Photovoltaic Generation System Research Articles

Optimal Energy Management System Applied to a Building Involving Solar Renewable Systems, Electrical Vehicles, and Storage Systems

This paper proposes an energy management system to achieve an optimal power flow that minimizes the total economic cost associated with the monthly energy consumption of a five-apartment residential building. The test has considered that each apartment has one electric vehicle, and the building has an energy storage system in the lower plant and a solar photovoltaic generation system on the rooftop. The aim is to provide residential users with guidelines on the times of the day to charge their electric vehicles and the amount of energy to charge each hour in a lower monthly energy bill. The optimization problem regarding economic cost minimization is solved using a particle swarm optimization algorithm. Thus, three cases defined as the consumption of residential users at different day hours are employed to test the method proposed. Simulation results show that the algorithm reduces the energy bill of a typical residential user up to 20.08% compared to a user whose patterns of electric vehicle chargers are not optimized. Additionally, the comparison of the results obtained for the three types of residential users has allowed the establishment of the ideal residential user that guarantees the lowest energy bill possible.

Analysis and optimizes of hybrid wind and solar photovoltaic generation system for off-grid small village

As an effective means of providing power to remote and off-grid areas of developing countries, where rural electrification problems are most common, hybrid renewable energy systems are considered. HOMER simulated and configured wind turbine, photovoltaic, battery bank, and converter for the electricity demand of the Mander rural community, which has 37 families with household sizes of 7 members, as a remote village in Northern Iraq in this article. The hypothesis project was also evaluated using the parameters Net Present Value and Simple Payback Period. Daily energy consumption of 173,120 kWh and peak electricity consumption of 32,14 kW were measured for the outcome of the selected site. The proposed system produced 68,458 kWh/yr (13.7 percent) by the wind turbine, PV created 432,354 kWh/yr. (86.3 percent), and 265 operating batteries with a total operating cost (TOC) and costs of energy (COE) of $9,195 and 0.365 $/kWh, respectively. This survey emphasized the role of solar photovoltaic and wind turbine as hybrid renewable energy systems HRESs in the sustainable supply of electricity in rural areas of northern Iraq.

The Design and Simulation of a Photovoltaic System Connected to the Grid Using a Boost Converter

The objective of this paper is to present the modelling and simulation of the PV generation system connected to the network under MATLAB/Simulink. Firstly, a mathematical model of the Photovoltaic Module is developed taking meteorological data namely the irradiance and temperature as input variables needed to model this device. The output can be current, voltage or power. The model allows the prediction of the behavior and characteristics of the PV module based on the equivalent circuit of the mathematical model under different temperatures and solar radiation readings. Secondly the PV array is connected to the boost DC-DC converter, the control systems based on Maximum Power Point Tracking (MPPT) with P&O algorithm helps the PV array to generate the maximum power to the grid in case of changing weather conditions, then in the third step, it is integrated into AC power grid by DC/AC inverter to control active and reactive power to achieve unity power factor which is validated by satisfactory results. In this paper, different cases are simulated and the results verified the validity of the models.

Distributed Generation Photovoltaic System Based on Fuzzy Logic

Abstract: Most of the Developing Countries in the world have facing the demand of unavoidable power demand. Due to this high demand, we facing the high-power losses and increase of the transmission lines. In our India we are totally based on the thermal & nuclear power plant and it’s also going to end in few Years. The continues power demand can cause reduction of the voltage levels and affect the system stability, that causes the failure in power system Network and make the transmission line in the stressed condition. In the current situation we going towards the renewable energy, and it’s gaining the attention around the globe. The renewable energy matches the load demand and full-fill it according to the load demand. To step in renewable energy, we have to study it carefully to avoid any unwanted issues occurs in the system and do not make it unstable. The main issue that faces by the consumers is, the solar system gets off during the main supply failure and the total load shifted on the Diesel generator. Due to this Diesel generator get more consumption of diesel and get heavily loaded. To avoid this Heavy load on Diesel Generator we have to use the solar plant during off-grid conditions with the help of smart synchronization between the photovoltaic system and Diesel Generator. Thus, the result of smart synchronization of Photovoltaic system and diesel generation, we get the less load on Diesel generator as compare to the photovoltaic system.

Energy Trading Strategy for Heat and Electricity-Coupled Microgrid Based on Cooperative Game

This paper proposes an energy trading framework for a combined heat and power (CHP) microgrid (MG) integrated with a Photovoltaic (PV) generation system. The parties involved in the CHP-MG energy market are a single MG operator (MGO) and multiple users with electric and thermal demand response (DR). The energy trading process between the MGO and users is formulated as a Nash bargaining game, where the users can bargain with the MGO regarding trading volumes and the prices of electricity and heat. The relationship between the Nash bargaining solution (NBS) and social welfare maximum is studied. A distributed optimization algorithm based on the alternating direction method of multipliers (ADMM) is adopted to achieve NBS. Case studies demonstrate the effectiveness of the proposed trading framework, and show the promotion of economic benefits.

Feasibility of hybrid wind and photovoltaic distributed generation and battery energy storage systems under techno-economic regulation

The Brazilian electric energy compensation system (EECS) states that 100% of the energy generated and inserted into the grid should be returned to prosumers as credits to their energy bill. Ongoing regulatory changes propose that compensation should only be provided for the energy cost (43%). From this perspective, with awareness of the complementarity between wind and solar sources, energy storage systems (ESS) applied to hybrid distributed generation (DG) can become attractive. This study aimed to assess the economic feasibility of hybrid DG power plants with battery banks. Stochastic analyses were carried out by varying nine of the variables (nominal power, solar radiation, wind speed, electricity demand, energy tariffs, discount rate, battery bank investment, and solar and wind installation costs) in three types of hybrid power plants (micro, mini, and small). All scenarios presented a high probability of viability. The main conclusions are as follows. The complementarity of the sources yields benefits to the system: batteries have a high investment cost, which require incentives for their insertion in the DG as a decrease in battery cost or a specific subsidy. The regulatory framework should consider the possibility of payout for the benefits provided by the use of an ESS for DG, i.e., energy storage is directly related to the smart grid concept.

Comparative Analysis Different Topologies of Grid-tied Transformer Less Inverters for Photovoltaic system.

Transformer less inverters are widely used in grid-tied photovoltaic (PV) generation systems, due to the benefits of achieving high efficiency and low cost. Various transformer less inverter topologies have been proposed to meet the safety requirement of leakage currents. In this paper, a family of H6 transformer less inverter topologies with low leakage currents is proposed, and the intrinsic relationship between H5 topology, highly efficient and reliable inverter concept (HERIC) topology, and the proposed H6 topology has been discussed as well. One of the proposed H6 inverter topologies is taken as an example for detail analysis with operation modes and modulation strategy. The power losses and power device costs are compared among the H5, the HERIC, and the proposed H6 topologies. A universal prototype is built for these three topologies mentioned for evaluating their performances in terms of power efficiency and leakage currents characteristics. Experimental results show that the proposed H6 topology and the HERIC achieve similar performance in leakage currents, which is slightly worse than that of the H5 topology, but it features higher efficiency than that of H5 topology.

Development of Open Switch Fault-Tolerant Capability in CCS-MLI Topology

Multilevel inverters (MLIs) are very popular in renewable energy applications and other DC to AC conversion systems due to their reliability, reduced voltage stress, low total harmonic distortion (THD), reduced filter size, low electromagnetic interference, etc. Consequently, the photovoltaic (PV) generation systems, mainly installed in remote areas, require highly reliable systems. The high failure rate of sources and power semiconductor devices results in very low reliability for inverters used in PV generation systems. The aim of this study is to develop a five-level MLI topology with fault-tolerant (FT) characteristics. Therefore, a highly resilient fault-tolerance topology, based on a cross-connected source-based MLIs (CCS-MLI) structure, is proposed in this paper. The developed CCS-MLI topology can tolerate open switch faults in any single switch failure. The proposed system and results developed in a MATLAB/Simulink environment are discussed under normal and faulty states. The simulation results are validated experimentally. Finally, the quantitative and qualitative superiority of the proposed CCS-MLI is demonstrated through the comparative analysis of other recent topologies.

Techno-economic feasibility assessment model for integrating hybrid renewable energy systems into power systems of existing ships: A case study of a patrol boat

The shipping industry has set out to reduce CO2 emissions by 50% by 2050 compared to 2008, as op. cit. in the note by the International Maritime Organisation to the UNFCCC Talanoa Dialogue. In order to achieve this target, ship owners and operators are to consider replacing the conventional diesel generators and gas turbines with renewable energy and other cleaner power producing systems. In this paper, a techno-economic feasibility evaluation model for integrating hybrid renewable energy systems (HRES) into the power architecture of existing ships for greener and sustainable shipping is presented. For HRES to qualify as technically and economically feasible, a decision is made based on a ‘techno-economic measure’ which is estimated by combining space availability, load served and economic performance. The proposed model is applied to a patrol boat sailing along the Eastern Coast of Ghana with three different proposed HRES. The results from the applied case shows that the most technical and economically feasible HRES for the patrol boat that meets the key performance indicators and offers low GHG emission is a hybrid solar PV, wind turbine and diesel generator system. The results further shows that the proposed model is capable of assisting ship owners to integrate affordable and cleaner energy into the power architecture of ships.

A novel global maximum power point tracking algorithm based on Nelder-Mead simplex technique for complex partial shading conditions

In this study, a novel global maximum power point tracking (GMPPT) algorithm for photovoltaic generation system (PGS) operating under complex partial shading conditions is proposed. The presented GMPPT technique is based on Nelder-Mead (NM) simplex technique, which is commonly used to solve complicated optimization problems and has advantages such as simple implementation, derivative-free nature, fast convergence, and high accuracy. In this study, simulation results of 252 shading patterns with non-repeatable irradiance levels and 243 shading patterns under repeatable irradiance levels are provided to validate the effectiveness of the proposed GMPPT methods. According to the simulated and experimental results, the presented NM-based GMPPT approach has the highest success rate and tracking accuracy under all the tested shading patterns compared with other GMPPT methods.

Designing a novel MPPT algorithm based on the extraterrestrial irradiance for photovoltaic energy generation systems and testing under partial shade conditions

Designing a novel MPPT algorithm based on the extraterrestrial irradiance for photovoltaic energy generation systems and testing under partial shade conditions

Optimization of Photovoltaic and Wind Generation Systems for Autonomous Microgrids With PEV-Parking Lots

Lately, the integration of renewable energy sources (e.g., photovoltaic and wind generation systems) has been raised into microgrids interconnected with plug-in electric vehicles (PEVs). Such intermittent generation and charging/discharging PEV profiles are challenging to ensure the secure and optimal operation of microgrids. In this article, an optimization approach is proposed to determine the optimal locations and sizes of photovoltaic and wind generation systems in microgrids with PEV-parking lots. The developed approach addresses 1) the uncertainty of generation profiles of photovoltaic and wind generation systems and loads; 2) the DSTATCOM feature of photovoltaic and wind generation systems; and 3) microgrid constraints. The feasible PEV conditions are also considered, i.e., initial and preset conditions of their state of charge, arriving and departing times, and various controlled/uncontrolled charging schemes. To solve the planning model, we have developed a bilevel metaheuristic-based approach. The upper-level and lower-level optimization tasks are to optimize the decision variables of renewable energy sources and PEVs, respectively. Both energy losses through the lines and energy from the main grid are considered as subobjectives to be minimized. Various simulations and study cases are performed to assess the effectiveness of the proposed approach. The outcomes show the efficacy of the proposed approach to simultaneously plan renewable energy sources and manage PEVs to form an autonomous microgrid.

An algorithm to extract the maximum power from the PV-based generation systems under non-uniform weather

This paper presents a fast and simple algorithm to extract the maximum power under non-uniform weather from the photovoltaic (PV) based generation systems. The proposed algorithm’s three stages are the scanning stage, the tracking stage, the detecting and avoiding the hidden points stage. The hidden points are caused by a transition between the global maximum power point (GMPP) and a local maximum power point (LMPP) when the partial shading conditions (PSCs) are changed. This transition cannot be observed by monitoring only the power difference of the PV generation system. Simulation results with comparisons to other algorithms developed for global maximum power point tracking (GMPPT) under PSCs are provided to clarify and show the effectiveness of the proposed GMPPT algorithm. The average tracking speed of the proposed algorithm is two times faster than the compared MPPT algorithms, with about 2% more power generated with no additional cost. Moreover, the proposed GMPPT algorithm is implemented in real-time using National Instruments (NI) CompactRIO in field-programmable gate array (FPGA) mode to confirm the applicability of the proposed work.

Mathematical modelling, performance evaluation and exergy analysis of a hybrid photovoltaic/thermal-solar thermoelectric system integrated with compound parabolic concentrator and parabolic trough concentrator

This article discusses the electrical and thermal performance of a hybrid concentrator photovoltaic thermal and solar thermoelectric generator (CPV/T-STEG) system using a compound parabolic concentrator (CPC) and a parabolic trough concentrator (PTC). For the first time, the idea of merging imaging and non-imaging concentrators for a CPV and TEG hybrid system is examined, providing an option to retrofit or remodel existing PTC-based CSP systems. The thermal resistance concept is applied to establish a steady-state mathematical model of the proposed hybrid CPV/T-STEG system. A Newton-Raphson iterative approach is employed to solve the mathematical model and compute the temperature in every layer of the hybrid system. After validation, the mathematical model is employed to evaluate the overall performance of the hybrid system. The modelling results revealed that the electrical and thermal output of the developed hybrid system were higher by 2 and 1.6 times, respectively, when compared with the prior parabolic trough-based hybrid CPV/T-STEG system described in the literature. The effects of ambient temperature, wind speed, flow rate, number of TEGs, and solar concentration ratio on the electrical and thermal performance were investigated. The optimal number of TEGs required for maximum electrical performance under different solar concentration ratios is also obtained. Finally, the hybrid system’s exergy efficiency is investigated for various solar concentration ratios. The simulation results revealed that the increase in the Reynolds number from 100 to 2000 improves the net electrical and thermal efficiency by 10.21% and 5.7%, respectively. At a fixed solar concentration ratio (CCPC=4suns and WPTC=2WCPC), the electrical efficiency of TEG drops by 81.4%, but the thermal efficiency increases by 16.81%, provided that the number of TEGs is increased from 1 to 17. The highest exergy of the hybrid system is 8.36% when CCPC=2suns and WPTC=2WCPC. Due to the poor efficiency of commercial TEGs, the overall exergy efficiency of the hybrid system decreases with an increasing solar concentration ratio. In the proposed hybrid system, a fluid channel separates both the PV and TEG modules; hence the electrical conversion efficiencies of both modules are not closely related.

Efficient Integration of PV Sources in Distribution Networks to Reduce Annual Investment and Operating Costs Using the Modified Arithmetic Optimization Algorithm

The optimal integration of photovoltaic generation systems is a challenge for distribution utilities since these devices have a direct impact on company finances due to the large amount of investment required at the beginning of the planning project. In this investigation, the problem regarding the optimal siting and sizing of photovoltaic resources in medium-voltage levels is addressed from an economical point of view, where the optimization model that represents said problem corresponds to a mixed-integer nonlinear programming model. The maximum allowed size for single photovoltaic units in the distribution network is set at 2400 kW. The investment costs, energy purchase costs and maintenance costs for photovoltaic units, are considered in the objective function. Typical constraints such as power balance, generation capacities, voltage regulation, among others, are considered in the mathematical formulation. The solution of the optimization model is addressed by implementing a modified version of the Arithmetic Optimization Algorithm, which includes a new exploration and exploitation characteristic based on the best current solution in iteration t, i.e., xbestt. This improvement is based on a Gaussian distribution operator that generates new candidate solutions with the center at xbestt, which are uniformly distributed. The main contribution of this research is the proposal of a new hybrid optimization algorithm to solve the exact optimization model, which is based on a combination of the Arithmetic Optimization algorithm with the Vortex Search algorithm and showed excellent numerical results in the IEEE 34-bus grid. The analysis of quantitative results allows us to conclude that the strategy proposed in this work has a greater effectiveness with respect to the General Algebraic Modeling System software solvers, as well as with metaheuristic optimizers such as Genetic Algorithms, the Newton–Metaheuristic Algorithm, and the original Arithmetic Optimization Algorithm. MATLAB was used as a simulation tool.

Optimal Control of an Energy-Storage System in a Microgrid for Reducing Wind-Power Fluctuations

In conventional low-voltage grids, energy-storage devices are mainly driven by final consumers to correct peak consumption or to protect against sources of short-term breaks. With the advent of microgrids and the development of energy-storage systems, the use of this equipment has steadily increased. Distributed generations (DGs), including wind-power plants as a renewable energy source, produces vacillator power due to the nature of variable wind. Microgrids have output power fluctuations, which can cause devastating effects such as frequency fluctuations. Storage can be used to fix this problem. In this paper, a grid-connected wind turbine and a photovoltaic system are investigated considering the atmospheric conditions and wind-speed variations, and a control method is proposed. The main purpose of this paper is to optimize the capacity of energy-storage devices to eliminate power fluctuations in the microgrid. Finally, the conclusion shows that, in microgrids with supercapacitors, the optimal capacity of microgrid supercapacitors is determined. This method of control, utilizing the combined energy-storage system of the battery supercapacitor, in addition to reducing the active power volatility of the wind turbine and photovoltaic generation systems, also considers the level of battery protection and reduction in reactive-power fluctuations. In the proposed control system, the DC link in the energy-storage systems is separate from most of the work conducted, which can increase the reliability of the whole system. The simulations of the studied system are performed in a MATLAB software environment.

Optimization of On-Grid Hybrid Renewable Energy System: A Case Study on Azad Jammu and Kashmir

Expansion of modern power systems due to increasing energy demands face the challenges of grid reinforcement cost, size and complexity, transmission losses, and environmental factors. Placement of renewable energy sources (RES) based generation systems addresses these challenges. However, the size and placement location of RES-based system require optimization of installation and operational cost with better return on investment and reduction of greenhouse gas emissions. This paper presents an optimized solution for RES-based generation system to be installed with the existing power system of Azad Jammu and Kashmir (AJK) region that is facing power shortfall and load shedding. The weather and climate data from NASA and National Renewable Energy Laboratory (NREL) have been used and various models of on-grid hybrid renewable energy system (HRES) are compared to highlight their techno-economic benefits. An optimal hybrid photovoltaic, wind, and hydroelectric energy-based generation system is proposed with a significant reduction in cost of energy, net present cost, initial costs, and GHG emissions. Installation of the proposed hybrid RES-based generation system guarantees reduction in system power losses and line flows with an improved voltage profile of the system.

Demand-Side Management Through Load Control and Local Generation in a Medical Education Facility: a Case Study

Electric energy generation from renewable sources is widely accepted thanks to the cost reduction that enables its transformation in an increasingly optimal way. However, these systems depend on climate variability. Accordingly, they cannot provide fixed generation. In order to improve the reliability of these systems, demand-side management strategies have been developed to optimize the operation of renewable generation systems. This article presents a case study of a medical education building with distributed generation. A dynamic tariff scenario is simulated according to the national demand in order to perform demand-side management with three types of loads: refrigeration, air conditioning, and ventilation. The model is fed with data obtained from the telemetering of the PV system generation and demand of the building. The result shows that about 16.2% of the electrical energy consumed can be saved through the implemented energy management system and complies the operation ranges allowed by the system.

Current Sensorless MPPT Control for PV Systems Based on Robust Observer

Photovoltaic (PV) systems are among the most used alternatives for electrical power generation from renewable sources. To ensure that PV systems make the most of the available solar energy, maximum power point tracking (MPPT) schemes must be implemented, which usually require voltage and current sensors to track the PV power. This paper presents the design of a robust observer using the Attractive Ellipsoid Method to achieve a precise estimation of PV current under parametric uncertainty and output perturbations. The application of such an observer enables the PV generation system to operate in a current sensorless mode, which reduces the overall cost of the system and enhances its reliability. The convergence of the observer is guaranteed by solving an optimization problem which generates the optimal gains using Linear Matrix Inequalities (LMI). To prove the effectiveness of the proposed sensorless scheme, simulations are performed in Matlab under test profiles based on the EN50530 standard and parameter uncertainty conditions, obtaining an accurate estimation which is used for MPPT operation.

New Control Approach of Multicell Stacked Cell Inverter for Solar Photovoltaic System

This paper presents the study, modelling, and simulation of the DCSVM (Duty Cycle Space Vector Modulation) control technique applied to a new inverter topology dedicated to isolated or grid-connected photovoltaic systems using the MATLAB/Simulink software. This inverter is based on the structures of a stacked multicell converter (SMC) and an H-bridge. This new topology allows the voltage stresses of the converter to be distributed among several switching cells. It also allows the input voltage to be divided into several fractions so that the number of switching power semiconductors is reduced. The DCSVM is a control technique that generates control signals to the two-level voltage converter as well as the intermediate times. The main advantage of this control technique is the reduction in the number of calculations, especially for the trigonometric functions and the generation of the reference voltage. In this contribution, the general topology of this microinverter is described and the DCSVM control technique is presented. Finally, simulation results, the efficiency of this topology, and the validity of the DCSVM control in a grid-connected PV generation system are discussed. The results obtained are very satisfactory.