Battery Storage Units Research Articles

Apprehending Fault Crises for an Autogenous Nanogrid System: Sustainable Buildings

This paper presents a novel approach for in-house operators to profile and allege fault interferences in a nanogrid system either locally or externally. The proposed hybridized methodology is modeled to apprehend, classify, and locate fault interventions using a heuristic data-driven processing model and a sensing directional flow theorem. Employment of fuzzy control and discrete Fourier transform systems are fused to recompose directional fault relay functionalities. The algorithm is composed of three computational stages: stage 1 quantifies conditional correlate coefficients (COC) based on current and phase angle features sampled at interconnecting feeders, stage 2 engages a fuzzy logic controller to express linguistic truth values against calculated COCs, and stage 3 directs circuit breaker operations advocating post phase-shift aberrations to isolate the faulted region. A nanogrid model inspired by Singapore's Green Mark Building Incentive is developed in the MATLAB environment consisting of a combine heat and power microturbine, a rooftop photovoltaic system, and battery storage units tied to the 22-kVAC distribution network. Analytical results exhibit practicability and decisive settlements in diagnosing various types of fault crises despite low data logging signal-to-noise ratio. Conjointly, engagements of circuit breakers have rendered accurate switching operations toward isolating faulted regions.

Performance Improvements of Induction Motor Drive Supplied by Hybrid Wind and Storage Generation System Based on Mine Blast Algorithm

This research investigates the performance improvements of induction motor (IM) drive supplied by a hybrid wind/battery storage system based on the optimal mine blast algorithm. This is done by using IM field-oriented speed control as an independent dynamic load and a battery as a storage power unit. To ensure the accuracy and quality of energy equilibrium in autonomous wind power systems, there is an urgent and necessary demand for battery storage units. So in principle, the overall system of the complete model is configured to be combined with an uncontrolled rectifier, a steady magnetic synchronous generator (PMSG), a buck converter, and a lead–acid battery (LAB) in addition to an induction motor. According to the imposed controller, the loads required power can be obtained effectively by the prescribed battery storage and the wind generation units. Considering the suggested vector control to adjust the induction motor velocity through a three-phase inverter, it will be obtained 220 V/50 Hz, which is the principal target of this research. Moreover, the system with the proposed optimal control is compared with the optimal control based on genetic algorithm (GA) and the classical PID control. It is, therefore, possible to conclude that the results of numerical calculations and simulations illustrate that the studied system has strong achievement and perfect predictor of the electric parameter waveforms.

Intelligent Control of Wind-Assisted PHEVs Smart Charging Station

Two technology opportunities, integration of renewable energy sources and the electrification of vehicles are being encouraged to reduce dependency on fossil fuels and pollution problems. Nevertheless, the huge increase of plug-in hybrid electric vehicles (PHEVs) on roads will cause an additional load in demand, especially at rush hours, and therefore, threatens the stability of existing power grids. Considering PHEV stay for several hours in the workplace, (i.e., university), this may provide an inimitable framework to charge PHEV from wind in the workplace. This paper introduces the possibility of introducing intelligent control of wind power and battery storage units as supplementary power sources for future PHEV charging demands during rush hours. The operation of the proposed algorithm is based on the priority levels of PHEVs charging, and fluctuations in DC link voltage levels due to the variation in wind speed. The priorities of PHEVs charging are developed according to their power requirements, maximum rating of distribution transformer and park duration of PHEVs in the workplace during wind speed. Various non-isolated proportional–integral controllers and improved intelligent fuzzy control are used to keep a minimum critical DC link voltage to permit the power conditioning system to operate a charging station uninterruptedly, even at low wind speed. The improved intelligent fuzzy controller also contributes to minimizing the stress on the DC bus and ensures quality output power. The performance of the proposed charging station is verified for the real PHEV under real-world record of wind speed. All the energy sources, electric charging station and their controllers are designed in MATLAB/Simulink. Finally, the feasibility of proposed charging station is checked experimentally in the laboratory.

Temporally-coordinated optimal operation of a multi-energy microgrid under diverse uncertainties

This paper proposes a temporally-coordinated operation method for a multi-energy microgrid under diverse uncertainties from renewable energy sources, power loads and electricity transaction prices between the microgrid and the utility grid. The method aims to coordinate multiple energies in different timescales considering distinct properties of thermal and power energy: the combined cooling heat and power plants, power-to-thermal conversion units and thermal storage tanks are dispatched hourly in the day-ahead operation stage; in the intra-day online operation stage, the battery storage units are dispatched to supplement the day-ahead operation decisions every 5 min after the uncertainties are realized. Based on constraints linearization and uncertain scenario generation/reduction, the problem is converted to a deterministic two-stage mixed-integer linear programming equivalent model which can be solved efficiently. Finally, the proposed method is verified on an IEEE 33 bus distribution network based multi-energy microgrid. Compared with the existing methods, the simulation results indicate that the proposed method can better coordinate multiple energies with low operating cost and high robustness.

Time-Constrained Nature-Inspired Optimization Algorithms for an Efficient Energy Management System in Smart Homes and Buildings

This paper proposes two bio-inspired heuristic algorithms, the Moth-Flame Optimization (MFO) algorithm and Genetic Algorithm (GA), for an Energy Management System (EMS) in smart homes and buildings. Their performance in terms of energy cost reduction, minimization of the Peak to Average power Ratio (PAR) and end-user discomfort minimization are analysed and discussed. Then, a hybrid version of GA and MFO, named TG-MFO (Time-constrained Genetic-Moth Flame Optimization), is proposed for achieving the aforementioned objectives. TG-MFO not only hybridizes GA and MFO, but also incorporates time constraints for each appliance to achieve maximum end-user comfort. Different algorithms have been proposed in the literature for energy optimization. However, they have increased end-user frustration in terms of increased waiting time for home appliances to be switched ON. The proposed TG-MFO algorithm is specially designed for nearly-zero end-user discomfort due to scheduling of appliances, keeping in view the timespan of individual appliances. Renewable energy sources and battery storage units are also integrated for achieving maximum end-user benefits. For comparison, five bio-inspired heuristic algorithms, i.e., Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search Algorithm (CSA), Firefly Algorithm (FA) and Moth-Flame Optimization (MFO), are used to achieve the aforementioned objectives in the residential sector in comparison with TG-MFO. The simulations through MATLAB show that our proposed algorithm has reduced the energy cost up to 32.25% for a single user and 49.96% for thirty users in a residential sector compared to unscheduled load.

Ice versus battery storage; a case for integration of renewable energy in refrigeration systems of remote sites

Global inclination towards renewable energy projects, facilitates deployment of alternative energy systems in various scales. However, due to the noise in usable energy generation and fluctuations in the source availability, battery units are deemed as an integral part of any mini-grid energy generation system. Although, sharp turns in battery prices have taken place over the last few years, batteries are still one of the largest capital components of such systems. On the other hand, like many other heavy industries, mining industry is also closely interested in renewable energy generation on site because of certain environmental and financial reasons. Nonetheless, the size of feasible energy generation and attached storage units are still forcing mining companies to reconsider. In this regard, renewable energy based coolth storage systems can help mining companies to enhance the financial outcomes of mine air-conditioning projects where heavy refrigeration is demanded. This paper promotes power generation via renewable energy systems and proposes coolth/energy storage by analyzing two options. The financial impact of substituting battery storage units and downsizing the refrigeration plant size by storing the peak demand as coolth was also studied.

Security-Constrained Unit Commitment in Presence of Lithium-Ion Battery Storage Units Using Information-Gap Decision Theory

This paper proposes a robust framework for the security-constrained unit commitment (SCUC) of generating units, in the presence of lithium-ion battery energy storage units, using the information-gap decision theory (IGDT) technique. In the suggested model, the degradation cost of the battery storage units has been considered in the objective function as a highly influencing factor in the operation of such storage units. The framework is independent of probability density functions or membership of sets and enables the system operator to adjust the conservatism of the operating strategy (between overconservative and reckless) against the load demand uncertainty. In this respect, the SCUC model has been presented within a day-ahead scheduling problem on the hourly basis using mixed-integer linear programming. Finally, the proposed framework has been simulated on a typical 6-bus test system as well as IEEE 24-bus and IEEE 118-bus systems to verify the efficiency and the effectiveness of the model using the IGDT technique.

Unified energy management and load control in building equipped with wind-solar-battery incorporating electric and hydrogen vehicles under both connected to the grid and islanding modes

This paper presents a unified model for home energy management. The proposed model optimizes the cogeneration of wind, solar, and battery storage units. The introduced tool considers electric and hydrogen vehicles and provides optimal charging pattern for them. The water electrolyze is also modeled to produced breathable oxygen and hydrogen from water. As well, the load modeling options such as adjustable and interruptible loads are included in the planning in order to increase the flexibility and adeptness of the proposed energy management system. The uncertainties of wind and solar powers are included resulting in a stochastic programming. The proposed stochastic optimization problem is mathematically expressed as a mixed integer linear programming and solved by GAMS software. The problem minimizes cost of energy consumption in the building subject to the operational constraints of wind unit, solar panel, battery system, loads, electric-hydrogen vehicles, and electricity grid. The proposed test building is studied under two states including connected to the electrical grid and disconnected from the gird (i.e., islanding mode or NetZero energy home). The impacts of the proposed planning on the environmental pollution are also considered and simulated. The results verify that the proposed strategy can successfully utilize wind-solar-battery units to supply the load, charging the electric-hydrogen vehicles, and reduction of the pollution. As well, it is demonstrated that the operation of the home under islanding mode is completely different from the connected state.

Optimal joint strategy of wind battery storage unit for smoothing and trading of wind power

Wind power is intermittent and causes problems to the operation of electric power systems. This leads to the need for flexible battery storage units to smooth the wind power output. However, the volatile profile of wind power output affects the operational performance of battery units. We propose here an optimisation model to define the optimal hourly commitment of a wind battery storage unit while also including relevant operational constraints for the battery and modelling its degradation. Results show that although the wind farm can have reduced revenue in the shorter-term because of these constraints, the revenue of the wind farm increases in the longer-term and the lifetime of the battery is also extended.

Virtual storage plant offering strategy in the day-ahead electricity market

Energy storage is gaining an important role in modern power systems with high share of renewable energy sources. Specifically, large-scale battery storage units (BSUs) are an attractive solution due to their modularity, fast response and ongoing cost reduction.This paper aims to formulate, analyze and clarify the role of merchant-owned BSUs in the day-ahead electricity market. It defines virtual storage plant (VSP) as a set of BSUs distributed across the network. A VSP offering model is formulated as a bilevel program in which the upper-level problem represents the VSP profit maximization and operation, while the lower-level problem simulates market clearing and price formation. This mathematical problem with equilibrium constraints (MPEC) is converted into a mixed-integer linear program (MILP). This is afterwards expanded to a game of multiple VSPs formulating an equilibrium problem with equilibrium constraints (EPEC), which is solved using the diagonalization procedure.The proposed model is applied to an updated IEEE RTS-96 system. We evaluate the impact VSPs have on the locational marginal prices and compare the coordinated approach (all BSUs operated under a single VSP), i.e. the MPEC formulation, to the competitive approach (multiple VSPs competing for profit), i.e. the EPEC formulation.

A conditional depreciation balancing strategy for the equitable operation of extended hybrid energy storage systems

Various history life depreciations and energy characteristics of the facilities in the hybrid energy supply system challenge the conventional balancing strategies, which mostly aim to address the state-of-charge imbalance issues. This paper proposes a conditional depreciation balancing strategy to cope with the stated challenge. The conditional depreciation balancing strategy is based on extended hybrid energy storage systems, which consist of supercapacitors, batteries and equivalent battery storage units corresponding to heating systems. An integrated virtual battery model is adopted in the equivalent process of the heating system. The conditional depreciation is innovatively defined to evaluate the operation equitability of the extended hybrid energy storage systems. The equalization of the conditional depreciation is achieved by a multiscale searching algorithm. The proposed conditional depreciation balancing strategy is validated by a hybrid energy supply system of a four-floor building in Shanghai, China. Test results show that the fast dynamic response ability of the supercapacitors and the high energy density of the integrated virtual battery models are utilized fully by the proposed conditional depreciation balancing strategy. The maximum power changing rate of the supercapacitors, integrated virtual battery models and batteries is 0.86 kW/s, 0.03 kW/s, and 0.22 kW/s, respectively. The 24-h charging/discharging energy of the supercapacitors, integrated virtual battery models and batteries is 7.80 kWh, 18.37 kWh and 5.21 kWh, respectively. Compared to the state-of-charge balancing strategy, the proposed conditional depreciation balancing strategy decreases the maximum imbalance coefficient of the energy storage units by 82.74%. The life depreciation rate and the life depreciation cost of the extended hybrid energy storage system decrease by 47.05% and 53.85%, respectively.

Multi‐criteria optimal sizing of hybrid renewable energy systems including wind, photovoltaic, battery, and hydrogen storage with ɛ‐constraint method

Hybrid renewable energy systems (HRES) should be designed appropriately with an adequate combination of different renewable sources and various energy storage methods to overcome the problem of intermittency of renewable energy resources. A multi-criteria approach is proposed in this study to design an HRES including wind turbine, photovoltaic panels, fuel cell, electrolyser, hydrogen tank, and battery storage unit with an intermittent load. Three design criteria including loss of power supply probability, total energy loss (TEL), and the power difference between generation and storing capacity (as TELSUB) are taken into account in minimising the total cost of the system considering the interest rate and lifetime. The justifications and advantages of using these criteria are thoroughly discussed along with appropriate presentation of the results. The purpose of considering TEL and TELSUB is discussed thoroughly. The e-constraint method is used to handle practical constraints of the proposed multi-criteria problem to construct a multi-objective fitness function. Shuffled frog leaping algorithm is implemented to achieve better optimal results. The proposed approach is implemented using real wind speed and solar irradiance data for a specific location with an intermittent load demand. The results verify performance of the proposed multi-criteria design procedure.

Optimization and energy management of a standalone hybrid microgrid in the presence of battery storage system

In this study, an optimal energy scheduling of a standalone microgrid under system uncertainties is investigated and several operational strategies are tested to evaluate the system performance. The main objective of the proposed optimization energy management system is to improve energy utilization efficiency, decrease system fuel cost and gas emissions reduction by planning generations of energy resources hourly for the next day. The system is modeled as a constrained single-objective optimization problem in order to minimize the operation and generated emission costs. Employing an advanced dynamic programming method, the optimization problem is solved. In order to achieve optimal utilization of renewable resources in a microgrid environment and system cost-effective operations, the effectiveness of a battery storage unit has to be examined. Two different operational policies are investigated to examine the system behavior, where the energy production of a microgrid is supplied by generation units with and without access to a battery storage system. The obtained results show a considerable reduction in system total cost and produced emissions when the MG has access to battery storage system in the proposed second policy. Simulation results demonstrate the feasibility and effectiveness of the proposed technique in microgrid energy planning and implementation.

Fuel Saving on Diesel Genset using PV/Battery Spike Cutting in Remote Area Microgrid

Diesel Generator set was found to be a favorite power generator in a remote area. In this area, diesel genset usually consumes a significant amount of diesel fuel with higher fuel price than an urban area. Diesel Generator capacity conventionally prepared twice bigger or more than the existing load to prevent any load spike from designated equipment. This work implements an Energy Management System to cut the spike with the support from battery storage unit and photovoltaic module. Once the Energy Management System cut the load spike using battery/photovoltaics, Diesel Generator loads no longer need to be irrelevantly bigger than the existing load. The current experiment in the remote island at Raja Ampat archipelago indicates that the using of 80 kVA Diesel Generator can be reduced to 42 kVA Diesel Generator. This Diesel Generator replacement induces fuel consumption up to 50 %. With this designed work, a smart microgrid with PV-Battery-Diesel can be installed in a designated remote area with lower fuel consumption.

Optimal Operation Control for Multiple BESSs of a Large-Scale Customer Under Time-Based Pricing

This paper presents an online optimal operation framework for multiple battery energy storage systems (BESSs) of a large-scale customer under time-based pricing. Many publications have been reported on optimal battery operation techniques but most of them were analyzed in a simulation environment or a specifically designed test bed. However, this paper focuses on implementing the proposed scheme into actual multiple battery storage units and investigating the performance during long-term field operation. The operation framework consists of two levels: optimal scheduling and real-time dispatch. The optimal scheduling is calculated every hour, using a model predictive control based nonlinear optimization model, to minimize the daily electricity usage cost while regulating the peak. The real-time dispatch determines final commands to multiple battery systems by monitoring the system state and checking for any violations of the operation constraints. The two-level control scheme was designed to handle uncertainty in forecast load and estimated state-of-charge levels of batteries. The operation method was applied into the energy management system supervising one lithium-polymer BESS and two lead-acid BESSs of an industrial site. Comprehensive field operation results prove the reliability and effectiveness of the optimal operation framework.

Energy production potential and economic viability of grid-connected wind/PV systems at Saudi Arabian coastal areas

This paper analyzes the electricity production potential and economic viability of grid-connected wind/photovoltaic (PV) energy systems at two coastal cities, Yanbu and Dhahran in Saudi Arabia. First, wind energy is assessed based on the hourly wind speed observation data recorded over the entire year 2013 in the selected locations. Electricity generation potential is estimated using two wind turbines: Vestas V82 and V90 models. The results indicate that both locations have sufficient wind resources for wind turbine operation. Strong wind resources are more common at Dhahran than at Yanbu with wind speeds above 3.5 m/s, accounting for 60.12% of the wind data at Dhahran, which is higher than 51.2% of Yanbu. Grid-connected hybrid systems using Vestas V90 wind turbines had the highest net present cost (NPC) compared with other configurations. The inclusion of battery storage units slightly increases the NPC. Surprisingly, systems with the highest NPC produced the least electricity. In contrast, cheaper V82-based systems had the lowest NPC and levelized cost of energy and produced the most electricity. Hence, a grid-connected wind/PV system using V82 turbines is most economically viable. Incorporating a small battery storage unit in the systems minimizes capacity shortages and improves reliability at minimal extra cost. Using different wind turbines with a lower cut-in speed of 3 m/s could increase the electricity production, as 9.1% and 10.3% of wind observations at Yanbu and Dhahran, respectively, had a wind speed of 3 m/s.

Optimal battery storage operation for PV systems with tariff incentives

Many efforts are recently being dedicated to developing models that seek to provide insights into the techno-economic benefits of battery storage coupled to photovoltaic (PV) generation system. However, not all models consider the operation of the PV – battery storage system with a feed-in tariff (FiT) incentive, different electricity rates and battery storage unit cost. An electricity customer whose electricity demand is supplied by a grid connected PV generation system benefiting from a FiT incentive is simulated in this paper. The system is simulated with the PV modelled as an existing system and the PV modelled as a new system. For a better understanding of the existing PV system with battery storage operation, an optimisation problem was formulated which resulted in a mixed integer linear programming (MILP) problem. The optimisation model was developed to solve the MILP problem and to analyse the benefits considering different electricity tariffs and battery storage in maximising FiT revenue streams for the existing PV generating system. Real data from a typical residential solar PV owner is used to study the benefit of the battery storage system using half-hourly dataset for a complete year. A sensitivity analysis of the MILP optimisation model was simulated to evaluate the impact of battery storage capacity (kWh) on the objective function. In the second case study, the electricity demand data, solar irradiance, tariff and battery unit cost were used to analyse the effect of battery storage unit cost on the adoption of electricity storage in maximising FiT revenue. In this case, the PV is simulated as a new system using Distributed Energy Resources Customer Adoption Model (DER-CAM) software tool while modifying the optimisation formulation to include the PV onsite generation and export tariff incentive. The results provide insights on the benefit of battery storage for existing and new PV system benefiting from FiT incentives and under time-varying electricity tariffs.

Multiple roles coordinated control of battery storage units in a large‐scale island microgrid application

In order to build a large‐scale island microgrid with 100% penetration intermittent photovoltaic power generation as the only power source, a structure with multiple role battery energy storage systems (BESSs) is proposed in this paper based on the analysis of energy storage demand in the island microgrid and performance comparison of two types of batteries. The storage system in the proposed structure is composed of three types of functional BESSs. In detail, the master control units (MCUs) with LiFePO4 batteries are responsible for the voltage and frequency stability and instantaneous power balance, slave storage units (SSUs) with lead‐acid batteries are responsible for daily energy storage, and multi‐function units (MFUs) with LiFePO4 batteries are used for short‐time energy regulation. A hierarchical control structure is adopted in the system. At the local level, the converters of the MCUs are controlled as the voltage sources in paralleled mode as grid‐forming units, and those of SSUs and MFUs are controlled in the current source mode as grid‐feeding units. At the system level, a real‐time power balance coordinated control strategy is proposed, which has the capability of efficient and orderly operation of different types of BESSs. Simulation and practical operation analysis of the Qumalai 7.023 MW microgrid demonstrate the practicality and effectiveness of the research methods of the island microgrid. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Varying phase angle control in isolated bidirectional DC–DC converter for integrating battery storage and solar PV system in standalone mode

This study proposes a varying phase angle control (VPAC) in isolated bidirectional dc-dc converter (IBDC) for integrating battery storage unit to a DC link in a standalone solar photovoltaic (PV) system. The IBDC is capable of power transfer using high step up/down ratio between DC link and battery. The VPAC control proposed in this study effectively manage the power flow control between the battery storage unit and the solar PV fed DC link by continuously varying the phase angle between high voltage and low voltage (LV) bridge voltage of the IBDC. The solar PV system is incorporated with the maximum power point tracking using DC-DC converter. In order to control the voltage across the AC load a voltage source inverter is used. The study also presents the design aspects of the IBDC converter for the application considered. The performance of the proposed power flow control strategy has been studied through PSCAD/EMTDC simulation and validated using LPC 2148 ARM processor.

Experimental investigation of a new smart energy management algorithm for a hybrid energy storage system in smart grid applications

Renewable energy sources (RES) are becoming an important part of energy continuity for today’s electrical power grid, since RES are intermittent and unstable. Energy storage technologies are the only solution for this energy sustainability problem. In this study, a new Smart Energy Management Algorithm (SEMA) is proposed for Hybrid Energy Storage System (HESS) supplied from 3-phase 4-wire grid connected photovoltaic (PV) power system. HESS consisting of battery and ultra-capacitor energy storage units is used for energy sustainability from solar PV power generation system. Several different operation cases in HESS have been analyzed and experimentally tested by using the proposed SEMA. In experimental tests, load status of one sunny day and PV power profile have been created and tested dynamically by using SEMA and some of the test results in eight different operation modes are given in this paper. The battery group is charged with 1320W power by the system and remaining energy is transferred to the grid with 5% current harmonic via the inverter in one of the operation modes. The HESS is the most effective energy storage system due to its high power density, fast response, and high efficiency. The proposed system has been verified simulations results and experimental tests.