposed ESSs planning significantly reduces the ENS of the network and can be employed to deal with low reliability issues in the real networks.

Optimal Tilt Angle of Photovoltaic Arrays and Economic Allocation of Energy Storage System on Large Oil Tanker Ship

This study optimizes the tilt angle of photovoltaic (PV) panels on a large oil tanker ship system and considers the impact of partial shading to improve the performance of the PV system. This work presents a novel method that considers the difference between the expected and real outputs of PV modules to optimize the size of energy storage system (ESS). The method also takes into account the cost of wasted power, the capital cost of the system, fuel cost and the CO2 emissions. Unlike on land, power generation using a PV on a ship depends on the date, latitude and longitude of the navigation. Accordingly, this work considers a route from Dalian in China to Aden in Yemen, accounting for the seasonal and geographical variations of solar irradiation. This proposed method adopts five conditions associated with the navigation route to model the total shipload. Various cases are discussed in detail to demonstrate the effectiveness of the proposed algorithm.

Influence of heat dumping on the operation of residential micro-CHP systems

This work deals with the effects of the heat dumping on the operation of four residential micro-CHP (combined heat and power) systems, each composed of a prime mover producing electricity and heat, a thermal energy storage system and an auxiliary boiler. The micro-CHP systems differ from one another on the prime mover, while the same multi-apartment housing situated in Italy has been considered as user. Four natural gas fueled commercial prime movers have been considered, two internal combustion engines and two microturbines, characterized by different electric and thermal powers. For each micro-CHP system, two heat-driven operation strategies, one with heat dumping and one without have been implemented by means of a home-made numerical code developed in Matlab environment, and in both the cases the economic optimization of the operation has been performed using the pattern search algorithm. For each analyzed case, the results are reported in terms of prime mover operating hours, thermal and electrical energy production, natural gas consumption, primary energy and economic savings with respect to separate generation of electricity and heat, and pollutants emission. The results of an economic analysis are also reported. The effects of the variation of the maximum capacity of the thermal energy storage system, and of the auxiliary boiler efficiency on the optimization results are analyzed, and the results relative to the two different operation strategies are compared and discussed. The major result of this study is that, for all the analyzed micro-CHP systems, an optimized application of heat dumping in the micro-CHP system operation permit to considerably reduce the size of the thermal energy storage system with respect to the heat-driven operation strategy without heat dumping.

A Stochastic Sizing Approach for Sharing-Based Energy Storage Applications

In order to foster renewable energy integration, improve power quality and reliability, and reduce hydrocarbon emissions, there is a strong need to deploy energy storage systems (ESSs), which can provide a control medium for peak hour utility operations. ESSs are especially desired at the residential level, as this sector has the most untapped demand response potential. However, considering their high acquisition, operation, and maintenance costs, individual ESS deployment is not economically viable. Hence, in this paper, we propose a \emph{sharing-based} ESS architecture, in which the demand of each customer is modeled stochastically and the aggregate demand is accommodated by a combination of power drawn from the grid and the storage unit when the demand exceeds grid capacity. Stochastic framework for analyzing the optimal size of energy storage systems is provided. An analytical method is developed for a group customers with \emph{single} type of appliances. Then, this framework is extended to any network size with arbitrary number of customers and appliance types. The analytical method provides a tractable solution to the ESS sizing problem. Finally, a detailed cost-benefit analysis is provided, and the results indicate that sharing-based ESSs are practical and significant savings in terms of ESS size can be achieved.

An Enhanced Voltage Sag Compensation Scheme for Dynamic Voltage Restorer

This paper deals with improving the voltage quality of sensitive loads from voltage sags using a dynamic voltage restorer (DVR). The higher active power requirement associated with voltage phase jump compensation has caused a substantial rise in size and cost of the dc link energy storage system of DVR. The existing control strategies either mitigate the phase jump or improve the utilization of dc link energy by the following: 1) reducing the amplitude of the injected voltage or 2) optimizing the dc bus energy support. In this paper, an enhanced sag compensation strategy is proposed, which mitigates the phase jump in the load voltage while improving the overall sag compensation time. An analytical study shows that the proposed method significantly increases the DVR sag support time (more than 50%) compared with the existing phase jump compensation methods. This enhancement can also be seen as a considerable reduction in dc link capacitor size for new installation. The performance of the proposed method is evaluated using simulation study and finally verified experimentally on a scaled laboratory prototype.

Transcap: A New Integrated Hybrid Supercapacitor and Electrolyte-Gated Transistor Device

The recent boom in multifunction, light and flexible portable electronic equipment and the increasing need of low-energy cost and autonomy for different fields ranging from wireless sensor networks for smart environments to biomedical applications are triggering intensive research efforts towards the development of self-powered, sustainable electronic devices. Within this context, the coupling of electronic devices (sensors,transistors, etc.) with small size energy storage systems (e.g. micro-batteries or micro-supercapacitors) is actively pursued. Micro-electrochemical supercapacitors are attracting much attention in electronics for their capability of delivering short power pulses with high stability over repeated charge/discharge cycling. One of the strategy which is pursued to increase the energy storage capability of supercapacitor is coupling electrode materials of different nature that are charged/discharged via different electrostatic and faradic modes in a hybrid configuration. The use of wide electrochemically stability electrolytes like ionic liquids, permits to achieve high cell voltage and , hence high energy. For their high specific pseudocapacitance, electronically conducting polymers are well known as positive materials for hybrid supercapacitors featuring high surface carbon negative electrodes. The processability of both polymer and carbon is of great relevance for the development of flexible miniaturised devices. Electronically conducting polymers are even well known to feature an electronic conductivity that depends on their oxidation (p-doped state) and that it is modulated by the polymer potential. This property and the related pseudocapacitive response make polymer very attracting channel materials for electrolyte-gated (EG) transistors. In this systems electrolytes replace conventional gate dielectrics and permit low-voltage operation, which in turn makes EG transistors attractive candidates to be coupled to energy harvester/storage microsystems. Here, we propose a novel concept of “Trans-capacitor”, an integrated device that exhibits the storage properties of a polymer/carbon hybrid supercapacitor and the low-voltage operation of an electrolyte-gated transistor. When the TransCap is ON, the polymer transistor channel is open. The p-doped polymer and the negatively polarized carbon gate electrode are storing the charge at a given gate-source voltage, hence the system is storing energy. When the TransCap is switched OFF, the channel and the gate are discharged and the delivered energy can be used for subsequent operation of the EG transistor itself or to power other components in the electronic system. This multifunctionality should positively impact on energy saving in the multicomponent electronic system where the TransCap will be used [1]. The performance of a TransCap based on a polymer channel like MEH-PPV, poly[2-methoxy-5-(20-ethylhexyloxy)-1,4-phenylene vinylene], a high surface area carbon gate, and the ionic liquid N-trimethyl-N-propylammonium bis (trifuoromethanesulfonyl) imide electrolyte are here reported and discussed. ACKNOWLEDGEMENTS This work was financially supported by NSERC (Discovery grants, CS and FC) and FQRNT (Nouveau Chercheur, CS). JS acknowledges fiancial support by CONACYT and CMC Microsystems. FS acknowledges financial support by Università di Bologna (Researcher Mobility Program, Italian-Canadian cooperation agreement). [1] J. Sayago, U. Shafique, F. Soavi, F. Cicoira and C. Santato, J. Mater. Chem. C, DOI: 10.1039/c4tc02119c

Probabilistic ESS sizing and scheduling for improved integration of PHEVs and PV systems in residential distribution systems

Environmental concerns and oil price volatility have created increased interest in smart grid green energy technologies such as photovoltaic (PV) arrays and plug-in hybrid electric vehicles (PHEVs). However, these technologies have been found to have a significant impact on distribution networks in terms of secondary distribution transformer overloading and increased reverse power flow. Energy storage systems (ESSs) are thought to be an effective tool for mitigating these negative effects. The primary challenge in implementing ESS technology lies in the difficulty of determining the appropriate sizes and operating schedules for these units, given the uncertainties inherent in PV array production and PHEV demand. This paper presents a probabilistic sizing and scheduling methodology for ESSs to facilitate the integration of PHEVs and PV arrays in distribution networks, taking into account different sources of uncertainty present in the system. The technical and economic feasibility of the proposed design methodology has been validated using Monte Carlo (MC) simulations for a variety of scenarios.

Advanced Control Solutions for Operating Isolated Power Systems: Examining the Portuguese islands

The operation of remote and isolated or islanded power systems is often very challenging because of their small system inertia. Moreover, economic and environmental pressure has led to an increasing renewable power penetration, particularly in wind generation and solar photovoltaics (PV). Simultaneously, significant technological progress has been made in terms of control capability of grid assets [generators, controllable loads such as electric vehicles (EVs), and energy storage systems], mostly exploiting the capabilities of power electronics. In this context, several advanced control solutions can be implemented, supporting and improving the robustness of the operation in terms of fast frequency and voltage control responses. In this article, the Portuguese islands are taken as a case study. Within the Madeira archipelago (Porto Santo and Madeira islands), two approaches were envisioned. For Porto Santo Island, the main goal is the sizing of a flywheel energy storage system (FESS) to avoid frequency stability problems. For Madeira Island, the objective relies on the exploitation of hydro resources through the quantification of the technical benefits resulting from variable speed hydro pumping stations that are able to provide primary frequency regulation services in the pump operation mode. In addition, this article also addresses the benefits of introducing EVs in Flores Island in the Azores Archipelago. Finally, to support the development of innovative technological solutions for this type of power system, a laboratory setup based on scaled test systems was also set up and is described. A set of applications was specifically developed for such autonomous power systems. The laboratorial infrastructure allowed the testing of solutions and prototypes for hardware and software modules related to those applications.

Value of the energy storage system in an electric bus fast charging station

Electric buses (EBs) are undergoing rapid development because of their environmental friendliness. Different from private electric vehicles, EBs are scheduled by a public transport company and required to be charged as soon as possible during operation hours. Consequently, the implementation of fast charging stations (FCSs) is essential to support the operation of EBs. Usually, the size of an FCS is constrained by the residual capacity of the connected distribution network and the investment budget. An energy storage system (ESS) is considered as a potential supplement not only to reduce the network integration cost for FCSs but also to reduce the charging cost of EBs through electricity price arbitrage. To quantify the value of ESS in an electric bus FCS, a mixed integer nonlinear programming (MINLP) formulation for optimal sizing and control of FCS and ESS is built. A simplification method is proposed to convert the MINLP problem to a linear one without any loss in optimality, which accelerates the solving process. Simulations are performed based on historical data of a practical FCS. Numerical results indicate that ESS can significantly help reduce the overall investment and charging cost of the FCS. Meanwhile, the parameters of investment cost, lifespan and time-of-use electricity price have significant influences on the overall value of ESS for an FCS.

Optimal design of hybrid renewable energy systems using simulation optimization

A hybrid renewable energy system (HRES) provides a viable solution for electrification of remote areas when grid extension is impossible or uneconomical. Such a system has several power stations and each of which includes photovoltaics (PV) and wind power generators, along with a diesel power generator as backup when renewable energy supply is insufficient. While the HRES is attractive due to the minimal environmental and health impact compared to fossil fuels, the design of HRES, specifically the determination of the size of PV, wind, and diesel power generators and the size of energy storage system in each power station, is very challenging. This is mainly due to a large number of factors involved in the problem, the profound uncertainty arising from the renewable resources and the demand load, and the complex interaction among factors. In this paper, we investigate the use of Monte Carlo simulation, along with simulation optimization techniques, for obtaining the optimal design of HRES in uncertain environments. The proposed model considers not only the equipment installation, including PV, wind and diesel power generators and the energy storage systems in each power station, but also the power generation, allocation and transmission within the HRES so as to achieve minimum expected total cost, while satisfying the power demand. An extensive computational study shows that the proposed model of realistic size can be solved efficiently, enabling quality decisions to be generated in practice.

A method for optimal sizing energy storage systems for microgrids

This paper proposes a genetic algorithm-based method for sizing the energy storage system (ESS) in microgrids. The main goal of the proposed method is to find the energy and power capacities of the storage system that minimizes the operating cost of the microgrid. The energy management strategy (EMS) used in this paper is based on a fuzzy expert system which is responsible for setting the power output of the ESS. The design of the EMS is carried out by means of a genetic algorithm that is used to set the fuzzy rules and membership functions of the expert system. Given that the size of the storage system has a major influence on the energy management strategy, in this paper the EMS and ESS capacities are jointly optimized. In addition, the proposed method uses an aging model to predict the lifetime of the ESS. In this way it is possible to determine the cost associated with energy storage in a more precise manner. The unit commitment problem, which is crucial for the proper operation of the microgrid, has been also considered in the present work. The suggested sizing methodology has been validated in two case studies.

Modeling Analysis and Improvement of Power Loss in Microgrid

The consumption of conventional energy sources and environmental concerns have resulted in rapid growth in the amount of renewable energy introduced to power systems. With the help of distributed generations (DG), the improvement of power loss and voltage profile can be the salient benefits. However, studies show that improper placement and size of energy storage system (ESS) lead to undesired power loss and the risk of voltage stability, especially in the case of high renewable energy penetration. To solve the problem, this paper sets up a microgrid based on IEEE 34-bus distribution system which consists of wind power generation system, photovoltaic generation system, diesel generation system, and energy storage system associated with various types of load. Furthermore, the particle swarm optimization (PSO) algorithm is proposed in the paper to minimize the power loss and improve the system voltage profiles by optimally managing the different sorts of distributed generations under consideration of the worst condition of renewable energy production. The established IEEE 34-bus system is adopted to perform case studies. The detailed simulation results for each case clearly demonstrate the necessity of optimal management of the system operation and the effectiveness of the proposed method.

Spatiotemporal Modeling of Wind Generation for Optimal Energy Storage Sizing

Ever increasing penetration of wind power generation along with the integration of energy storage systems (ESSs) makes the successive states of the power system interdependent and more stochastic. Appropriate stochastic modeling of wind power is required to deal with the existence of uncertainty either in observations of the data (spatial) or in the characteristics that drive the evolution of the data (temporal). Particularly, for capturing spatiotemporal interdependencies and determining energy storage requirements, this paper proposes a versatile model using advanced statistical modeling based on the vine-copula theory. To tackle the complexity and computational burden of modeling high-dimensional wind data, a systematic truncation method is utilized that significantly reduces computational burden of the method while preserving the required accuracy. By constructing a graphical dependency model, unlike existing autoregressive and Markov chain models, the proposed method can replicate the exact autocorrelation function (ACF) and cross-correlation function (CCF), while retaining the correct distribution of the original data as well as the effective dependence between different sites under study. The practical importance of the proposed model is demonstrated through an example of ESS sizing for wind power.

Solar Power Shaping: An Analytical Approach

The focus of our work is the use of an energy storage system (ESS) to integrate solar energy generators into the electrical grid. Although, in theory, an ESS allows intermittent solar power to be shaped to meet any desired load profile, in practice, parsimonious ESS dimensioning is challenging due to the stochastic nature of generation and load and the diversity and high cost of storage technologies. Existing methods for ESS sizing are based either on simulation or on analysis, both of which have shortcomings. Simulation methods are computationally expensive and depend on the availability of extensive data traces. Existing analytical methods tend to be conservative, overestimating expensive storage requirements. Our key insight is that solar power fluctuations arise at a few distinct time scales. We separately model fluctuations in each time scale, which allows us to accurately estimate ESS performance and efficiently size an ESS. Numerical examples with real data traces show that our model and analysis are tight.

Control and Size Energy Storage Systems for Managing Energy Imbalance of Variable Generation Resources

This paper presents control algorithms and sizing strategies for using energy storage to manage energy imbalance for variable generation resources. The control objective is to minimize the hourly generation imbalance between the actual and the scheduled generation of wind farms. Three control algorithms are compared: 1)tracking minute-by-minute power imbalance; 2)postcompensation; and 3)precompensation. Measured data from a wind farm are used in the study. The results show that tracking minute-by-minute power imbalance achieves the best performance by keeping hourly energy imbalance zero. However, the energy storage system (ESS) will be significantly oversized. Postcompensation reduces the power rating of the ESS but the hourly energy imbalance may not be reduced to zero when a large and long-lasting power imbalance occurs. A linear regression forecasting algorithm is developed for a two-stage precompensation algorithm to precharge or predischarge the ESS based on the predicted energy imbalance. An equivalent charge cycle estimation method is proposed to evaluate the effect of providing the energy balancing service on battery life. The performance comparison shows that the precompensation method reduces the size of the ESS by 30% with satisfactory performance.

Optimization of Sizing and Battery Cycle Life in Battery/Ultracapacitor Hybrid Energy Storage Systems for Electric Vehicle Applications

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/ discharging cycles during acceleration and deceleration periods, particularly in Urban driving conditions. Oversized energy storage system (ESS) meets the high power demand; however, in tradeoff with increased ESS size, volume, and cost. In order to reduce overall ESS size and extend battery cycle life, battery/ultracapacitor (UC) hybrid ESS (HESS) has been considered as a solution in which UCs act as a power buffer to charging/discharging peak power. In this paper, a multiobjective optimization problem is formulated to minimize the overall ESS size, while maximizing the battery cycle life according to the assigned penalty functions. An integrated framework for HESS sizing and battery cycle life optimization applied in a midsize EV, using an Autonomie simulation model, is described and illustrated in this paper. This multidimensional optimization is realized by a sample-based global search oriented DIviding RECTangles (DIRECT) algorithm. The optimization results under Urban Dynamometer Driving Schedule (UDDS) are compared with the battery-only ESS results, which demonstrate significant battery cycle life extension of 76% achieved by the optimized HESS with 72 UC cells.

Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants

This paper proposes a methodology for the economic optimisation of the sizing of Energy Storage Systems (ESSs) whilst enhancing the participation of Wind Power Plants (WPP) in network primary frequency control support. The methodology was designed flexibly, so it can be applied to different energy markets and to include different ESS technologies. The methodology includes the formulation and solving of a Linear Programming (LP) problem.The methodology was applied to the particular case of a 50MW WPP, equipped with a Vanadium Redox Flow battery (VRB) in the UK energy market. Analysis is performed considering real data on the UK regular energy market and the UK frequency response market. Data for wind power generation and energy storage costs are estimated from literature.Results suggest that, under certain assumptions, ESSs can be profitable for the operator of a WPP that is providing frequency response. The ESS provides power reserves such that the WPP can generate close to the maximum energy available. The solution of the optimisation problem establishes that an ESS with a power rating of 5.3MW and energy capacity of about 3MWh would be enough to provide such service whilst maximising the incomes for the WPP operator considering the regular and frequency regulation UK markets.

Influence of the energy management on the sizing of Electrical Energy Storage Systems in an aircraft

In an aircraft, Electrical Energy Storage Systems (EESS) are used as support to other sources in few mission phases in order to ensure the energy availability. They are also used as electrical smoothing devices in order to guarantee the required levels of reliability, stability and quality for an embedded electrical network. This paper deals with the association of two EESS: supercapacitors and secondary battery, which exhibit complementary properties. In this paper, a sizing method for both EESS is developed by taking into account their hybridization and their characteristics (such as capacity or depth-of-discharge) so as to minimize the global storage system weight. Moreover, an energy management based on a frequency approach is implemented to dispatch the power between all the sources. The influence of this management on the sizing is studied. Indeed the cut-off frequency of the low-pass filter is used as a setting parameter of the sizing algorithm. Finally, the sizing validity is assessed and discussed according to temperature constraints. Although battery performances are reduced at low temperature, the sizing determined with the algorithm at 20 °C is still valid on all the temperature range thanks to an adaptation of the energy management parameter.