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5 pages, 669 KiB

Open AccessEditorial

Control of Energy Storage

by Timur Yunusov, Maximilian J. Zangs and William Holderbaum

Energies 2017, 10(7), 1010; https://doi.org/10.3390/en10071010 - 16 Jul 2017

Cited by 2 | Viewed by 4077

Abstract

In the attempt to tackle the issue of climate change, governments across the world have agreed to set global carbon reduction targets. [...] Full article

(This article belongs to the Special Issue Control of Energy Storage)

Research

Jump to: Editorial

22 pages, 13827 KiB

Open AccessArticle

Integrated Equivalent Circuit and Thermal Model for Simulation of Temperature-Dependent LiFePO₄ Battery in Actual Embedded Application

by Zuchang Gao, Cheng Siong Chin, Wai Lok Woo and Junbo Jia

Energies 2017, 10(1), 85; https://doi.org/10.3390/en10010085 - 11 Jan 2017

Cited by 60 | Viewed by 11223

Abstract

A computational efficient battery pack model with thermal consideration is essential for simulation prototyping before real-time embedded implementation. The proposed model provides a coupled equivalent circuit and convective thermal model to determine the state-of-charge (SOC) and temperature of the LiFePO₄ battery working [...] Read more.

A computational efficient battery pack model with thermal consideration is essential for simulation prototyping before real-time embedded implementation. The proposed model provides a coupled equivalent circuit and convective thermal model to determine the state-of-charge (SOC) and temperature of the LiFePO₄ battery working in a real environment. A cell balancing strategy applied to the proposed temperature-dependent battery model balanced the SOC of each cell to increase the lifespan of the battery. The simulation outputs are validated by a set of independent experimental data at a different temperature to ensure the model validity and reliability. The results show a root mean square (RMS) error of 1.5609 × 10⁻⁵ for the terminal voltage and the comparison between the simulation and experiment at various temperatures (from 5 °C to 45 °C) shows a maximum RMS error of 7.2078 × 10⁻⁵. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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13 pages, 2481 KiB

Open AccessArticle

Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

by Jin-Sun Yang, Jin-Young Choi, Geon-Ho An, Young-Jun Choi, Myoung-Hoe Kim and Dong-Jun Won

Energies 2016, 9(12), 1010; https://doi.org/10.3390/en9121010 - 30 Nov 2016

Cited by 14 | Viewed by 5205

Abstract

An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an [...] Read more.

An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO) method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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14 pages, 738 KiB

Open AccessArticle

The Demand Side Management Potential to Balance a Highly Renewable European Power System

by Alexander Kies, Bruno U. Schyska and Lueder Von Bremen

Energies 2016, 9(11), 955; https://doi.org/10.3390/en9110955 - 15 Nov 2016

Cited by 50 | Viewed by 7126

Abstract

Shares of renewables continue to grow in the European power system. A fully renewable European power system will primarily depend on the renewable power sources of wind and photovoltaics (PV), which are not dispatchable but intermittent and therefore pose a challenge to the [...] Read more.

Shares of renewables continue to grow in the European power system. A fully renewable European power system will primarily depend on the renewable power sources of wind and photovoltaics (PV), which are not dispatchable but intermittent and therefore pose a challenge to the balancing of the power system. To overcome this issue, several solutions have been proposed and investigated in the past, including storage, backup power, reinforcement of the transmission grid, and demand side management (DSM). In this paper, we investigate the potential of DSM to balance a simplified, fully renewable European power system. For this purpose, we use ten years of weather and historical load data, a power-flow model and the implementation of demand side management as a storage equivalent, to investigate the impact of DSM on the need for backup energy. We show that DSM has the potential to reduce the need for backup energy in Europe by up to one third and can cover the need for backup up to a renewable share of 67%. Finally, it is demonstrated that the optimal mix of wind and PV is shifted by the utilisation of DSM towards a higher share of PV, from 19% to 36%. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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16 pages, 7281 KiB

Open AccessArticle

Application of a LiFePO₄ Battery Energy Storage System to Primary Frequency Control: Simulations and Experimental Results

by Fabio Massimo Gatta, Alberto Geri, Regina Lamedica, Stefano Lauria, Marco Maccioni, Francesco Palone, Massimo Rebolini and Alessandro Ruvio

Energies 2016, 9(11), 887; https://doi.org/10.3390/en9110887 - 29 Oct 2016

Cited by 30 | Viewed by 7293

Abstract

This paper presents an experimental application of LiFePO₄ battery energy storage systems (BESSs) to primary frequency control, currently being performed by Terna, the Italian transmission system operator (TSO). BESS performance in the primary frequency control role was evaluated by means of a [...] Read more.

This paper presents an experimental application of LiFePO₄ battery energy storage systems (BESSs) to primary frequency control, currently being performed by Terna, the Italian transmission system operator (TSO). BESS performance in the primary frequency control role was evaluated by means of a simplified electrical-thermal circuit model, taking into account also the BESS auxiliary consumptions, coupled with a cycle-life model, in order to assess the expected life of the BESS. Numerical simulations have been carried out considering the system response to real frequency measurements taken in Italy, spanning a whole year; a parametric study taking into account different values of governor droop and of BESS charge/discharge rates (C-rates) was also performed. Simulations, fully validated by experimental results obtained thus far, evidenced a severe trade-off between expected lifetime and overall efficiency, which significantly restricts the choice of operating parameters for frequency control. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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16 pages, 956 KiB

Open AccessArticle

Energy Link Optimization in a Wireless Power Transfer Grid under Energy Autonomy Based on the Improved Genetic Algorithm

by Zhihao Zhao, Yue Sun, Aiguo Patrick Hu, Xin Dai and Chunsen Tang

Energies 2016, 9(9), 682; https://doi.org/10.3390/en9090682 - 26 Aug 2016

Cited by 7 | Viewed by 5416

Abstract

In this paper, an optimization method is proposed for the energy link in a wireless power transfer grid, which is a regional smart microgrid comprised of distributed devices equipped with wireless power transfer technology in a certain area. The relevant optimization model of [...] Read more.

In this paper, an optimization method is proposed for the energy link in a wireless power transfer grid, which is a regional smart microgrid comprised of distributed devices equipped with wireless power transfer technology in a certain area. The relevant optimization model of the energy link is established by considering the wireless power transfer characteristics and the grid characteristics brought in by the device repeaters. Then, a concentration adaptive genetic algorithm (CAGA) is proposed to optimize the energy link. The algorithm avoided the unification trend by introducing the concentration mechanism and a new crossover method named forward order crossover, as well as the adaptive parameter mechanism, which are utilized together to keep the diversity of the optimization solution groups. The results show that CAGA is feasible and competitive for the energy link optimization in different situations. This proposed algorithm performs better than its counterparts in the global convergence ability and the algorithm robustness. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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20 pages, 6414 KiB

Open AccessArticle

Distributed Energy Storage Control for Dynamic Load Impact Mitigation

by Maximilian J. Zangs, Peter B. E. Adams, Timur Yunusov, William Holderbaum and Ben A. Potter

Energies 2016, 9(8), 647; https://doi.org/10.3390/en9080647 - 17 Aug 2016

Cited by 13 | Viewed by 5924

Abstract

The future uptake of electric vehicles (EV) in low-voltage distribution networks can cause increased voltage violations and thermal overloading of network assets, especially in networks with limited headroom at times of high or peak demand. To address this problem, this paper proposes a [...] Read more.

The future uptake of electric vehicles (EV) in low-voltage distribution networks can cause increased voltage violations and thermal overloading of network assets, especially in networks with limited headroom at times of high or peak demand. To address this problem, this paper proposes a distributed battery energy storage solution, controlled using an additive increase multiplicative decrease (AIMD) algorithm. The improved algorithm (AIMD+) uses local bus voltage measurements and a reference voltage threshold to determine the additive increase parameter and to control the charging, as well as discharging rate of the battery. The used voltage threshold is dependent on the network topology and is calculated using power flow analysis tools, with peak demand equally allocated amongst all loads. Simulations were performed on the IEEE LV European Test feeder and a number of real U.K. suburban power distribution network models, together with European demand data and a realistic electric vehicle charging model. The performance of the standard AIMD algorithm with a fixed voltage threshold and the proposed AIMD+ algorithm with the reference voltage profile are compared. Results show that, compared to the standard AIMD case, the proposed AIMD+ algorithm further improves the network’s voltage profiles, reduces thermal overload occurrences and ensures a more equal battery utilisation. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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18 pages, 3270 KiB

Open AccessArticle

A Novel Power-Saving Transmission Scheme for Multiple-Component-Carrier Cellular Systems

by Yao-Liang Chung

Energies 2016, 9(4), 265; https://doi.org/10.3390/en9040265 - 2 Apr 2016

Cited by 5 | Viewed by 4607

Abstract

As mobile data traffic levels have increased exponentially, resulting in rising energy costs in recent years, the demand for and development of green communication technologies has resulted in various energy-saving designs for cellular systems. At the same time, recent technological advances have allowed [...] Read more.

As mobile data traffic levels have increased exponentially, resulting in rising energy costs in recent years, the demand for and development of green communication technologies has resulted in various energy-saving designs for cellular systems. At the same time, recent technological advances have allowed multiple component carriers (CCs) to be simultaneously utilized in a base station (BS), a development that has made the energy consumption of BSs a matter of increasing concern. To help address this concern, herein we propose a novel scheme aimed at efficiently minimizing the power consumption of BS transceivers during transmission, while still ensuring good service quality and fairness for users. Specifically, the scheme utilizes the dynamic activation/deactivation of CCs during data transmission to increase power usage efficiency. To test its effectiveness, the proposed scheme was applied to a model consisting of a BS with orthogonal frequency division multiple access-based CCs in a downlink transmission environment. The results indicated that, given periods of relatively light traffic loads, the total power consumption of the proposed scheme is significantly lower than that of schemes in which all the CCs of a BS are constantly activated, suggesting the scheme’s potential for reducing both energy costs and carbon dioxide emissions. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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20 pages, 5313 KiB

Open AccessArticle

Analysis of a Battery Management System (BMS) Control Strategy for Vibration Aged Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 Battery Cells

by Thomas Bruen, James Michael Hooper, James Marco, Miguel Gama and Gael Henri Chouchelamane

Energies 2016, 9(4), 255; https://doi.org/10.3390/en9040255 - 1 Apr 2016

Cited by 24 | Viewed by 9952

Abstract

Electric vehicle (EV) manufacturers are using cylindrical format cells as part of the vehicle’s rechargeable energy storage system (RESS). In a recent study focused at determining the ageing behavior of 2.2 Ah Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 battery cells, significant increases [...] Read more.

Electric vehicle (EV) manufacturers are using cylindrical format cells as part of the vehicle’s rechargeable energy storage system (RESS). In a recent study focused at determining the ageing behavior of 2.2 Ah Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 battery cells, significant increases in the ohmic resistance (R_O) were observed post vibration testing. Typically a reduction in capacity was also noted. The vibration was representative of an automotive service life of 100,000 miles of European and North American customer operation. This paper presents a study which defines the effect that the change in electrical properties of vibration aged 18650 NMC cells can have on the control strategy employed by the battery management system (BMS) of a hybrid electric vehicle (HEV). It also proposes various cell balancing strategies to manage these changes in electrical properties. Subsequently this study recommends that EV manufacturers conduct vibration testing as part of their cell selection and development activities so that electrical ageing characteristics associated with road induced vibration phenomena are incorporated to ensure effective BMS and RESS performance throughout the life of the vehicle. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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18 pages, 10184 KiB

Open AccessArticle

Control Strategies with Dynamic Threshold Adjustment for Supercapacitor Energy Storage System Considering the Train and Substation Characteristics in Urban Rail Transit

by Fei Lin, Xuyang Li, Yajie Zhao and Zhongping Yang

Energies 2016, 9(4), 257; https://doi.org/10.3390/en9040257 - 31 Mar 2016

Cited by 31 | Viewed by 8193

Abstract

Recuperation of braking energy offers great potential for reducing energy consumption in urban rail transit systems. The present paper develops a new control strategy with variable threshold for wayside energy storage systems (ESSs), which uses the supercapacitor as the energy storage device. First, [...] Read more.

Recuperation of braking energy offers great potential for reducing energy consumption in urban rail transit systems. The present paper develops a new control strategy with variable threshold for wayside energy storage systems (ESSs), which uses the supercapacitor as the energy storage device. First, the paper analyzes the braking curve of the train and the V-I characteristics of the substation. Then, the current-voltage dual-loop control method is used for ESSs. Next, in order to achieve the best energy-saving effect, the paper discusses the selection principle of the charge and discharge threshold. This paper proposes a control strategy for wayside supercapacitors integrated with dynamic threshold adjustment control on the basis of avoiding the onboard braking chopper’s operation. The proposed control strategy is very useful for obtaining good performance, while not wasting any energy in the braking resistor. Therefore, the control strategy has been verified through simulations, and experimental tests, have been implemented on the Batong Line of Beijing subway using the 200 kW wayside supercapacitor energy storage prototype. The experimental results show that the proposed control is capable of saving energy and considerably reducing energy consumption in the braking resistor during train braking. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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17 pages, 1575 KiB

Open AccessEditor’s ChoiceArticle

Optimal Power Management Strategy for Energy Storage with Stochastic Loads

by Stefano Pietrosanti, William Holderbaum and Victor M. Becerra

Energies 2016, 9(3), 175; https://doi.org/10.3390/en9030175 - 9 Mar 2016

Cited by 23 | Viewed by 8420

Abstract

In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary [...] Read more.

In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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13 pages, 1254 KiB

Open AccessArticle

Distributed Energy Storage Using Residential Hot Water Heaters

by Linas Gelažanskas and Kelum A. A. Gamage

Energies 2016, 9(3), 127; https://doi.org/10.3390/en9030127 - 25 Feb 2016

Cited by 20 | Viewed by 6805

Abstract

This paper proposes and analyses a new demand response technique for renewable energy regulation using smart hot water heaters that forecast water consumption at an individual dwelling level. Distributed thermal energy storage has many advantages, including high overall efficiency, use of existing infrastructure [...] Read more.

This paper proposes and analyses a new demand response technique for renewable energy regulation using smart hot water heaters that forecast water consumption at an individual dwelling level. Distributed thermal energy storage has many advantages, including high overall efficiency, use of existing infrastructure and a distributed nature. In addition, the use of a smart thermostatic controller enables the prediction of required water amounts and keeps temperatures at a level that minimises user discomfort while reacting to variations in the electricity network. Three cases are compared in this paper, normal operation, operation with demand response and operation following the proposed demand response mechanism that uses consumption forecasts. The results show that this technique can produce both up and down regulation, as well as increase water heater efficiency. When controlling water heaters without consumption forecast, the users experience discomfort in the form of hot water shortage, but after the full technique is applied, the shortage level drops to nearly the starting point. The amount of regulation power from a single dwelling is also discussed in this paper. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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20 pages, 1558 KiB

Open AccessArticle

A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs

by Enrico Telaretti, Mariano Ippolito and Luigi Dusonchet

Energies 2016, 9(1), 12; https://doi.org/10.3390/en9010012 - 25 Dec 2015

Cited by 38 | Viewed by 8008

Abstract

Price arbitrage involves taking advantage of an electricity price difference, storing electricity during low-prices times, and selling it back to the grid during high-prices periods. This strategy can be exploited by customers in presence of dynamic pricing schemes, such as hourly electricity prices, [...] Read more.

Price arbitrage involves taking advantage of an electricity price difference, storing electricity during low-prices times, and selling it back to the grid during high-prices periods. This strategy can be exploited by customers in presence of dynamic pricing schemes, such as hourly electricity prices, where the customer electricity cost may vary at any hour of day, and power consumption can be managed in a more flexible and economical manner, taking advantage of the price differential. Instead of modifying their energy consumption, customers can install storage systems to reduce their electricity bill, shifting the energy consumption from on-peak to off-peak hours. This paper develops a detailed storage model linking together technical, economic and electricity market parameters. The proposed operating strategy aims to maximize the profit of the storage owner (electricity customer) under simplifying assumptions, by determining the optimal charge/discharge schedule. The model can be applied to several kinds of storages, although the simulations refer to three kinds of batteries: lead-acid, lithium-ion (Li-ion) and sodium-sulfur (NaS) batteries. Unlike literature reviews, often requiring an estimate of the end-user load profile, the proposed operation strategy is able to properly identify the battery-charging schedule, relying only on the hourly price profile, regardless of the specific facility’s consumption, thanks to some simplifying assumptions in the sizing and the operation of the battery. This could be particularly useful when the customer load profile cannot be scheduled with sufficient reliability, because of the uncertainty inherent in load forecasting. The motivation behind this research is that storage devices can help to lower the average electricity prices, increasing flexibility and fostering the integration of renewable sources into the power system. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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23 pages, 1674 KiB

Open AccessArticle

Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm

by Huan Xia, Huaixin Chen, Zhongping Yang, Fei Lin and Bin Wang

Energies 2015, 8(10), 11618-11640; https://doi.org/10.3390/en81011618 - 16 Oct 2015

Cited by 80 | Viewed by 8071

Abstract

The installation of stationary super-capacitor energy storage system (ESS) in metro systems can recycle the vehicle braking energy and improve the pantograph voltage profile. This paper aims to optimize the energy management, location, and size of stationary super-capacitor ESSes simultaneously and obtain the [...] Read more.

The installation of stationary super-capacitor energy storage system (ESS) in metro systems can recycle the vehicle braking energy and improve the pantograph voltage profile. This paper aims to optimize the energy management, location, and size of stationary super-capacitor ESSes simultaneously and obtain the best economic efficiency and voltage profile of metro systems. Firstly, the simulation platform of an urban rail power supply system, which includes trains and super-capacitor energy storage systems, is established. Then, two evaluation functions from the perspectives of economic efficiency and voltage drop compensation are put forward. Ultimately, a novel optimization method that combines genetic algorithms and a simulation platform of urban rail power supply system is proposed, which can obtain the best energy management strategy, location, and size for ESSes simultaneously. With actual parameters of a Chinese metro line applied in the simulation comparison, certain optimal scheme of ESSes’ energy management strategy, location, and size obtained by a novel optimization method can achieve much better performance of metro systems from the perspectives of two evaluation functions. The simulation result shows that with the increase of weight coefficient, the optimal energy management strategy, locations and size of ESSes appear certain regularities, and the best compromise between economic efficiency and voltage drop compensation can be obtained by a novel optimization method, which can provide a valuable reference to subway company. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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18 pages, 412 KiB

Open AccessArticle

Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration

by Yuqing Yang, Weige Zhang, Jiuchun Jiang, Mei Huang and Liyong Niu

Energies 2015, 8(10), 10718-10735; https://doi.org/10.3390/en81010718 - 25 Sep 2015

Cited by 20 | Viewed by 6645

Abstract

With global conventional energy depletion, as well as environmental pollution, utilizing renewable energy for power supply is the only way for human beings to survive. Currently, distributed generation incorporated into a distribution network has become the new trend, with the advantages of controllability, [...] Read more.

With global conventional energy depletion, as well as environmental pollution, utilizing renewable energy for power supply is the only way for human beings to survive. Currently, distributed generation incorporated into a distribution network has become the new trend, with the advantages of controllability, flexibility and tremendous potential. However, the fluctuation of distributed energy resources (DERs) is still the main concern for accurate deployment. Thus, a battery energy storage system (BESS) has to be involved to mitigate the bad effects of DERs’ integration. In this paper, optimal scheduling strategies for BESS operation have been proposed, to assist with consuming the renewable energy, reduce the active power loss, alleviate the voltage fluctuation and minimize the electricity cost. Besides, the electric vehicles (EVs) considered as the auxiliary technique are also introduced to attenuate the DERs’ influence. Moreover, both day-ahead and real-time operation scheduling strategies were presented under the consideration with the constraints of BESS and the EVs’ operation, and the optimization was tackled by a fuzzy mathematical method and an improved particle swarm optimization (IPSO) algorithm. Furthermore, the test system for the proposed strategies is a real distribution network with renewable energy integration. After simulation, the proposed scheduling strategies have been verified to be extremely effective for the enhancement of the distribution network characteristics. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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20 pages, 3225 KiB

Open AccessArticle

Development of an Optimal Power Control Scheme for Wave-Offshore Hybrid Generation Systems

by Seungmin Jung and Gilsoo Jang

Energies 2015, 8(9), 9009-9028; https://doi.org/10.3390/en8099009 - 25 Aug 2015

Cited by 6 | Viewed by 4534

Abstract

Integration technology of various distribution systems for improving renewable energy utilization has been receiving attention in the power system industry. The wave-offshore hybrid generation system (HGS), which has a capacity of over 10 MW, was recently developed by adopting several voltage source converters [...] Read more.

Integration technology of various distribution systems for improving renewable energy utilization has been receiving attention in the power system industry. The wave-offshore hybrid generation system (HGS), which has a capacity of over 10 MW, was recently developed by adopting several voltage source converters (VSC), while a control method for adopted power conversion systems has not yet been configured in spite of the unique system characteristics of the designated structure. This paper deals with a reactive power assignment method for the developed hybrid system to improve the power transfer efficiency of the entire system. Through the development and application processes for an optimization algorithm utilizing the real-time active power profiles of each generator, a feasibility confirmation of power transmission loss reduction was implemented. To find the practical effect of the proposed control scheme, the real system information regarding the demonstration process was applied from case studies. Also, an evaluation for the loss of the improvement rate was calculated. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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16 pages, 1052 KiB

Open AccessArticle

Application of Model Predictive Control to BESS for Microgrid Control

by Thai-Thanh Nguyen, Hyeong-Jun Yoo and Hak-Man Kim

Energies 2015, 8(8), 8798-8813; https://doi.org/10.3390/en8088798 - 19 Aug 2015

Cited by 38 | Viewed by 9128

Abstract

Battery energy storage systems (BESSs) have been widely used for microgrid control. Generally, BESS control systems are based on proportional-integral (PI) control techniques with the outer and inner control loops based on PI regulators. Recently, model predictive control (MPC) has attracted attention for [...] Read more.

Battery energy storage systems (BESSs) have been widely used for microgrid control. Generally, BESS control systems are based on proportional-integral (PI) control techniques with the outer and inner control loops based on PI regulators. Recently, model predictive control (MPC) has attracted attention for application to future energy processing and control systems because it can easily deal with multivariable cases, system constraints, and nonlinearities. This study considers the application of MPC-based BESSs to microgrid control. Two types of MPC are presented in this study: MPC based on predictive power control (PPC) and MPC based on PI control in the outer and predictive current control (PCC) in the inner control loops. In particular, the effective application of MPC for microgrids with multiple BESSs should be considered because of the differences in their control performance. In this study, microgrids with two BESSs based on two MPC techniques are considered as an example. The control performance of the MPC used for the control microgrid is compared to that of the PI control. The proposed control strategy is investigated through simulations using MATLAB/Simulink software. The simulation results show that the response time, power and voltage ripples, and frequency spectrum could be improved significantly by using MPC. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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18 pages, 1093 KiB

Open AccessArticle

Design and Field Tests of an Inverted Based Remote MicroGrid on a Korean Island

by Woo-Kyu Chae, Hak-Ju Lee, Jong-Nam Won, Jung-Sung Park and Jae-Eon Kim

Energies 2015, 8(8), 8193-8210; https://doi.org/10.3390/en8088193 - 5 Aug 2015

Cited by 31 | Viewed by 7493

Abstract

In this paper, we present the results of an economic feasibility study and propose a system structure to test and maintain electrical stability. In addition, we present real operation results after constructing a remote microgrid on an island in South Korea. To perform [...] Read more.

In this paper, we present the results of an economic feasibility study and propose a system structure to test and maintain electrical stability. In addition, we present real operation results after constructing a remote microgrid on an island in South Korea. To perform the economic feasibility study, a commercial tool called HOMER was used. The developed remote microgrid consists of a 400 kW wind turbine (WT) generator, 314 kW photovoltaic (PV) generator, 500 kVA × 2 grid forming inverter, 3 MWh lithium ion battery, and an energy management system (EMS). The predicted renewable energy fraction was 91% and real operation result was 82%. The frequency maintaining rate of the diesel power plants was 57% but the remote microgrid was 100%. To improve the operating efficiency of the remote microgrid, we investigated the output range of a diesel generator. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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15 pages, 414 KiB

Open AccessArticle

A Distributed Control Strategy for Frequency Regulation in Smart Grids Based on the Consensus Protocol

by Rong Fu, Yingjun Wu, Hailong Wang and Jun Xie

Energies 2015, 8(8), 7930-7944; https://doi.org/10.3390/en8087930 - 31 Jul 2015

Cited by 17 | Viewed by 5391

Abstract

This paper considers the problem of distributed frequency regulation based on the consensus control protocol in smart grids. In this problem, each system component is coordinated to collectively provide active power for the provision of ancillary frequency regulation service. Firstly, an approximate model [...] Read more.

This paper considers the problem of distributed frequency regulation based on the consensus control protocol in smart grids. In this problem, each system component is coordinated to collectively provide active power for the provision of ancillary frequency regulation service. Firstly, an approximate model is proposed for the frequency dynamic process. A distributed control algorithm is investigated, while each agent exchanges information with neighboring agents and performs behaviors based on communication interactions. The objective of each agent is to converge to a common state considering different dynamic load characteristics, and distributed frequency control strategy is developed to enable the agents to provide active power support. Then, the distributed proportional integral controllers with the state feedback are designed considering the consensus protocol with topology . The theory of distributed consensus protocol isfurther developed to prove the stability of the proposed control algorithm. Whenproperly controlled, the controllers can provide grid support services in a distributed manner that turn out the grid balanced globally. Finally, simulations of the proposed distributed control algorithm are tested to validate the availability of the proposed approach and the performance in the electrical networks. Full article

(This article belongs to the Special Issue Control of Energy Storage)

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