Photovoltaic Battery Energy Storage Systems Research Articles

Highly Efficient BBFIC for Grid-Connected Photovoltaic-Battery Energy Storage System Using Hybrid Optimization Assisted Framework

The conventional grid has been combined with a number of renewable energy solutions. As a result, the modern power system is constantly evolving with the help of various power electronics topologies. Due to the growing complexity and new system configuration, the modern power grid is subjected to many challenges and the risk factors are increasing exponentially. In order to evaluate the performance of grid-connected solar photovoltaic (PV) energy systems with battery energy storage system (BESS), highly efficient buck-boost-flyback integrated converter (BBFIC) experiments have been conducted. The whole cybernetics methodology utilized for real-time, closed-loop simulation, validation with other researchers, and numerous optimization techniques are applied in the research work. This paper is developing a new framework that focuses on increasing the voltage gain of the BBFIC for grid-tied PV-BESS. For enhancing the voltage gain of BBFIC, it is planned to optimize the duty cycle of the converter. For optimization purposes, this work deploys a hybrid algorithm termed as “alpha score based on salp-grey wolf optimization (AS-GWO)” that combines the concepts of both “grey wolf optimization (GWO) as well as salp swarm algorithm (SSA).” Finally, it has been demonstrated that the results are superior when compared to other approaches in terms of numerous aspects of measurements.

Grid-Interfaced Photovoltaic–Battery Energy Storage System With Slime Mold Optimized Adaptive Seamless Control

This article presents a photovoltaic (PV)–battery energy storage (BES) system functioning in both grid-tied and standalone modes while performing multifunctional operations, including reactive power compensation, power balancing, and power quality enhancement. The PV–BES system ensures uninterrupted power supply to the critical loads even during seamless transitions from grid-tied mode to islanded mode, and vice versa. The incremental conductance technique controls the boost converter and confirms maximum PV power extraction. The bidirectional converter connects BES to the dc bus. The dc bus voltage <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$({{V}_{dc}})$</tex-math></inline-formula> is regulated by a slime mold optimized proportional-integral controller to limit the dynamic state variation and improve stability. The voltage-source converter (VSC) is controlled by a minimum kernel-risk-sensitive mean <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i> -power loss algorithm during the grid-synchronization mode. In contrast, the voltage control algorithm executes islanded control of VSC. The VSC control transition is achieved seamlessly without any significant disturbance at the point of common coupling. The hardware test results demonstrate that the present system remains stable during dynamic conditions and performs adequately as per the IEEE 519-2014 standard.

Integrated PV–BESS-Fed High Gain Converter for an LED Lighting System in a Commercial Building

The demand for electricity is rapidly growing and renewable energy sources such as solar, wind and tidal energy can compensate the demand to a substantial level. Among these, solar energy is abundant, scalable and is cheaper. The generated energy can be used in an efficient way if the DC output is directly supplied to the load instead of converting it to AC. Every electrical system is capable of operating in DC and, for example, energy efficient Light Emitting Diode (LED) lights have become popular as they provides more lumens with less power consumption and also can be directly operated from DC. LED lighting system in large commercial buildings has irradiance levels which vary sigificantly during operation. Extracting maximum power from the energy system and maintaining constant voltage output at different loads is another challenge. This paper proposes a solar Photo Voltaic (PV)-based energy system including Battery Energy Storage System (BESS) for supplying LED lamps to a commercial building through a modified high gain Luo converter. The Perturb and Observe control algorithm has been used for maximum power extraction from a PV cell whereas PI (Proportional Integral) controllers maintain constant output voltage from PV–BESS against different irradiance levels. To supply the desired voltages to the LED lighting system, a modified high gain Luo converter is designed. To make the output voltage constant at different load currents, PI and Sliding Mode Controllers (SMC) are designed with the help of the state-space average model. It is found that the sliding mode controller outperforms the PI controller in terms of behavior in the transient period and tracking capability. The system is simulated using MATLAB/Simulink®. The Sliding Mode Controller has a 95% less transient period and is 75% faster in tracking capability when compared to other controllers. The system could be incorporated with the PV source to obtain green energy.

Community Battery Storage Systems Planning for Voltage Regulation in Low Voltage Distribution Systems

The regulation of the grid voltage within operational limits becomes increasingly challenging as residential photovoltaic (PV) adoption rises. Therefore, this study proposes a method for the efficient planning of multiple community battery energy storage systems (BESS) in low voltage distribution systems embedded with high residential rooftop PV units. A bi-level optimization method based on a Neural Network Optimization Algorithm is developed to regulate the voltage in grid-connected solar PV. Since BESS characteristics are crucial for the reliable operation of the distribution networks, the objective of the bi-level optimization problem is to optimally place and operate BESS collectively at a distributed system level. The charging/discharging protocol of the batteries management system is obtained utilizing linear programming that minimizes the daily voltage signal. Simulations were carried out on a modified IEEE low voltage test feeder to examine the impact of PV integration and BESS installation on the voltage profile. Experimental results show the efficacy of the proposed method in enabling the utility to determine the optimal location, capacity, and number of BESS in the distribution system to keep the network voltage magnitude within acceptable bounds. In addition, results demonstrate that the network topology, load profiles, and amount of PV power highly influence the BESS characteristics.

Impact of climate on photovoltaic battery energy storage system optimization

The optimization of the battery energy storage (BES) system is critical to building photovoltaic (PV) systems. However, there is limited research on the impact of climatic conditions on the economic benefits and energy flexibility of building PV–BES systems. Taking an office building as an example, a method for minimizing the total cost of a PV–BES system was established using a mixed integer nonlinear programming model to optimize the BES capacity. Then, the effects of the grid import/export power limit and peak feed-in tariff on BES capacity optimization were investigated, and the various economic benefits of the PV–BES system were discussed and analyzed accordingly. The results show that the operating cost was reduced significantly when the PV–BES system was employed in any of the evaluated climates; the relative payback period of the PV–BES system in Changsha was the minimum at 1.4 years. The grid import power limit and the peak feed-in tariff had a much greater impact on the battery capacity, energy flexibility, and economic benefits of the PV–BES system than the grid export power limit. The results of this study provide guidance for the application of PV–BES systems in different climates.

Optimal battery schedule for grid-connected photovoltaic-battery systems of office buildings based on a dynamic programming algorithm

The optimal schedule of energy storage systems is an effective way to improve the economy and stability of grid connected photovoltaic-battery energy storage systems (PV-BESS). This study presents an operation strategy considering economic feasibility and photovoltaic self-consumption rate (SCR) for the energy management of office buildings under time-of-use (ToU) electricity price. The strategy aims to optimize FiT revenue streams for the PV-BESS by scheduling the overall energy flow in real time based on a dynamic programming algorithm. The battery control strategy based on a dynamic programming algorithm can control the energy flow in a flexible way to minimize net present value (NPV) in a typical year, while taking such factors as dynamic electricity price, the battery cycling aging, and demand response characteristics into account. An existing PV-BESS used for a middle-size office building in Beijing was taken as a case study to evaluate the optimization model. It is shown that the dispatch strategy could achieve superior performance in the cold region in China. Additionally, the indices affecting economic performance were figured out to validate the feasibility of the proposed algorithm. The results show that while the unit cost of energy storage is dropped to about 100$/kWh, the system could gain revenue under different electricity prices. Lastly, it is concluded that electricity price is the most sensitive parameter to the system's economy through sensitivity analysis.

An online energy management tool for sizing integrated PV-BESS systems for residential prosumers

This paper presents an online energy management tool that suggests the most suitable size of a hybrid photovoltaic-battery energy storage system (PV-BESS) to residential prosumers based on their self-sufficiency expectations. An offline analysis of electricity generation and consumption expected from 128 residential prosumers has been carried out at first in order to find out their self-sufficiency map with different sizes of PV and BESS; this is carried out by the genetic algorithm based energy management (GA) presented in a previous work. Subsequently, a number of clusters have been defined, each of which groups prosumers that share similar self-efficiency maps; particularly, clustering has been carried out and refined by identifying the most significant features of prosumers belonging to the same cluster, as well as those that differentiate prosumers belonging to different clusters. As a result, it has been revealed that the habit of usage of some appliances, such as Heat Ventilation Air Conditioning system (HVAC) and water heater, and peak electricity consumption represent the most important features influencing clustering. Based on these outcomes, the proposed online energy management tool is able to assign a prosumer to the most suitable cluster just based on the answers to a few simple questions related to energy consumption habits, providing the corresponding self-efficiency map almost immediately. The results achieved by the proposed tool, which is currently running online, are promising and show that significant self-sufficiency increases can be obtained, allowing the proper choice of PV-BESS depending on specific prosumer’s needs and expectations.

The impact of a subsidized tax deduction on residential solar photovoltaic-battery energy storage systems

In May 2020, as a response to COVID-19, the Italian government introduced a subsidized tax deduction of 110% over five years for the realization of battery energy storage systems integrated into photovoltaic (PV) plants in residential settings. To assess the effectiveness of this measure, we applied an economic model using net present value, and we estimated the conditions under which economic feasibility would be reached, using break-even point analysis. The results showed that the 110% tax deduction significantly reduced the impact of the battery investment cost on profitability. The share of self-consumed energy emerged as the most significant determinant of economic feasibility.

Research on energy management strategy of photovoltaic–battery energy storage system

Abstract Photovoltaics have the advantages of being clean and renewable and have gained a wide range of applications. It is promising to use photovoltaic energy for the power supply of buildings, as the building sector accounts for a large portion of global energy consumption with a constantly increasing trend. However, photovoltaics are greatly affected by time and environment, and it is usually combined with batteries to form a photovoltaic–battery energy storage system to meet the load demand. This paper aims to analyze and compare energy management strategies of an on-grid solar photovoltaic–battery system for a real building project in a typical May and October region, but unlike other studies, the strategies used in this paper are very simple and easy to implement. It can also realize photovoltaic, battery and grid to meet the load power demand. Two strategies are used in this paper. Strategy 1 is to maximize the utilization of the energy generated by photovoltaics: while the energy generated by photovoltaics cannot meet the load demand, the battery will provide energy, and while the battery cannot meet the load demand, the grid will provide energy. The photovoltaic energy is given priority to the battery under the premise of meeting the load demand. Strategy 2 is to use the time-of-use electricity price, and the battery obtains cheap electricity at night to meet the load of the high electricity price the next day. The feasibility of the strategy used is demonstrated by actual data of buildings and photovoltaic–battery energy storage systems. This study can provide theoretical references for the energy management and system operation to facility managers and building occupants.

Optimal Operation Approach With Combined BESS Sizing and PV Generation in Microgrid

Photovoltaic (PV) energy generation in microgrids (MGs) is increasing. Battery energy storage systems (BESSs) reduce the fluctuations in PV outputs caused by the intermittent availability of solar energy. Although BESSs are advantageous for stable MG operation, they are still relatively expensive. By remaining within the operational limits during normal and contingency operation, optimal sizing of BESS is required to maintain security considering cost of MG system. This paper proposes a BESS sizing optimization approach for MGs by solving the security constrained optimal power flow (SCOPF), considering the stochastic errors in forecasting the PV outputs. The degree of compensation for the solar energy forecasting error is firstly configured. To address these errors, the combined PV and BESS operation system is modeled by applying a control strategy to smooth PV fluctuations and minimize battery life degradation. BESS sizing optimization, under a certain degree of compensation, minimizes the PV penalty cost and BESS operation cost. The optimal BESS capacity and schedule are then obtained for the MG. To enhance the convergence and computational efficiency, decomposed-probabilistic security constrained optimal power flow (D-PSCOPF) is proposed. It efficiently solves the problem by dividing it into a master problem and a slave problem. The base case solution is computed in the slave problem, which induces the partial optimal size of BESS. By adding the feasibility cut through the violation of the slave problem, the master problem derives the optimal BESS capacity. Different case studies were analyzed, confirming the superiority and computational efficiency of the proposed approach.

Optimal Battery Energy Storage System Scheduling within Renewable Energy Communities

In this work, a strategy for scheduling a battery energy storage system (BESS) in a renewable energy community (REC) is proposed. RECs have been defined at EU level by the 2018/2001 Directive; some Member States transposition into national legislation defined RECs as virtual microgrids since they still use the existing low voltage local feeder and share the same low-medium voltage transformer. This work analyzes a REC which assets include PV generators, BESS and non-controllable loads, operating under the Italian legislative framework. A methodology is defined to optimize REC economic revenues and minimize the operation costs during the year. The proposed BESS control strategy is composed by three different modules: (i) a machine learning-based forecast algorithm that provides a 1-day-ahead projection for microgrid loads and PV generation, using historical dataset and weather forecasts; (ii) a mixed integer linear programming (MILP) algorithm that optimizes the BESS scheduling for minimal REC operating costs, taking into account electricity price, variable feed-in tariffs for PV generators, BESS costs and maximization of the self-consumption; (iii) a decision tree algorithm that works at the intra-hour level, with 1 min timestep and with real load and PV generation measurements adjusting the BESS scheduling in real time. Validation of the proposed strategy is performed on data acquired from a real small-scale REC set up with an Italian energy provider. A 10% average revenue increase could be obtained for the prosumer alone when compared to the non-optimized BESS usage scenario; such revenue increase is obtained by reducing the BESS usage by around 30% when compared to the unmanaged baseline scenario.

Precise current sharing and decentralized power management schemes based on virtual frequency droop method for LVDC microgrids

One of the challenging issues in DC microgrids attracted by many researchers is the current sharing enhancement among distributed generations (DGs) with different rated currents and/or lines impedances. In this paper, DG topology is considered comprising photovoltaic (PV) system as power resource and battery energy storage system (BESS). By inspecting the frequency droop control of synchronous generators, a unique corrective sinusoidal term is added to the output voltage in DC-DC converters of each DG with purpose of current sharing control between DC DGs based on their nominal capacities. This virtual decentralized current sharing scheme named as the frequency droop method (FDM) can accurately regulate the point of common coupling (PCC) voltage without any communication link. Moreover, a decentralized power management scheme with different operating modes for PV system and BESS is proposed in this paper based on the state of charge of BESS and the frequency obtained from FDM scheme. The performance of FDM and power management schemes is investigated by time domain off-line and real-time simulations in MATLAB/SIMULINK environment. Seven case studies are implemented considering the effects of load and solar irradiance variations under equality and inequality of lines impedances as well as rated currents, mode transition, and plug-and-play ability. By applying the proposed control schemes, the purposes of precise current sharing and DC-link voltage regulation are achieved smoothly with an acceptable transient compared to an existing power sharing method. Also, FDM scheme is more reliable than available methods due to its independence on line impedance.

A United Control Strategy of Photovoltaic-Battery Energy Storage System Based on Voltage-Frequency Controlled VSG

At present, the installed capacity of photovoltaic-battery energy storage systems (PV-BESs) is rapidly increasing. In the traditional control method, the PV-BES needs to switch the control mode between off-grid and grid-connected states. Thus, the traditional control mode reduces the reliability of the system. In addition, if the system is accidentally disconnected from the grid or the energy storage battery fails to work normally, the DC voltage of the inverter increases or decreases rapidly. To address these two problems, in this paper, a united control strategy is proposed. In the case of grid connection, based on the voltage-frequency controlled VSG strategy, the strategy adjusts the output power of the VSG by changing the position of the primary frequency modulation curve. This method can ensure that, after the system is connected to the grid, excess PV power can be sent to the grid, or power can be absorbed from the grid to charge energy storage. In the off-grid state, the strategy uses FPPT technology and superimposes a voltage component onto the voltage loop to quickly balance the DC power and AC power of the inverter. This strategy can improve the reliability of the system’s power supply if the energy storage fails to work normally. Finally, a PV-BES model was built using MATLAB-Simulink, and the simulation results proved the effectiveness of the proposed strategy.

Analysis of Lightning-Induced Voltages Effect with SPD Placement for Sustainable Operation in Hybrid Solar PV-Battery Energy Storage System

This paper discusses the lightning-induced voltage effect on a hybrid solar photovoltaic (PV)-battery energy storage system with the presence of surge protection devices (SPD). Solar PV functions by utilizing solar energy, in generating electricity, to supply to the customer. To ensure its consistency, battery energy storage is introduced to cater to the energy demand. For the countries located at the Equator, lightning has always become a major issue for the system to operate at maximum efficiency, due to its nature of installation in open space areas where the equipment may suffer serious damage that may stop the operation abruptly. To minimize the possible damages, insulation coordination on the lightning protection system is needed. Hence, three case studies, i.e., lightning current amplitude, lightning strike distance, and cable length are presented in this paper, which the quantified analysis is taking into account, to identify the performance of the system with the single installation of SPD Class II at DC and AC sides. The simulation results have contributed towards a better understanding of the importance of SPDs, and the need to properly coordinate according to the standard, taking into account the quantified information obtained from this work, hence providing the necessity of proper installation of SPD will provide better maintenance and prolong the lifespan of the equipment.

Impacts of Lightning-Induced Overvoltage on a Hybrid Solar PV–Battery Energy Storage System

With increased electrical energy demands projected in the future, the development of a hybrid solar photovoltaic (PV)–battery energy storage system is considered a good option. However, since such systems are normally installed outdoors and in open areas, they are vulnerable to lightning strikes and may suffer from malfunctions or significant damage to sensitive components, which may result in a major breakdown and loss of revenue due to equipment replacement costs and inefficient operation. Thus, the objective of this paper is to investigate the effect of lightning-induced overvoltage on a hybrid solar PV–battery energy storage system, considering indirect lightning strikes nearby the system. The presented hybrid solar PV–battery energy storage system and lightning-induced overvoltage are modeled in Electro-Magnetic Transient Program-Restructured Version (EMTP-RV) software. The lightning-induced overvoltage is simulated based on a lightning waveshape of 10/350 µs using the Heidler expression, whilst the Rusck model is used to simulate the lightning-induced overvoltage. Different lightning current amplitudes (3, 19, and 169 kA), lightning strike locations (20, 50, and 100 m), and cable lengths (5, 10, and 20 m) are used to investigate the induced effects on the system and on the impulse withstand voltage of 6kV, as stated in MS IEC 60664-1 for solar PV–battery systems and inverters at the DC side. The results indicate that as the lightning strike distance increases from 20 to 100 m, the percentage of strikes exceeding the impulse withstand voltage reduces from 67% to 54% at 19 kA. At 169 kA, the impulse withstand voltage is exceeded by more than 100%, regardless of the strike distance (from 20 to 100 m). Furthermore, differences in cable length do not have much impact on the lightning-induced overvoltage due to the small voltage drop across the short cable length. This study provides useful information for PV systems owners and will be useful in assigning appropriate lightning protection schemes for PV farms.

Sliding Mode Control of Hybrid Renewable Energy System

This paperpresents an ANFIS based adaptive sliding mode control (ASMC) of a standalone single phase microgrid system. The proposed microgrid system integrates a micro-hydro turbine driven single-phase two winding self-excited induction generator (SEIG) with a wind driven permanent magnet brushless DC (PMBLDC) generator, solar photo-voltaic (PV) array and a battery energy storage system (BESS). These renewable energy sources are integrated using a single-phase voltage source converter (VSC). The ASMC based control algorithm is used to estimate the reference source current which controls the single-phase VSC and regulates the voltage and frequency of the microgrid in addition to harmonics current mitigation. The adaptive sliding mode control with ANFIS is used to maintain the energy balance among wind, micro-hydro, solar PV power and BESS, which controls the frequency of standalone microgrid. Simulation results from MATLAB/SIMULINK of the proposed microgrid shows that the grid voltage and frequency are maintained constant while the system is following various changes in dynamic state such as sudden change in wind speed, changes in solar insolation level and changes in loads.

Policy options for enhancing economic profitability of residential solar photovoltaic with battery energy storage

Share of solar photovoltaic (PV) is rapidly growing worldwide as technology costs decline and national energy policies promote distributed renewable energy systems. Solar PV can be paired with energy storage systems to increase the self-consumption of PV onsite, and possibly provide grid-level services, such as peak shaving and load levelling. However, the investment on energy storage may not return under current market conditions. We propose three types of policies to incentivise residential electricity consumers to pair solar PV with battery energy storage, namely, a PV self-consumption feed-in tariff bonus; “energy storage policies” for rewarding discharge of electricity from home batteries at times the grid needs most; and dynamic retail pricing mechanisms for enhancing the arbitrage value of residential electricity storage. We soft-link a consumer cost optimization model with a national power system model to analyse the impact of the proposed policies on the economic viability of PV-storage for residential end-users in the UK. The results show that replacing PV generation incentives with a corresponding PV self-consumption bonus offers return on investment in a home battery, equal to a 70% capital subsidy for the battery, but with one-third of regulatory costs. The proposed energy storage policies offer positive return on investment of 40% when pairing a battery with solar PV, without the need for central coordination of decentralized energy storage nor providing ancillary services by electricity storage in buildings. We find that the choice of optimal storage size and dynamic electricity tariffs are key to maximize the profitability of PV-battery energy storage systems.

Decision Support Framework for Resilience-Oriented Cost-Effective Distributed Generation Expansion in Power Systems

Resilience of electricity grids to rare but severely disruptive events, such as natural disasters, has emerged in recent years as an important aspect in power system planning. Development of resilience-oriented techniques are needed due to the limitations of reliability-oriented methods in addressing large unexpected outages. This article presents a novel decision analysis approach to enhance the resilience of a power distribution system by leveraging the distributed nature of solar photovoltaic (PV) and battery energy storage system (BESS) resources. The proposed decision-making framework uses an analytic hierarchy process to evaluate different possible allocations of PV and BESS resources to load buses for multiple contingencies based on resilience enhancement and cost. Each allocation plan provides the size of PV arrays and BESS units to be installed at each bus within the distribution system. A deterministic formulation ranks line outage scenarios based on unserved load. The tradeoff between cost and resilience is modeled via cost-effectiveness analysis (CEA) that indicates the preferability of each allocation plan. The main contribution of this article is the development of an adaptable and computationally feasible decision support framework to determine cost-effective configurations of PV arrays and BESSs for mitigating the effects of power line outage contingencies. To evaluate the proposed framework, a case study is carried out on the IEEE 33-bus radial distribution system. The results show that the proposed method can offer effective guidance to the planner for making informed investment decisions and achieving cost-effective resilience enhancement.

Trading-oriented battery energy storage planning for distribution market

In this paper, we present a trading-oriented battery energy storage system (BESS) planning model for a distribution market. The proposed planning model is formulated as a mutual-iteration and multi-objective two-stage optimization problem. The first stage is designed to optimize the internal resources allocation including PV system, wind turbine, gas turbine and BESS. Then a double-side auction model named as averaging pricing market (APM) mechanism is presented in the second stage, which aims at solving the issue of energy trading benefit loss caused by the relatively high difference between time-of-use (ToU) electricity price and feed-in-tariff. The contribution of this paper lies in combining the planning of BESS with the optimization of the distribution electricity market. Numerical results on a modified IEEE 24-bus system are presented to demonstrate the superiority of the two-stage optimization model and the sensitivity of the model is also investigated based on regret analysis.

Optimal Design Model for a Residential PV Storage System an Application to the Spanish Case

Self-consumption of photovoltaic energy is being promoted as an effective way for energy consumption in residential households. The European Directive 944/2019 promotes the use of green energy and battery energy storage systems (BESS) for self-consumption and, in Spain, the 244/2019 Royal Decree of the Spanish electrical regulatory framework allows the self-consumption of energy with a photovoltaic (PV) facility for residential use, as well as the injection of the surplus energy into the grid for which compensation will be received. At the same time, new developments in PV and BESS technologies reduce the costs of facilities, a fact that can increase the profitability of self-consumption through PV energy. This study evaluates the profitability of a household PV facility with BESS using a model based on real market prices, hourly data from user smart meters, and their own location; especially, the model gives the best configuration of PV panels power and BESS capacity. The financial indicators taken as reference for the results and conclusions are the Net Present Value (NPV), Internal Rate of Return (IRR), and Investment Return (IR). Our method examines also the effect of the BESS and PV panel costs on the profitability of the facility. Unlike other studies, our model is based on actual (not simulated) demand and price data, and it can be easily extended to other locations and market prices.