Capacity-based adaptive droop control for battery energy storage operation

Lithium‐ion battery (LIB) energy storage systems play a significant role in the current energy storage transition. Globally, codes and standards are quickly incorporating a framework for safe design, siting, installation, commissioning, and decommissioning of battery energy storage systems (BESS). Full‐scale fire testing provides essential understanding of thermal runaway, fire, and explosion hazards associated with LIBs and BESSs. Engineers must then interpret that data to inform the site‐specific design, but there are cell, module, unit, and installation‐level data to decipher. Understanding the testing data and their limitations is critical for the design and operation of BESSs. Real‐life examples of where engineers misunderstood or misapplied test data will be presented to help bridge the knowledge gaps between stakeholders, industry, and engineers.

Power systems have been undergoing radical changes in recent years, and their planning and operation will be surely undertaken according to the Smart Grid (SG) vision in the near future. The SG initiatives aim at introducing new technologies and services in power systems, to make the electrical networks more reliable, efficient, secure and environmentally-friendly. In particular, it is expected that communication technologies, computational intelligence and distributed energy sources will be widely used for the whole power system in an integrated fashion. In particular, nowadays, unprecedented challenges like as stringent regulations, environmental concerns, growing demand for high quality, reliable electricity and rising customer expectations are forcing utilities to rethink about electricity generation and delivery from the bottom up. Moreover, the availability of low cost computing and telecommunications technologies, new generation options, and scalable, modular automation systems push utilities to be dynamic, innovative and ambitious enough to take advantage of them. Driven by the dynamics of the new energy environment, leading utilities, technology vendors and government organizations have created a vision of the next generation of energy delivery systems: the Smart Grid. Operational changes of the grid, caused by restructuring of the electric utility industry and electricity storage technology advancements, have created an opportunity for storage systems to provide unique services to the evolving grid. Especially Battery Energy Storage Systems (BESSs), thanks to the large number and variety of services they can provide, are powerful tools for the solution of some challenges that future grids will face. This consideration makes BESSs critical components of the future grids. The BESS can be applied for different services into the different levels of power system chain to satisfy technical challenges and provide financial benefits. In the context of the application of BESSs in SGs, there are two main problems that need to be addressed in a way that exploits the BESS potential, that are linked to their operation and sizing. This thesis focuses on both these aspects, proposing new strategies that allow optimizing the BESS adoption. When dealing with BESSs, sizing and operation are strictly linked. The correct sizing of a BESS, in fact, needs to take into account its operation which in turn will be effected with the aim of optimizing the whole system where it is included. In the first part of this research study, advanced optimal operating strategies were proposed for BESSs by considering both the distribution system operator perspective and the end user. Thus, the proposed operating strategies were performed with the aim of (i) leveling the active power requested by the loads connected to a distribution system (distribution system operator service), (ii) reducing the electricity costs sustained by an end-use costumer that provides demand response (DR) (end user service) and (iii) scheduling a microgrid (µG) with DR resources such as Plug-in Electric Vehicles (PEVs) and Data Centers (DCs) (both the two section service). The proposed strategies also satisfied technical constraints of BESSs and other components of the µG. The second part of the thesis presented the optimal sizing of BESSs aimed at maximizing the benefits related to their use. In the thesis, the sizing, which is performed by considering the end user point of view with reference to both the industrial and residential customers, is effected by adopting both deterministic and probabilistic approaches. With reference to the deterministic approach, a simple and quick closed form procedure for the sizing of BESSs in residential and industrial applications was proposed. In case of probabilistic approach, the case of a BESS installed in an industrial facility was considered and the sizing was performed based on the decision theory. Technical improvements and economic benefits of optimal operation and optimal sizing of BESSs in SG are demonstrated by the obtained results which are reported in the numerical applications. More specifically, it was clearly determined that BESSs can offer technical supports into the distribution operator section of the grid in terms of load management and security challenges. Moreover optimal integration of BESSs into the grid was also appealing for end users thanks to valuable amounts of electricity bill cost reduction. Regarding the original contribution of the thesis, the following considerations can be done. With reference to the load leveling service, an innovative two-step procedure (day-ahead scheduling and very short time predictive control) was proposed which optimally controls a BESS connected to a distribution substation in order to perform load leveling. In case of DR, a proper control of the BESS was proposed in order to perform DR under different price schemes, such as Real Time Pricing (RTP) and Time of Use (TOU) without modifying the daily work cycle of the industrial loads. The control procedure allows achieving contemporaneously two important goals that are the reduction of the bill costs and the prolonging the battery's lifetime so further reducing the costs sustained by the customer. With reference to the scheduling of microgrids, the original contribution of the thesis is focused on the proposal of optimization strategies aimed at managing and coordinating, simultaneously, batteries on board of vehicles or equipping data centers' Uninterruptable Power Supply (UPS) and Distributed Generation (DG) units. Also comparisons among different single-objective based strategies are made in order to highlight the most convenient. With reference to the sizing based on deterministic approach, unlike the other relating literature, the innovative contribution is that the closed form procedure takes into account both the technical constraints of the battery and contractual agreements between the customer and the utility. Moreover, in the economical analysis performed for the sizing, which is applied with reference to both residential and small industrial customers and is based on actual TOU tariffs, a wide sensitivity analysis to consider different perspectives in terms of life span and future costs was performed. Some aspects that affect the profitability of the battery, such as technological limitations (e.g. the battery and converter efficiency), economic barriers (e.g. capital cost and the rate of change of the cost) and variation of the load profile along the years were deeply analyzed. In case of sizing based on probabilistic approach, the original contributions of the thesis are mainly referred to the proposal of a new method that uses a decision theory-based process to obtain the best sizing alternative considering the various uncertainties affecting the sizing procedure. The thesis is organized in three chapters which are dealing with integration of BESSs in SGs. The first chapter reports basic concepts and characteristics of BESSs, fundamental components and features of SGs and different services that BESSs can provide. The optimal operation strategies of BESS are considered in second chapter which includes their problem formulation, solving procedures and results. The third chapter deals with the optimal sizing problem of BESSs for which the problem formulation, solving procedures and results are reported. Finally, the conclusions are presented in the last part of thesis.

A battery energy storage scheme to enable short-term dispatch commitment from a grid-connected wind-turbine generating power station is considered. Among the various types of energy storage medium, technical factors leading to the selection of battery are explained. The scheme utilizes two battery energy storage systems (BESS) in which the generated wind power charges one BESS while concurrently, the second BESS is to discharge power into the grid. The role of the two BESS interchanges when the BESS reaches specified state of charge/discharge. Furthermore, based on forecasted charging wind power and the monitored states of charge of the two BESS, the discharge power level from the generating station is determined and scheduled a few hours ahead. The dispatch scheme maximizes wind energy harnessed, achieved with the minimum number of the BESS switch-overs. The design thus prolongs the service life of the BESS. Numerical examples to demonstrate the performance of the scheme are also included.

Due to the dramatic growth of the global population, building multi-story buildings has become a necessity, which strongly requires the installation of an elevator regardless of the type of building being built. This study focuses on households, which are the second-largest electricity consumers after the transportation sector. In residential buildings, elevators impose huge electricity costs because they are used by many consumers. The novelty of this paper is implementing a Hybrid Energy Storage System (HESS), including an ultracapacitor Energy Storage (UCES) and a Battery Energy Storage (BES) system, in order to reduce the amount of power and energy consumed by elevators in residential buildings. The control strategy of this study includes two main parts. In the first stage, an indirect field-oriented control strategy is implemented to provide new features and flexibility to the system and take benefit of the regenerative energy received from the elevator’s motor. In the second stage, a novel control strategy is proposed to control the HESS efficiently. In this context, the HESS is only fed by regenerated power so the amount of energy stored in the UC can be used to reduce peak consumption. Meanwhile, the BES supplies common electrical loads in the building, e.g., washing machines, heating services (both boiler and heat pump), and lighting, which helps to achieve a nearly zero energy building.

<span>This paper proposes a new optimal operation of Microgrids (MGs) in a distribution system with wind energy generators (WEGs), solar photovoltaic (PV) energy systems, battery energy storage (BES) systems, electric vehicles (EVs) and demand response (DR). To reduce the fluctuations of wind, solar PV powers and load demands, the BES systems and DR are utilized in the proposed hybrid system. The detailed modeling of WEGs, solar PV units, load demands, BES systems and EVs has been presented in this paper. The objective considered here is the minimization of total operating cost of microgrid, and it is formulated by considering the cost of power exchange between the main power grid and microgrid, cost of wind and solar PV energy systems, cost of BES systems, EVs and the cost due to the DR in the system. Simulations are performed on a test microgrid, and they are implemented using GAMS software. Various case studies are performed with and without considering the proposed hybrid system.</span>

The automotive industry has rapidly introduced pollution-free vehicles such as Electric Vehicle (EV). The development and improvement of the EV to replace the conventional vehicle become crucial to obtain the customer satisfaction and high technology achievements. The main systems in EV that are improvise to be switch from the conventional engine with a fuel source to an electric type drive system, include the electric motor and the energy/power storage called battery. There are several types of electric motors that suitable for EV and the best solution was Brushless Direct Current (BLDC) motor in terms of power, speed, torque and low maintenance. Meanwhile, the fuel source replacement is the electrical energy/power storage such as batteries. The aims were to study the best Energy Storage System (ESS) in EV which leads to introducing Battery Energy Storage System (BESS), but the drawbacks of the system give the opportunity improvement, in replacement using Supercapacitor Energy storage System (SESS) and Hybrid Energy Storage System (HESS). SESS is a reliable source, but the stand-alone Supercapacitor also has a minimum operation time. With several adjustments in the energy management control strategy, the discharge rate of energy from a supercapacitor can be minimized to prolong its operation.

This paper proposes state-of-charge (SOC) balancing control based on discrete consensus algorithm to improve the accuracy of power dispatch of the battery energy storage systems (BESS), reducing system cost and prolong the service life of the BESS in islanded microgrid. This has been achieved with hierarchical distributed secondary cooperative control based on discrete consensus algorithm, which modifies the BESS output power to reach a balanced SOC. The control structure has two layers. The cooperative control works as the secondary layer, obtaining equal SOC of the BESS of the grid through interchanges information of energy storage systems state of charge (SOC) with its neighbors. BESS control approach as the primary control layer, they are able to realize the output power sharing and the balancing discharge rate by regulating the virtual resistance. The simulation platform is built based on Matlab/Simulink software. The validity and feasibility of the proposed control strategy has been further verified by various simulation results.

This paper proposes the use of battery energy storage (BES) system for the grid-connected doubly fed induction generator (DFIG). The BES would help in storing/releasing additional power in case of higher/lower wind speed to maintain constant grid power. The DC link capacitor is replaced with the BES system in a DFIG-based wind turbine to achieve the above-mentioned goal. The control scheme is modified and the co-ordinated tuning of the associated controllers to enhance the damping of the oscillatory modes is presented using bacterial foraging technique. The results from eigenvalue analysis and the time domain simulation studies are presented to elucidate the effectiveness of the BES systems in maintaining the grid stability under normal operation.

Battery energy storage for load frequency control of an interconnected power system

The integration of battery energy storage systems (BESS) with renewable energy is a potential solution to address the disadvantages of renewable energy systems, which is irregular and intermittent power. In particular, residential BESS is advancing in numerous countries. The residential BESS connected to the photovoltaic system (PV) can store the PV power in the battery through charging, and supply the PV power, which was stored in the battery, to the load through discharging when there is no PV power. Therefore, the utilization of residential BESS with PV reduces the daily electric power consumption and the electricity bills that households have to charge. However, it is understood that there is no case of installing and using residential BESS in Korea yet. Most residential houses in Korea are apartment houses, and thus residential BESS can be used with balcony PV. This paper presents operation modes of residential BESS with balcony PV for apartment houses. The BESS capacity was estimated by considering the balcony PV capacity, which can be installed in households, and power consumption. The applicability of the residential BESS was analyzed through performance and economics evaluation under current and various conditions. The operation modes of BESS were divided into four types according to PV power supply priority and battery charging source, and a test took place in a demonstration house. The risk of fully discharging the battery has been discovered when PV power is first charged to the battery or when only PV power is charged with the battery. As a result, preferential charging of the battery with PV power and then with PV and grid power was found to be the most optimal operation mode. In addition, additional functions were proposed for residential BESS in apartment households. The results will contribute to effective application of residential BESS with balcony PV in the near future.

The power system faces a lot of challenges due to incorporation of a large number of renewable energy sources. Here, Battery Energy Storage System (BESS) can be used effectively to deal with the grid’s rising peak demands without the necessity of upgrading the grid capacity. An energy management strategy is considered based on peak load shaving combined with transformer power limit and BESS State of Charge (SOC). Cooperation Search Algorithm (CSA) is utilised to determine the number of batteries in BESS and Photovoltaic (PV) panels with the goal of maximising economic benefits. The optimisation model of solar microgrid energy storage is established and solved for three scenarios of the grid only (Base Case), BESS without PV (Case-A) and BESS with PV (Case-B). From the result, it is verified that in Case-B, the customer will pay 31% and 34% less compared to the Base Case and Case-A, respectively, towards energy costs in a day.

In order to optimally size battery energy storage systems (BESS), it is necessary to take into consideration the degradation of the battery. Battery degradation in grid applications depends on the services provided by the energy storage and its operational regimes. In this paper, we propose a bi-level multi-objective optimization model to optimize the design of a BESS that simultaneously provides peak shaving and frequency regulation services. In the lower-level optimization, the daily scheduling scheme of the BESS is optimized to maximize the daily profit of the BESS. In the upper-level optimization, the rated capacity and power of the BESS is optimized to maximize the return on investment (ROI) of the BESS for the life cycle. The equivalent number of cycles of the BESS is calculated by using a rainflow algorithm to estimate the equivalent value loss of BESS in each day. In addition, the calendar aging and cycle aging of battery capacity and power capability is evaluated for every year. The simulation results using realistic data show that considering battery degradation in the optimization model reduces the battery number of cycles by about one half with a reduction in revenue, while still being profitable.

With the rapid development of renewable energy technologies, islanded DC microgrids have received extensive attention in the field of distributed power generation due to their plug-and-play, flexible operation modes and convenient power conversion, and are likely to be one of the mainstream structures of microgrids in the future. The islanded DC microgrid contains multiple distributed power generation units. The battery energy storage system (BESS) is the main controlled unit used to smooth power fluctuations. The main parameter of concern is the state of charge (SOC). In order to maintain the stability of the microgrid, this paper takes the islanded DC microgrid as the research object and designs a control strategy based on the SOC of the BESS. Additionally, in the control strategy, the BESS’s energy balance control strategy and the microgrid’s operation control strategy are emphatically designed. The designed BESS control strategy adjusts the droop coefficient in real time according to the SOC of the battery energy storage unit (BESU), and controls the charge and discharge power of the BESU to achieve the SOC balance among the BESUs. The microgrid operation control strategy takes the energy storage system (ESS) as the main controlled unit to suppress power fluctuations, and distributes the power of distributed power sources according to the SOC of the BESS to achieve power balance in the microgrid, and control the DC bus voltage fluctuation deviation within 4.5%.

Planning battery energy storage system in line with grid support parameters enables circular economy aligned ancillary services in low voltage networks

Battery energy storage system (BESS) is the key element to integrate a distributed generation (DG) unit into a microgrid. This paper presents a microgrid consisting of singlephase photovoltaic (PV) arrays which function as the primary DG units and a BESS to supplement the intermittent PV power generation and demand variations in the microgrid. An energy management system is proposed to coordinate the operations of the microgrid during grid-connected and islanded modes of operation. The BESS is incorporated into the microgrid to deal with power imbalance and peak load demand during grid-connected operation and to compensate for any power shortage during islanded operation. The controller design for the voltage source inverter employs a model predictive control (MPC) algorithm which enables faster dynamic response. MATLAB/Simulink is used to simulate the proposed microgrid under different test scenarios. The simulation results show that the operations of the BESS in the microgrid can be coordinated effectively using the proposed control system to ensure stable operation of the overall microgrid.