PV-battery Hybrid System Research Articles

Common-Mode Voltage Reduction Method-Based Flexible Power Control for Multiport DC–AC Converter in PV–Battery Hybrid System

Common-Mode Voltage Reduction Method-Based Flexible Power Control for Multiport DC–AC Converter in PV–Battery Hybrid System

Unified control of high gain DC-DC converter for PV-battery hybrid system in a standalone and DC-microgrid applications

This paper presents power management and control of standalone PV and battery integrated hybrid system using high gain converter suitable for the DC Microgrid applications. The necessity of high gain DC-DC converter is raised due to generation of low output voltage of PV system. The attractive features of high gain converter are high voltage gain, continuous input current and suitability for integration of multiple input sources. The perturb and observe algorithm is used for tracing the maximum power point from solar and intermittency of solar is compensated by energy storage element battery. In the suggested hybrid system, the battery charging is carried out from DC bus voltage through buck converter and discharging to the load through high gain DC-DC converter. In the proposed work, Simulink model of proposed system rated for 1.2 kW PV module, 120 V, 42 Ah battery is developed using Simulink of MATLAB software and results are obtained under different operating conditions. Scaled experimental model of proposed hybrid system is implemented in laboratory environment using STM32F407VGT6 microcontroller and results are validated.

DC-link Voltage Control Using Battery-side Controller in a Hybrid System

This work aims to model the PV-Battery hybrid system as well as design a controller used to stabilize the voltage at the DC-link for the load. It is intended to make the voltage between the battery and PV system stable, or it can be said that the voltage at the load becomes stable. The input system used is battery current and PV current is considered as a disturbance because of its characteristics that cannot be controlled when generating maximum power. Therefore, a full order state feedback controller with integrator is designed to reduce the steady state error. In addition, an algorithm is needed to estimate the PV current and at the same time reduce sensor utilization. This work utilizes Disturbance Observer to estimate these parameters as well as disturbance rejection. To verify the proposed system, there are three scenarios. The first scenario tests the system with constant PV load and current. The second scenario tests the system with varying PV current, and finally tests the system with varying load and current. From the scenarios, the system performed well with output voltage RMSE values equal to 0.003 in the first scenario, 0.4 in the second scenario, and 0.481 in the third scenario.

Design and assessment of energy management strategy on rail coaches using solar PV and battery storage to reduce diesel fuel consumption

This study is focused to develop energy management strategy using battery backup source for electrical load of the rail coaches. To assess the effectiveness of battery storage inclusion, the higher and lower battery state of charge cases were simulated using parametric approach where solar Photovoltaic (PV) power, battery state of charge (SoC) and load consumption parameters were used develop the controller. Fuzzy logic and Adaptive neuro-fuzzy interference system (ANFIS) approaches were used for the controller design. It was found that the Solar PV-battery hybrid system helps in a significant reduction in diesel consumption i.e., about 10 % in diesel savings with higher SoC values and 7 % of diesel savings during worst cases. Annually, while comparing two controllers, it was found that the annual diesel savings increase from PKR 604.17 million to PKR 684.00 million, while the amount of CO2 emissions reduction increase from 6932.70 to 7848.75 tons, while using ANFIS control.

Zero-Vector-Regulation-Based Closed-Loop Power Distribution Strategy for Dual-DC-Port DC–AC Converter-Connected PV–Battery Hybrid Systems

The dual-dc-port dc-ac converter-connected photovoltaic (PV)-battery hybrid systems present high-efficiency and low-cost features with single-stage power conversion as PV and battery are connected to the grid directly. However, it is challenging to achieve flexible power distribution in this configuration due to its coupled features in grid-side current tracking and power distribution. To deal with this issue, this paper proposes a zero vector regulation-based closed-loop power distribution strategy for the dual-dc-port dc-ac converter-connected PV-battery hybrid systems. By modeling the dual-dc-port dc-ac converter as an equivalent two-level one, an extra control freedom for power regulation is accessible and a closed-loop power control is adopted for flexible power distribution by zero vector regulation. With the proposed power distribution strategy, the desirable quality of the grid-side current is achieved without complicated voltage vector synthesis, along with good adaptivity to different modes/voltages and flexible power control. Besides, detailed power distribution discussion and analysis with different proportions of zero vector are carried out. Finally, the islanded microgrid experimental tests are conducted to verify its effectiveness and feasibility.

Towards rural net-zero energy buildings through integration of photovoltaic systems within bio-based earth houses: Case study in Eastern Morocco

Off-grid rural electrification programs involving renewable energy provide effective ways to boost the availability of power in remote areas. Herein, the combination of local bio-based building materials with appropriate sizing of a photovoltaic (PV) system to achieve energy-efficient rural housing in developing countries is investigated. The study focused on the fabrication and laboratory testing of a building material incorporating plant fibers, followed by a feasibility analysis of an integrated stand-alone PV system. EnergyPlus software was used to assess the energy-saving potential of bio-based building envelopes, and Homer Pro software was used for techno-economic optimization. Using a case-study building, various configurations were evaluated in terms of levelized energy cost and net present cost. According to the experimental results, the inclusion of 8 wt% Alfa fibers in earth blocks led to a noteworthy enhancement in the thermal resistance and time lag of the building envelope. Specifically, the improvement ranged from 0.549 to 1.125 m2K/W and from 18.5–h to 23.2–h, respectively, compared to using earth alone. This improvement resulted in a substantial decrease in the building's annual energy consumption, with a reduction of 24.3% for heating and 26.7% for cooling. Furthermore, the techno-economic analysis revealed that the electricity provided by a PV-battery hybrid system was 100% renewable and emission-free, with an energy cost of approximately $0.218/kWh and a present net cost of $11,560.21 These findings indicated that combining available solar energy with locally produced bio-based construction materials could be a viable approach for achieving carbon neutrality and building energy-efficient ulta-low-cost rural housing.

Profit Maximization with Imbalance Cost Improvement by Solar PV-Battery Hybrid System in Deregulated Power Market

The changeable nature of renewable sources creates difficulties in system security and stability. Therefore, it is necessary to study system risk in several power system scenarios. In a wind-integrated deregulated power network, the wind farm needs to submit the bid for its power-generating quantities a minimum of one day ahead of the operation. The wind farm submits the data based on the expected wind speed (EWS). If any mismatch occurs between real wind speed (RWS) and expected wind speed, ISO enforces the penalty/rewards to the wind farm. In a single word, this is called the power market imbalance cost, which directly distresses the system profit. Here, solar PV and battery energy storage systems are used along by the wind farm to exploit system profit by grasping the negative outcome of imbalance cost. Along with system profit, the focus has also been on system risk. The system risk has been calculated using the risk assessment factors, i.e., Value-at-Risk (VaR) and Cumulative Value-at-risk (CVaR). The work is performed on a modified IEEE 14 and modified IEEE 30 bus test system. The solar PV-battery storage system can supply the demand locally first, and then the remaining power is given to the electrical grid. By using this concept, the system risk can be minimized by the incorporation of solar PV and battery storage systems, which have been studied in this work. A comparative study has been performed using three dissimilar optimization methods, i.e., Artificial Gorilla Troops Optimizer Algorithm (AGTO), Artificial Bee Colony Algorithm (ABC), and Sequential Quadratic Programming (SQP) to examine the consequence of the presented technique. The AGTO has been used for the first time in the risk assessment and alleviation problem, which is the distinctiveness of this work.

A New Energy Management Control Strategy for PV-Battery Hybrid System

A New Energy Management Control Strategy for PV-Battery Hybrid System

Design and control of hybrid energy microgrid system using renewable energy sources

Decentralized distributed generation technologies based on renewable energy resources like Photo Voltaic (PV) or/and Wind Turbine Generators (WTG) address the above barriers to large extent and are therefore considered as emerging alternate power solutions to telecommunication base stations. Three stand-alone SPV power systems using different storage technologies i.e. PV-Battery system, PV-Fuel Cell (FC) system and SPV-FC-Battery system are optimized, analysed, compared in paper. PV configurations with tracker also included. According simulation results observed that PV-Battery hybrid system with maximum power point tracker most economical solution. Cost and energy sensitivity with solar radiation data also analysed in this paper. Hybrid system modelling, designing of each component of Hybrid system is done in MATLAB sim power. In this paper, the hybrid system modelled is used for the different insulation, noticed the power output change with the insulation input change. Simulation is done for a step change of 1 kW for the PV-FC system. Different Maximum power point tracking algorithms are discussed, from these algorithms P&O method is implemented in MATLAB. Simulation done for one module and compared the result with actual result. This MPPT tracker used in the PV-FC, PV-Battery-FC hybrid systems for extracting the maximum power available from the PV system.

A multi-objective predictive energy management strategy for residential grid-connected PV-battery hybrid systems based on machine learning technique

This paper proposes a multi-objective predictive energy management strategy based on machine learning technique for residential grid-connected hybrid energy systems. The hybrid system considered in this study comprise three principal components: a photovoltaic array as a renewable energy source, a battery bank as an energy storage system, and residential building as an electric load. The proposed strategy comprises three levels of controls: a logical level to manage the computational load and accuracy, a dual prediction model based on residual causal dilated convolutional networks for energy production and electric load on system, and a multi-objective optimization for efficient trade of energy with the utility grid by battery charge scheduling. The prediction model used in this study can provide one-step ahead photovoltaic energy production and load forecast with sufficient accuracy using a sliding window training technique and can be implemented on an average personal computer. The energy management problem comprises multiple objectives that include minimization of energy bought from utility grid, maximization the battery bank’s state-of-charge and reduction of carbon dioxide emission. The optimization problem is constrained to the maximum allowed carbon dioxide production and battery bank’s state-of-charge limits. The proposed strategy is tested for static and dynamic electricity prices using hourly energy and load data. Simulation results show a high coefficient of determination of 93.08% for energy production predictions and 97.25% for electric load predictions using proposed dual prediction model. The proposed prediction model is benchmarked against naïve prediction, support vector machine and artificial neural network models using several metrics and shows noticeable improvements in prediction accuracy. Not only the proposed strategy combined with the proposed prediction model can handle over 50% of the total yearly load requirement but also shows a significant decrease in electricity bill and carbon dioxide compared to residential buildings without hybrid energy systems and hybrid energy system without energy management strategy.

Comparative techno-economic assessment of integrated PV-SOFC and PV-Battery hybrid system for natural gas processing plants

Natural gas will remain among the leading sources of energy, at least for the next few decades. Further, it is necessary to make natural gas processing operation a cost-competitive, clean, and efficient energy source, and less dependent on the grid. A comparative investigation based on two case studies is presented in this paper for a natural gas processing plant; an integration of Photovoltaic panels with Battery Energy Storage System (PV-BESS) and an integration of Photovoltaic panels with Solid Oxide Fuel cell (PV–SOFC) technologies. The aim is to be more independent from the grid for efficient operations and to reduce the emissions by introducing renewable energy in gas processing operation plant.A techno-economic analysis is performed for both cases considering a PV capacity of 33.5 MW. The outcome of this study indicates that for 25 years of operation, the Levelized cost of electricity (LCOE) for PV-BESS is found to be 0.16 US$/kWh, and for PV-SOFC is 0.11 US$/kWh, which makes the PV-SOFC option more economical and feasible than PV-BESS. Besides, in the projected scenario where investment cost is expected to reduce, PV-SOFC’s IRR is 3% and has a positive NPV of 5 Million USD$ for an internal rate of 4%. Furthermore, the LCOE for PV-SOFC in this scenario is around 0.04 USD$ per kWh, which is still less than the LCOE of PV-BESS and less than the tariff set by the Qatari electric authority for bulk industries.

An Intelligent Controlling Method for Battery Lifetime Increment Using State of Charge Estimation in PV-Battery Hybrid System

In a photovoltaic (PV)-battery integrated system, the battery undergoes frequent charging and discharging cycles that reduces its operational life and affects its performance considerably. As such, an intelligent power control approach for a PV-battery standalone system is proposed in this paper to improve the reliability of the battery along its operational life. The proposed control strategy works in two regulatory modes: maximum power point tracking (MPPT) mode and battery management system (BMS) mode. The novel controller tracks and harvests the maximum available power from the solar cells under different atmospheric conditions via MPPT scheme. On the other hand, the state of charge (SOC) estimation technique is developed using backpropagation neural network (BPNN) algorithm under BMS mode to manage the operation of the battery storage during charging, discharging, and islanding approaches to prolong the battery lifetime. A case study is demonstrated to confirm the effectiveness of the proposed scheme which shows only 0.082% error for real-world applications. The study discloses that the projected BMS control strategy satisfies the battery-lifetime objective for off-grid PV-battery hybrid systems by avoiding the over-charging and deep-discharging disturbances significantly.

Design and Dynamic Modelling of PV-Battery Hybrid Systems for Custom Electromagnetic Transient Simulation

Battery energy storage systems (BESS) can alleviate the unstable effects of intermittent renewable energy systems, such as solar and wind power systems. In addition, a BESS can level the load of the existing utility grid. The penetration rate of this type of system is expected to increase in the future power grid, i.e., the microgrid. In this paper, a modeling technique is proposed that allows users to customize the photovoltaic (PV) battery hybrid systems. A dynamic power system computer-aided design/electromagnetic transients including DC system (PSCAD/EMTDC) model of a PV battery hybrid system is presented in this paper. Dynamic modeling of PV arrays, BESS, maximum power point tracking (MPPT) algorithms, and bidirectional converters are provided as well. The PV model, battery model, and MPPT control model are designed using a user-defined model (UDM) for custom electromagnetic transient simulation. A control method for stabilizing the output of the PV battery hybrid system is proposed. Finally, a PSCAD/EMTDC simulation is conducted to verify the effectiveness of the operating algorithm.

Active Charge Balancing Strategy Using the State of Charge Estimation Technique for a PV-Battery Hybrid System

Charging a group of series-connected batteries of a PV-battery hybrid system exhibits an imbalance issue. Such imbalance has severe consequences on the battery activation function and the maintenance cost of the entire system. Therefore, this paper proposes an active battery balancing technique for a PV-battery integrated system to improve its performance and lifespan. Battery state of charge (SOC) estimation based on the backpropagation neural network (BPNN) technique is utilized to check the charge condition of the storage system. The developed battery management system (BMS) receives the SOC estimation of the individual batteries and issues control signal to the DC/DC Buck-boost converter to balance the charge status of the connected group of batteries. Simulation and experimental results using MATLAB-ATMega2560 interfacing system reveal the effectiveness of the proposed approach.

A Hybrid PV-Battery System for ON-Grid and OFF-Grid Applications—Controller-In-Loop Simulation Validation

In remote locations such as villages, islands and hilly areas, there is a possibility of frequent power failures, voltage drops or power fluctuations due to grid-side faults. Grid-connected renewable energy systems or micro-grid systems are preferable for such remote locations to meet the local critical load requirements during grid-side failures. In renewable energy systems, solar photovoltaic (PV) power systems are accessible and hybrid PV-battery systems or energy storage systems (ESS) are more capable of providing uninterruptible power to the local critical loads during grid-side faults. This energy storage system also improves the system dynamics during power fluctuations. In present work, a PV-battery hybrid system with DC-side coupling is considered, and a power balancing control (PBC) is proposed to transfer the power to grid/load and the battery. In this system, a solar power conditioning system (PCS) acts as an interface across PV source, battery and the load/central grid. With the proposed PBC technique, the system can operate in following operational modes: (a) PCS can be able to work in grid-connected mode during regular operation; (b) PCS can be able to charge the batteries and (c) PCS can be able to operate in standalone mode during grid side faults and deliver power to the local loads. The proposed controls are explained, and the system response during transient and steady-state conditions is described. With the help of controller-in-loop simulation results, the proposed power balancing controls are validated, for both off-grid and on-grid conditions.

PV-Battery Hybrid System with Less AH Capacity for Standalone DC Loads

Abstract Partial Shading Condition (PSC) is one of the key issues faced by Solar Photovoltaic (PV) systems. PSCs mainly occur due to clouds, shadows of trees/buildings, dust and so on. During the PSC, the shaded PV module acts like a sink and absorbs the power from highest irradiated modules in a string and leads to hotspot. This situation is highly vulnerable and has to be avoided. Bypass diodes are used in series configured PV modules to overcome the hotspot effect caused due to PSC. However, the use of bypass diodes leads to multiple peaks in the Power-Voltage (P-V) graph of a PV array. One among them is Global peak point, where PV array needs to operate under PSC. In such a case, some amount of power generated by the shaded modules gets wasted, which will lead to poor performance and efficiency of the overall system. Moreover, for standalone DC load applications an auxiliary supply also required to provide reliable supply to the load during night times and PSC. Normally, batteries are used in standalone systems as an auxiliary supply. To control the charging and discharging process of battery a bi-directional DC-DC converter is used as a charge/discharge controller. The amount of power that is being charged/discharged by batteries depends upon the load requirement and solar power availability. Under PSC, due to lack of extraction of PV power from shaded modules, batteries have to supply the deficient power to the load. This situation forces to increase the AH capacity of the battery to provide reliable supply. In this research article PV-Battery Hybrid system is proposed to improve the performance of PV under varying irradiance and load conditions with reduced AH capacity of battery for standalone DC loads. The performance assessment of proposed topology has been carried out with the comparison of percentage improvement in power extraction, percentage reduction in the average current consumption of battery and SoC delivered by battery with conventional methodologies of bypass diode and proposed methodology under PSC. The assessment is carried out on MATLAB/SIMULINK and results are presented.

Power management control strategy using physics-based battery models in standalone PV-battery hybrid systems

Abstract The rechargeable lithium-ion batteries (LiBs) are becoming a technology of choice for energy storage applications, due to its high energy and power density. In this paper, a power management control strategy is proposed for a standalone PV-Battery Energy Storage (BES) hybrid system. The proposed control algorithm tracks the Maximum Power Point (MPP) of the solar-cells while avoiding overcharging of LiBs under different solar radiation and load conditions. The controller has two regulation modes; (a) MPP Tracking mode, (b) battery state of charge limit mode. The standalone PV-BES hybrid system is represented as a system of differential algebraic equations and enables effective implementation of control algorithms. A physics-based single particle model accounting for internal states of a battery is implemented in the simulation and control algorithm. A mixed-order finite difference method with optimal node spacing and strong stability-preserving time-stepping Runge–Kutta scheme is used to solve the battery model. A case study is provided to demonstrate the effectiveness of the proposed strategy using real world data. The study reveals that the proposed power control strategy is robust and meets multiple objectives of standalone PV-BES hybrid systems such as no overcharging, 0% excess output power production, and ensuring no energy is transferred to the dump load.

Market value of PV battery systems for autonomous rural energy supply

Abstract Solar photovoltaics (PV) panels in combination with batteries are often proposed as a solution to provide stable power supply in rural areas. PV generation is mostly dominated by the solar diurnal cycle and has, in some countries, already started to have influence on the daily price distribution on the electricity market. In this work, we study the performance and optimisation of rural PV-battery hybrid systems in a future renewable Polish power system. We use data on generation potentials to study PV and battery deployment. Together with a power system optimisation and dispatch model for the Polish power system, we study market values when selling at the national market for different CO2 price scenarios. We show that optimal orientations with respect to tilt/azimuth are subject to change as the PV share grows and that the benefit from batteries grows for higher shares of renewables.

Energy management and performance evaluation of grid connected PV-battery hybrid system with inherent control scheme

To decrease the payback time of the photovoltaic (PV) system and make it financially attractive, we propose a Photovoltaic Customer Grid Supply System (PCGSS) with bi-directional power flow, so the surplus energy fully or partially is delivered of the grid, following its needs, while, for critical operating conditions, the grid supplies the loads directly. For this purpose, a new management algorithm is proposed to optimize the generated power and allows the system to act as a distributed source inside the utility grid. Two scenarios are considered; in the first, the grid absorbs all the power delivered by the distributed system, while in the second, the power is injected to the grid based on the its requirements. Furthermore, to meet the proposed objectives, the PV system is strictly sized to supply only the high priority loads, in addition, the system has to work at the Maximum Power Point (MPP) or at the Limited Power Point (LPP) modes to meet the management algorithm requests. To reach the LPP, a modified Perturbation and Observation (P&O) algorithm is used. Meanwhile, to sustain the functionality of the system and to assure the continues supply of energy, a battery system has been integrated with the PV system.

Control of fuzzy logic based PV-battery hybrid system for stand-alone DC applications

The paper presents a hybrid system comprising of photovoltaic (PV) and battery with fuzzy logic control (FLC) to meet the demands of isolated off grid DC loads. Perturb and Observe (P&O) method is used to achieve the maximum power point tracking (MPPT) by controlling the duty cycle of a dc–dc boost converter. Fuzzy logic controller regulates the power flow of the battery by means of a bidirectional buck-boost converter. The complete energy management system has been validated in MATLAB/SIMUINK with variable solar irradiation profile. The simulation results show that the system with fuzzy logic control prolongs the battery lifespan by reducing the battery peak current up to 0.22% and also significantly decreases the settling time and peak overshoot of the DC load voltage up to 16.23% and 14.62% as compared to the system with conventional PID control.