Battery Storage Units Research Articles

RETRACTED: Robust bidding strategy of interconnected multi-carrier systems in the electricity markets under the uncertainty in electricity load

This paper presents a robust bi-level model for optimal bidding of interconnected multi-carrier systems (MCSs) in the wholesale electricity markets under the uncertainty in electricity load. The proposed model implements a robust optimization method (ROM) to model the risk-based bidding of interconnected MCSs under the uncertainty in load in the upper-level problem while including the energy and reserve markets in the lower-level problem. The studied MSCs include combined heat and power (CHP) units, boilers, central air conditioning (CAC) systems, and battery storage units to provide local energy and make the MCSs’ operator capable of participating in the reserve market to gain profit. ROM models the electricity demand and provides different bidding strategies (i.e., risk-seeking, risk-neutral, and risk-averse) for the participation of MCSs’ operator in the energy and reserve markets. The studied bi-level model is converted to a single-level mixed-integer linear programming problem using the Karush–Kuhn–Tucker conditions and strong duality and then solved using the CPLEX solver of the General Algebraic Modeling System. Numerical experiments reveal that the interconnection of MSCs, along with the integration of storage units, enables the MSCs’ operator to control the uncertainty in the electricity load and increase the energy efficiency in order to optimally bid in the day-ahead energy and reserve markets. Results show that by enabling the MCSs to locally trade energy, the total operation cost of MCSs in the risk-seeking, risk-neutral, and risk-averse modes decreases by 5.65%, 4.28%, and 3.49%. Moreover, with the integration of battery storage systems into the interconnected operation of MCSs, the total operation cost of systems in the risk-seeking, risk-neutral, and risk-averse modes decreases by 7.65%, 6.99%, and 6.40%, respectively.

Development of a battery management system for Centralized Control of a Battery Cluster

The purpose of this paper is to establish a supervisory battery management system which collects measurements from the installed battery storage units and enables various battery management functions. In addition, an HMI user interface was designed to allow the user to monitor and control the batteries. The batteries communicate with the PLC via Modbus TCP/IP protocol. The communication enables the exchange of measured power and state of charge values between the PLC and batteries, as well as setting the desired setpoint values. The PLC and HMI communicate via PROFINET. The battery storage units are installed in Smart Grid Laboratory (SGLab) at the University of Zagreb Faculty of Electrical Engineering and Computing.

Thermal Sensor Allocation for Effective and Efficient Heat Transfer Measurements in Transportation Systems.

Power plants, electric generators, high-frequency controllers, battery storage, and control units are essential in current transportation and energy distribution networks. To improve the performance and guarantee the endurance of such systems, it is critical to control their operational temperature within certain regimes. Under standard working conditions, those elements become heat sources either during their entire operational envelope or during given phases of it. Consequently, in order to maintain a reasonable working temperature, active cooling is required. The refrigeration may consist of the activation of internal cooling systems relying on fluid circulation or air suction and circulation pulled from the environment. However, in both scenarios pulling surrounding air or making use of coolant pumps increases the power demand. The augmented power demand has a direct impact on the power plant or electric generator autonomy, while instigating higher power demand and substandard performance from the power electronics and batteries' compounds. In this manuscript, we present a methodology to efficiently estimate the heat flux load generated by internal heat sources. By accurately and inexpensively computing the heat flux, it is possible to identify the coolant requirements to optimize the use of the available resources. Based on local thermal measurements fed into a Kriging interpolator, we can accurately compute the heat flux minimizing the number of sensors required. Considering the need for effective thermal load description toward efficient cooling scheduling. This manuscript presents a procedure based on temperature distribution reconstruction via a Kriging interpolator to monitor the surface temperature using a minimal number of sensors. The sensors are allocated by means of a global optimization that minimizes the reconstruction error. The surface temperature distribution is then fed into a heat conduction solver that processes the heat flux of the proposed casing, providing an affordable and efficient way of controlling the thermal load. Conjugate URANS simulations are used to simulate the performance of an aluminum casing and demonstrate the effectiveness of the proposed method.

Thermodynamic analysis of a bifacial PV/T‐driven ejector cooling and electrodialysis system for off‐grid sustainable climate refuge in hot‐arid climates

AbstractIn hot‐arid climatic regions like Qatar, it is important to facilitate pedestrians' journeys. One way to do so is by providing them with shelters, that is, from a station to their destination building. It is necessary for such shelters to provide on‐site space cooling and freshwater in an off‐grid condition. In this respect, the proposed off‐grid system in this study includes bifacial photovoltaic (BPV) and a solar thermal collector for energy generation with battery and thermal storage units. BPV with an efficiency of 16% can produce power up to about 6.1 kW on the rooftop, which also reduces the cooling load via effective shading. The ejector‐based cooling system is deployed for efficient space cooling in high ambient temperatures (more than 28°C), while for less than 28°C, both fan and water misting systems are operated for the comfort of pedestrians. Finally, an electrodialysis system is integrated to generate freshwater from seawater to be used for drinking and water misting purposes in the off‐grid sustainable shelter. The overall energy and exergy efficiencies of the system are calculated to be 13.2% and 5.29%, respectively. The effects of several parameters are also studied to observe the overall system efficiency and the energy generated and consumed by the system.

Grouping consistency control strategy based on DMPC and energy storage unit constraints

This paper proposes a distributed packet consistency control strategy to solve the distributed coordinated control problem among multiple battery storage units. In order to ensure that the distributed power allocation results meet the power constraints of each energy storage unit and reduce the communication requirements of distributed control, this paper proposes a weighted consistency algorithm based on distributed model predictive control and state constraints. A grouping control strategy of energy storage units is proposed. The weight of energy storage unit is set according to SOC information to improve consistency of SOC of energy storage unit. Meanwhile, based on the proposed consistency algorithm, an inter-group coordination control strategy and an efficiency improvement strategy of energy storage units are developed to improve the regulation ability of energy storage system, extend the life of energy storage system and improve the energy conversion efficiency. Finally, the proposed algorithm and control strategy are simulated and analyzed by building a microgrid system with eight battery storage units in Matlab. The simulation results show that the proposed algorithm and control strategy have certain advantages in improving convergence speed, optimizing control effect, prolong energy storage life and improve the operation efficiency of the energy storage system.

Sizing of Microgrid System Including Multi-Functional Battery Storage and Considering Uncertainties

Battery storage units (BSUs) are usually used to perform a single function in most planning studies related to microgrids (MGs). This paper presents an effective methodology to use the BSUs to perform multi-function including supply/demand matching and energy arbitrage. This is done according to a system policy containing all possible scenarios to fully utilize the BSUs to maximize the benefit. In the proposed work, the optimal sizing of the MG system under study containing wind turbines (WTs), photovoltaic system (PV), BSUs, and diesel units (DUs) is obtained. The main objectives of the proposed methodology are; 1) minimizing the total costs of the MG, 2) minimizing the harmful gas emissions, and 3) minimizing the accumulated power difference between the generation from renewable energy systems (RESs) and the demand. Due to the stochastic behavior of the output from the RESs, the uncertainties of wind speed, solar irradiance, and temperature are considered in the study. Two modes of operation of the MG (grid-connected and islanded) and the demand side management (DSM) are also considered. The problem is formulated as a constrained nonlinear optimization problem and is solved using two metaheuristic optimization algorithms, Moth-Flame Optimization (MFO) and Hybrid Firefly and Particle Swarm Optimization (HFPSO). Moreover, the uncertainties in the different parameters are considered by using the Latin Hypercube Sampling (LHS) method to generate samples of wind speed, solar irradiance, and temperature. To examine the proposed methodology, different case studies are presented and discussed. Moreover, the results of the used two algorithms, MFO and HFPSO, are compared to show their effectiveness in solving the proposed problem and assure the optimal solution. The optimization problem is implemented and solved using MATLAB software.

Environmental assessment of prosumer digitalization: The case of virtual pooling of PV battery storage systems

The emergence of decentralized renewable energies together with digitalization enable new possibilities for the provision of system services that are needed for the energy transition. In Germany and worldwide, prosumers with a PV battery storage system are on the rise. With the aid of digital information and communication technologies (ICT), energy service providers can pool individual battery storage units to form a virtual battery energy storage system (VBES). The VBES is supposed to provide flexibility services and, thereby, support the transition towards an energy system with high shares of intermittent renewables. Although the concept is environmentally motivated, a holistic environmental assessment is missing so far. Therefore, we carry out a life-cycle analysis that considers environmental benefits, as well as burdens of VBES. For this, we compare a PV battery storage unit in a German single-family household with and without participation in a VBES for the year 2018. We assess three levels of environmental effects: direct effects due to digitalization (data transfer, ICT resources for VBES operation), indirect effects from external optimization on the household-level (changes in battery life and power supply), and enablement effects on the system level (provision of Frequency Containment Reserve, redispatch, and preventing renewables curtailment). We find that digitalization has a comparably low direct impact but it can enable relatively high environmental benefits for climate protection, and in other impact categories. Conditions for our findings are that battery life and the household's degree of self-sufficiency with PV electricity are not significantly affected by the external control of the VBES operator. We conclude that current and future battery owners should be encouraged to allow external access for system services. Furthermore, the necessary ICT roll out should be implemented in the short- to mid-term.

Design and performance optimization of a tri‐generation energy hub considering demand response programs

AbstractThe design and development of renewable energy resources‐based poly‐generation microgrids have recently increased to supply multiple demands such as cool, heat, and power as well as mitigate pollutants improving efficiency. This paper aims to develop a combined cooling, heating, and power production network integrating photovoltaic panels (PVs), wind and gas turbines, a battery, an ice bank tank, a heater, an electrical chiller, a thermal energy storage medium. In this tri‐generation facility, natural gas is utilized for district heating and fueling the gas turbine power generation cycle. The local power distribution system in combination with the output powers of PVs, wind and gas turbines is used to directly supply the electrical appliances, ice maker process, and chiller as well as charge the battery storage unit. Moreover, the air/water‐cooled chiller procures the cooling flux for a benchmark microgrid. Its heating energy requirement is also provided by the gas‐fired heater, the flue gases of the gas turbine, and the thermal storage medium. A mixed integer linear programming problem is coded using a generalized algebraic modeling system (GAMS) to minimize daily operating costs and emissions. Simulations are examined and analyzed over a 24‐h study horizon on a sample summer day. Time‐of‐use energy rates and RTPs are considered two strategic demand response schemes to investigate the cost‐effectiveness capability of the gas‐power nexus model. The proposed approach is coded using a GAMS to confirm its effectiveness and cost‐environ benefits in four cases with and without heat/cool/electrical storage units considering time‐of‐use energy rates and real‐time prices.

Model predictive control based autonomous DC microgrid integrated with solar photovoltaic system and composite energy storage

In this paper, a model predictive controller (MPC) is developed along with a simplified power management algorithm (PMA) for the autonomous DC microgrid. The autonomous DC microgrid includes a solar photovoltaic (SPV) unit integrated with composite energy storage (CES). The CES unit is composed of lithium-ion battery storage and supercapacitor storage units. Compared to conventional DC-microgrids with the SPV source alone, the integrated CES unit effectively handles the long-term and short-term power fluctuations due to the abrupt load variations and uncertainty in power generation by the SPV. This results in providing sustainable and reliable power supply to the remote accessing loads in rural electrification and improving the flexible operation of the microgrid. In addition, the integration of the supercapacitor with battery storage regulates the common dc-link voltage smoothly and is maintained at its reference value. Furthermore, with the proposed control strategy, the performance indices such as maximum peak overshoot, settling time, and steady-state error of the dc-link voltage have been improved as compared to the conventional control techniques. Besides that, the rate of change in battery current responds quickly to the step load variation. The efficacy and performance of the proposed system are verified and validated through MATLAB/Simulink and real-time simulation results using OPAL-RT OP4510 real-time simulator under various dynamic operating conditions.

New optimized configuration for a hybrid PV/diesel/battery system based on coyote optimization algorithm: A case study for Hotan county

The main objective of this study is to present a multi-objective and optimal hybrid PV/diesel generator/ battery Renewable Energy System (HRES) to provide this reliability in the Hotan county, placed in Taklamakan Desert. This study uses the ɛ-constraint method along with a developed version of the coyote optimization algorithm to achieve the best values of the component sized to decrease the loss of load probability, CO2 emission value, and the annualized cost of the system. Sensitivity analysis also is performed to show each component’s impact on the system. The results demonstrate that the DG backup system improves the yearly cost of the system from 8347.2 $ to 9318.4 $, which shows about 10.42% increasing by increasing the fuel consumption. Here, the LLP increases from 0% to 9.19% and the CO2 emissions improve from 2531.2 kg/yr to 13257 kg/yr. Accordingly, the COE value is reduced from 0.39 $/kWh to 0.24 $/kWh over the PV penetration, reducing from 92.27% to 59.42%. This decreasing indicates that the system fuel cost has more impact than the cost of PV on the COE, which is due to the low cost required of conventional power production than the PV system. The results also indicate a noteworthy upshot on the battery storage unit size such that the size of ɛCO2 has been enhanced from 27.4 kWh to 50 kWh in the range from 7000 kg/year to 25 kg/year. The results also are compared with the PSO-based optimal system and HOMER software results to show its excellence toward them.

Optimal techno-economic multi-level energy management of renewable-based DC microgrid for commercial buildings applications

An optimal techno-economic multi-level energy management strategy (EMS) is designed for a DC microgrid applied to a commercial building. The proposed power system is a grid-connected microgrid composed of a fuel cell (FC) system, a photovoltaic (PV) array, and a battery storage unit. The interaction between various types of power sources may lead to stability problems. Moreover, providing an uninterruptible and high-quality power supply, reducing operating costs, and maximizing system efficiency are essential factors. This paper presents a techno-economic EMS, one of the most significant objectives for the following years. The proposed EMS comprises two levels for minimizing the operating cost and supplying the load and another control level based on flatness control theory to improve the power quality. The first level is based on one of the following EMSs: State Machine Control (SMC), Equivalent Consumption Minimization Strategy (ECMS), and External Energy Maximization Strategy (EEMS) to improve efficiency and reduce the required power. The second level is based on the economic dispatching algorithm (EDA) to reduce the operating cost and ensure a UPS. Finally, the system performance is elaborated; the simulation results prove the superiority of the EEMS-EDA combination, where the cost-saving can be enhanced by 3.47%, and the efficiency is about 80.44%.

A novel grid-connected microgrid energy management system with optimal sizing using hybrid grey wolf and cuckoo search optimization algorithm

Renewable energy systems, particularly in countries with limited fossil fuel resources, are promising and environmentally sustainable sources of electricity generation. Wind, solar Photovoltaic (PV), and biomass gasifier-based systems have gotten much attention recently for providing electricity to energy-deficient areas. However, due to the intermittent nature of renewable energy, a completely renewable system is unreliable and may cause operation problems. Energy storage systems and volatile generation sources are the best way to combat the problem. This paper proposes a hybrid grid-connected wind-solar PV generation Microgrid (MG) with biomass and energy storage devices to meet the entire value of load demand for the adopted buildings in an intended region and ensure economic dispatch as well as make a trade in the electricity field by supplying/receiving energy to/from the utility grid. The control operation plan uses battery storage units to compensate energy gap if the priority resources (wind turbine and solar PV) are incapable of meeting demand. Additionally, the biomass gasifier is used as a fallback option if the batteries fail to perform their duty. At any time, any excess of energy can be utilized to charge the batteries and sell the rest to the utility. Additionally, if the adopted resources are insufficient to meet the demand, the required energy is acquired from the utility. A Hybrid Grey Wolf with Cuckoo Search Optimization (GWCSO) algorithm is adopted for achieving optimal sizing of the proposed grid-connected MG. To assess the proposed technique’s robustness, the results are compared to those obtained using the Grey Wolf Optimization (GWO) algorithm. The GWCSO method yielded a lower total number of component units, annual cost, total Net Present Cost (NPC), and Levelized Cost Of Energy (LCOE) than the GWO algorithm, whereas the GWCSO algorithm has the lowest deviation, indicating that it is more accurate and robust than the GWO algorithm.

Hierarchical Cooperative Control Strategy for Battery Storage System in Islanded DC Microgrid

This paper presents a novel hierarchical cooperative control strategy to solve the problems of unbalanced State of Charge (SoC), unreasonable load current sharing, and unstable bus voltage for battery storage system (BSS) in islanded DC microgrid. In the communication layer, a neighbor-to-neighbor communication network architecture is constructed in which each battery storage unit (BSU) only communicates information with neighboring nodes, and a multi-agent consensus algorithm is used to iteratively estimate the relevant average global variables. In the main control layer, the droop coefficient is dynamically adjusted by constructing a fast SoC convergence function to ensure that the load current is reasonably distributed based on the rated capacity of each BSU. In the secondary control layer, a virtual voltage drop equalization controller and an average bus voltage compensation controller are designed to eliminate the impact of line impedance mismatch and compensate the average bus voltage. Furthermore, an optimized factor is designed to accelerate the later stage of SoC convergence. Finally, a DC microgrid experimental platform based on StarSim HIL is built, and the results demonstrate that the proposed strategy can achieve the control objectives of fast SoC balance, proportional load current sharing, and bus voltage stability.

Residents Against Dirty Energy: using energy justice to understand the role of local activism in shaping low-carbon transitions

ABSTRACT “Residents Against Dirty Energy” (RADE) are a community-led energy activist group in Bristol city, UK. Since their inception, they have effectively lobbied the city council for the deployment of battery storage units in place of diesel generators in Lockleaze, north Bristol. As a result, Lockleaze now hosts battery storage facilities with 15MW of storage capacity able to store excess energy from the grid. Drawing on a focus group (n = 8) with local energy actors in Bristol and in-depth interviews (n = 2) with RADE, alongside document analysis of key secondary data sources, the paper uses three tenets of energy justice (distributional, recognition and procedural justice) to shed light on the role of local energy activism in shaping low-carbon energy infrastructures. The qualitative data reveals RADE’s efforts to ensure that local communities are closely involved in energy decision-making, to ensure that the siting of new energy technologies does not burden marginalised communities. However, questions around distributional-economic benefits and ownership are secondary to RADE; their primary concern is with the improvement of local air quality and reducing harm to the local population and environment. These issues connect strongly to Bristol’s divided landscape, underpinned by an unequal geography of socio-economic division and racial inequality. As such, the paper sees the further integration of “spatial justice” as a core tenet of energy justice as necessary to enhancing its explanatory power, concluding with a call for scholars and policymakers to further consider the visions and efforts of local and civil society energy activists in shaping just transitions.

Performance analysis of a hybrid renewable generation system connected to grid in the presence of DVR

This paper discusses the performance of a hybrid renewable generation system (HRGS). Dynamic voltage restorer (DVR) enhances the voltage profile of the grid. HRGS consists of Photovoltaic (PV), Battery storage unit (BSU) and an auxiliary unit (AU). AU is a backup generation consists of Diesel Generator (DG) and fuel cell. In stand-alone mode, HRGS supply power to remote residents, while the remainder is supplied to the grid. If the load demand exceeds the capacity of the PV generation and the State of Charge (SOC) is less than 0.2, AU is used to generate power otherwise excess power stored in the BSU and supply to the grid. The performance of HRGS has been improved using modified Perturb and Observe (P&O) algorithm of PV, control strategy of BSU & AU. The validation of different shunt fault and power quality issues are also tested to check the effectiveness and stability of the system.

Scheduling Home Appliances with Integration of Hybrid Energy Sources using Intelligent Algorithms

This paper presents Home Energy Management System(HEMS) for smart homes. This system includes Photovoltaic Sources and Battery Storage Units(BSU)and scheduling Smart Home(SH) appliances with various kinds and types of residential users. In addition, a classification algorithm of energy response programs, which relies on the electricity prices, is introduced for scheduling appliances of single and multiple homes using combined the Time of Use(TOU) and Inclining Block Rate(IBR) to control the demand under the grid station capacity and energy efficacious integration of hybrid power sources in Smart Grid(SG). Four different optimization algorithms used and compared for scheduling appliances. The simulation results show that the proposed algorithm achieves the desired objectives, in which the electricity cost and the Peak Average Ratio(PAR) were lowered, waiting time to the user is minimized, reducing the electricity bill per month/year. In addition, the proposed system increases the stability and reliability of the grid and consumers satisfaction.

Design Considerations for Reducing Battery Storage in Off-Grid, Stand-Alone, Photovoltaic-Powered Cold Storage in Rural Applications

This paper presents design considerations for the design and implementation of stand-alone photovoltaic-powered containerized cold storage solutions for rural off-grid applications. The work presented is based on a case study of an off-grid photovoltaic-powered cold storage unit located in rural South Africa. Although solar-powered solutions for off-grid rural applications are very attractive and offer many benefits, including increased food security, skills development, income generation, and productivity due to the presence of solar power, the application of cold storage requires careful consideration of the design aspects to ensure that the solution is feasible and sustainable. The challenge of maintaining low temperatures inside a cold storage system in an excessively warm environment, such as that frequently encountered in most African rural settings, has stimulated discussions of design considerations for optimal efficiency. Not only are the design aspects of the PV panel mounting and tilt associated with the geographic location of the application, but the heating implications are also derived from the physical orientation of the storage unit. Results from mathematical models are substantiated with field data collected from a case deployment. The design considerations for the sizing of the electrical components in the system are presented. The paper concludes by answering the research question as to what design aspects should be considered for an off-grid, PV-powered containerized cold storage system to reduce the size of the battery storage unit.

Heterogeneous changes in electricity consumption patterns of residential distributed solar consumers due to battery storage adoption

SummaryThis study provides an empirical assessment of how adopting battery storage units can change the electricity consumption patterns of PV consumers using individual-consumer-level hourly smart meter data in Arizona, United States. We find that on average after adding batteries, PV consumers use more solar electricity to power their houses and send less solar electricity back to the grid. In addition, adding battery storage reduces electricity needed from the grid during system peak hours, helping utilities better flatten the load curves. Most importantly, we find a large degree of heterogeneity in the changes in electricity consumption patterns due to adopting battery storage that are not consistent with engineering or economic principles such as those not maximizing consumers’ economic benefits. Such heterogeneous changes imply that utilities and policymakers need to further study the underlying behavioral reasons in order to maximize the social benefits of battery storage and PV co-adoption.

An Improved Distributed Secondary Control Strategy for Battery Storage System in DC Shipboard Microgrid

In this article, an improved distributed secondary control strategy is proposed to achieve state of charge (SoC) balance, accurate load current sharing, and bus voltage recovery for battery storage system in dc shipboard microgrid. First, each battery storage unit (BSU) is regarded as a multiagent, and a neighbor-to-neighbor communication network is constructed to reduce the system communication burden. Each BSU is based on distributed consensus protocol, and global consensus can be achieved only by communication between adjacent BSUs. On this basis, a novel consensus-based SoC balancing algorithm is proposed to achieve accurate load current sharing, and a dc bus voltage controller is designed to achieve secondary regulation of the bus voltage. Furthermore, the SoC convergence characteristics, systems stability analysis, global dynamic model, and steady-state analysis of the proposed control strategy are studied. Finally, the simulation and StarSim HIL experimental results show that the proposed control strategy can achieve SoC dynamic balance, accurate load current sharing, and average bus voltage recovery under various complex conditions, and has a faster SoC convergence speed than advanced methods.

Analysis and Implementation of a Bidirectional Converter with Soft Switching Operation

This paper presents a soft switching direct current (DC) converter, with the benefits of bidirectional power conversion and wide-ranging voltage operation for battery charging and discharging capability. A series resonant circuit with variable switching frequency modulation is used to achieve the advantages of soft switching turn-on or turn-off of semiconductor devices. Therefore, the switching power losses in power devices can be reduced. A symmetric resonant circuit topology with a capacitor–inductor–inductor–capacitor (CLLC) structure is adopted to achieve a bidirectional power conversion capability for battery storage units in electric vehicle applications. Due to the symmetric circuit structure on both input and output sides, the converter has similar voltage gains for each power flow operation. In order to overcome the drawback of narrow voltage range operation in conventional resonant converters, a variable transformer turns ratio is adopted in the circuit, to achieve wide output voltage operation (150–450 V) for battery charging applications. To demonstrate the converter performance, a 1-kW laboratory prototype was constructed and tested. Experimental results are provided, to verify the effectiveness of the studied circuit.