Solar Grid Research Articles

Design Approach of Grid Coupled Solar Inverter

In novel times, more demands are gained by grid connected solar inverters along with the upgrading of the solar energy generation. In grid connected solar power generation, if there is increase in placing more number of solar inverters it may result in effecting the power quality issues. Solar Grid Tied Inverter system is a electrical power generating system that is coupled to the functioning power grid. This power generating system unit consists of elements like Photovoltaic array, DC to DC converter, DC to AC converter, single phase/three phase converter, and AC Source. The inverter converts DC power generated by the array of photovoltaic cells into AC power and this generated AC power is fed to the connected AC loads. If the amount power generation is exceeding the power demanded, excess AC power is supplied to the grid. With this novel approach we can minimize the use of the AC power from the power grid and also even make a generation to the power grid and this is measured with help of net metering. In this paper designing of 281.6Kw grid tied solar power generation and technical specifications required for them are proposed.

Design and analysis of distributed photo-voltaic power station

After the location of the power station is determined, the construction scale of the solar grid connected photo-voltaic power station is mainly with the terrain conditions and the conditions of land use.The selection of solar cell components and installation methods, access to the power grid and other factors are related.In this paper, according to the existing construction conditions in the sewage plant, the area suitable for the layout of the solar cell array is selected.Accordmg to the structural characteristics of existing structures and the prediction of the power load in the sewage plant, the installed capacity of the plan is 4.9218MWp. A 10kV installed switch-gear station is built, and the 1 10kV outlet is connected to the total distribution room power station. The project is completed at once.Solar energy is converted to DC power through photo-voltaic array composed of PV modules. After three phase inverter (DC-AC) is converted to three-phase alternating current, it is converted to AC power that meets the requirements of public power grid and directly connected to the public power grid through the step-up transformer.The construction and operation of photo-voltaic power stations will not cause pollution to the environment, and can also provide some clean energy, which can reduce the use of fossil fuels such as coal.

Design and Flood Control Assessment of 5MWp Fishing and Photovoltaic Power Project in Xinghua City

In order to reduce coal consumption in Jiangsu Province and develop new energy sources, considering on the distribution of geology, solar energy resources, traffic and grid connection in Xinghua City, the aim is to determine the configuration of photovoltaic modules and photovoltaic array tracking mode, design photovoltaic array and layout scheme. But the project is a wading project, it is built in Dong Tan Lake polder I115, it needs scientific and reasonable evaluation to the effect of Dong Tan Lake’s flood storage and discharge. The results can provide guidance for similar engineering’s design.

Literature Review and Implementation of Multilevel Inverter by Using Capacitor for Solar PV Grid

Literature Review and Implementation of Multilevel Inverter by Using Capacitor for Solar PV Grid

The value of demand response in Florida

Many electrical loads may be operated flexibly to provide grid services, including peaking capacity, reserves, and load shifting. The authors model 14 demand end uses in Florida and analyze their operational impacts and overall value for a wide range of solar penetrations and grid flexibility options. They find demand response is able to reduce production costs, reduce the number of low-load hours for traditional generators, reduce starting of gas generators, and reduce curtailment.

Evaluation of PV hosting capacities of distribution grids with utilisation of solar roof potential analyses

Increasing distributed photovoltaic (PV) systems can lead to voltage violations and overloading of grid assets in distribution grids. This raises the necessity to consider the future growth of installed PV capacity for the planning process of distribution system operators (DSOs). This study proposes the combination of a solar roof potential analysis and grid integration studies at the medium-voltage (MV) level. Three different methods are developed to assume the distribution of PV along the feeders based on the solar roof potential, and subsequently to estimate the PV hosting capacity of these feeders. The results show that the approach with an even distribution of PV systems along the feeders leads to higher hosting capacity of PV for the analysed grids. In addition, for most analysed feeders in this study, an overloading of MV/LV (low voltage) transformers is expected to be the limitation of hosting capacity for potential PV systems.

Simulation Study on the Effect of Reduced Inputs of Artificial Neural Networks on the Predictive Performance of the Solar Energy System

In recent years, there has been a strong growth in solar power generation industries. The need for highly efficient and optimised solar thermal energy systems, stand-alone or grid connected photovoltaic systems, has substantially increased. This requires the development of efficient and reliable performance prediction capabilities of solar heat and power production over the day. This contribution investigates the effect of the number of input variables on both the accuracy and the reliability of the artificial neural network (ANN) method for predicting the performance parameters of a solar energy system. This paper describes the ANN models and the optimisation process in detail for predicting performance. Comparison with experimental data from a solar energy system tested in Ottawa, Canada during two years under different weather conditions demonstrates the good prediction accuracy attainable with each of the models using reduced input variables. However, it is likely true that the degree of model accuracy would gradually decrease with reduced inputs. Overall, the results of this study demonstrate that the ANN technique is an effective approach for predicting the performance of highly non-linear energy systems. The suitability of the modelling approach using ANNs as a practical engineering tool in renewable energy system performance analysis and prediction is clearly demonstrated.

Design and experimental validation of a generalised electrical equivalent model of Vanadium Redox Flow Battery for interfacing with renewable energy sources

In this paper a MATLAB/Simulink based generalised electrical equivalent model of Vanadium Redox Flow Battery (VRFB) has been proposed with an objective of interfacing VRFB with renewable energy sources. The impact of practical parameters like flow rate, self discharge, pump power loss and charge-discharge current profile has been considered for analysing VRFB performance. The model involves online estimation of VRFB stack terminal voltage and state of charge (SOC) under different constant current charge-discharge profiles. The accurate estimation of electrical characteristics of VRFB leads to a benchmark for selection of the design parameters of an efficient charge controller taking into account the variability of renewable energy sources. An optimal range of variable electrolyte flow rates for dynamic SOC has been estimated to design suitable flow rate controller. This ensures minimum VRFB system power consumption during charging and maximum power output during discharging which leads to maximum overall VRFB system efficiency. A generic MATLAB library has also been created for optimal design of any generalised VRFB system. A practical 20 Cell 1kW 6h VRFB system has been used for experimental validation of simulation results of the proposed model which shows a very good agreement having maximum error within 0.5% and 0.21% for VRFB cell terminal voltage estimation during charging and discharging respectively. The proposed model of the VRFB system is then applied for interfacing and investigating the performance of a 1kW 6h VRFB with a microgrid system comprising of 10kW Solar PV, local loads and distribution grid.

Droop Control of Solar PV, Grid and Critical Load using Suppressing DC Current Injection Technique without Battery Storage

This paper presents design of a sustainable solar Photo voltaic system for an Indian cities based residential/community house, integrated with grid, supporting it as supplementary sources, to meet energy demand of domestic loads. The role of renewable energy sources in Distributed Generation (DG) is increasingly being recognized as a supplement and an alternative to large conventional central power supply. Though centralized economic system that solely depends on cities is hampered due to energy deficiency, the use of solar energy in cities is never been tried widely due to technical inconvenience and high installation cost. To mitigate these problems, this paper proposes an optimized design of grid-tied PV system without storage which is suitable for Indian origin as it requires less installallation cost and supplies residential loads when the grid power is unavailable. The energy requirement is mainly fulfilled from PV energy module for critical load of a city located residential house and supplemented by grid/DG for base and peak load. The system has been developed for maximum daily household demand of 50kWp and can be scaled to any higher value as per requirement of individual/community building ranging from 50kWp to 60kWp as per the requirement. A simplified control system model has been developed to optimize and control flow of power from these sources. The simulation work, using MATLAB Simulink software for proposed energy management, has resulted in an optimal yield leading efficient power flow control of proposed system.

Cost-Constrained Viterbi Algorithm For Resource Allocation in Solar Base Stations

Solar energy is currently a popular renewable resource, yet limited daily. In green cellular networks, multiple constraints optimization (MCO) problems arise naturally. For example, a typical objective is to control the power transmission of the hybrid base stations (BSs) (connected to both solar panels and electrical grid) in order to maximize user’s average throughput, under the constraints of consumed grid energy and user’s blocking rate. However, such problems have been generally proved to be NP-hard. In this paper, we formulate this generic MCO problem as a quantized Markovian cost-reward model, with no assumption on input data. We then propose a novel algorithm, namely cost-constrained Viterbi algorithm, which recursively returns the optimal policy with linear computational complexity for this model. As an application, we provide engineering rules for the design of hybrid BSs through extensive simulations. In comparison with brute force method for a simple scenario, we find that our algorithm does achieve the constrained optimal policy.

Techno-economic analysis of hybrid solar-diesel-grid connected power generation system

Due to ever increasing energy demand and depletion of conventional energy resources, renewable energy is being promoted throughout the globe. The Government of India initiated a large number of schemes for encouragement of renewable energy for power generation and to make it competitive with fossil-based energy options like coal, oil etc. Keeping these initiatives in mind, this paper aims to optimize several hybrid energy system models consisting of solar PV, diesel generators and grid. Optimization is based on the techno-economic analysis of renewable as well as grid connected hybrid systems in HOMER software. The comparison is based on per unit cost of electrical energy production, operating cost of conventional fossil fuel based energy sources and reduction in green house gases.

Voltage Profile Improvement of Solar PV Grid – Connected Inverter with Micro Grid Operation using PI Controller

Microgrids (MGs) are initiating the large number of opportunities for the future of distribution units. Distributed generation resources (DERs) such as solar, wind, combined heat and power, energy storage, etc are tie up with the microgrid or distribution grid (DG) which can be used for improving the power quality. Distributed generation and microgrid are the most challenges to the power system network. This includes the stability, reliability, increasing power demand and power quality issues in power system. The objective of this paper is to improve the voltage profile of grid – connected PV systems. In the distribution system, PV source is the challenging one which is directly disturbs the power quality issues. Here MPPT algorithm is used to achieve the maximum amount of power in grid – connected PV systems. This paper presents the grid connected inverter with a PI controller is proposed. At the connection of point of common coupling real and reactive power by abc to dqo transformation could be compensated under the unbalanced load condition. The proposed control method is used to improve the voltage profile in the PV systems, dc voltage regulation across the grid side inverter control and to reduce the distortions under the sudden load changes. The effectiveness of the proposed system is replicated through the MATLAB/SIMULINK using Simpower system library.

Socio-Technical Drivers for Community Renewable Energy Systems – Analysis of Case Studies from India

Renewable energy sector of India has the potential to be a credible alternative for households and communities. The sector accounts for approximately 13 per cent of the national energy capacity, including technologies such as solar grid/ off – grid generation, wind power, small hydro power, biomass/ biogas, and waste to energy. Statistics related to implementation illustrate the scope of tapping the renewable energy sector comprehensively, esp. for decentralized, household and community level applications. This paper analyses on – ground case studies and projects from various renewable energy categories, specifically the socio – technical and community aspects that play a significant role in successful Renewable Energy Technologies (henceforth RET) implementation. The distilled positive and negative drivers include technical, economic considerations, policy and regulatory, environmental aspects, market/ business models, and social/ community linked aspects. Case studies describe the need for a system based and stakeholder engagement approach where all possible stakeholders and their issues are envisaged and taken into account. Use of an evaluating framework is suggested to ensure successful community models of RETs and mass adoption of renewable technologies.

Location or insolation: the importance of siting in emissions mitigation from solar photovoltaics

Achieving environmental benefits is often a primary motivation for integrating renewable energy into the grid. The magnitude of generation from a solar power project is influenced by the solar resource quality, but locations with high insolation do not necessarily yield the greatest emission reduction benefits. This study simulates the power system response to 10 identical solar projects in different regions across the United States, selected to represent a wide range of solar resource quality and power grid configurations. The power grid mix is often a key determinant in offsetting CO2 , SO2 , and NOx emissions, illustrating how lower‐quality solar resources can be more effective than sunnier sites at emissions mitigation when one considers characteristics of the power grid. The analysis shows a strong relationship between emissions mitigation and the share of offset generation that is coal‐fired. The strongest correlation is shown for CO2 ; the presence or absence of emissions control equipment and the sulfur content of the coal complicates the relationship of SO2 and NOx . The emissions intensity of offset generation is insensitive to whether the solar project is fixed tilt or single‐axis tracking. When seeking to mitigate power sector emissions, the impacts of solar design considerations on the temporal profile of generation are less important than the overall amount of generation and the location of interconnection. Public policies that target only the magnitude of generation from renewables (e.g., many Renewable Portfolio Standards) or the installed cost (e.g., the Investment Tax Credit) will likely lead to suboptimal emissions mitigation. WIREs Energy Environ 2017, 6:e249. doi: 10.1002/wene.249This article is categorized under: Photovoltaics > Climate and Environment Energy and Development > Systems and Infrastructure

A Multiagent Minority-Game-Based Demand-Response Management of Smart Buildings Toward Peak Load Reduction

This paper presents a cyber-physical management of smart buildings based on smart-gateway network with distributed and real-time energy data collection and analytics. We consider a building with multiple rooms supplied with one main electricity grid and one additional solar energy grid. Based on smart-gateway network, energy signatures of rooms are first extracted with consideration of uncertainty and further classified as different types of agents. Then, a multiagent minority-game (MG)-based demand-response management is introduced to reduce peak demand on the main electricity grid and also to fairly allocate solar energy on the additional grid. Experiment results show that compared to the traditional static and centralized energy-management system (EMS), and the recent multiagent EMS using price-demand competition, the proposed uncertainty-aware MG-EMS can achieve up to $50\times $ and $145\times $ utilization rate improvements, respectively, regarding to the fairness of solar energy resource allocation. More importantly, the peak load from the main electricity grid is reduced by 38.50% in summer and 15.83% in winter based on benchmarked energy data of building. Lastly, an average 23% uncertainty can be reduced with an according 37% balanced energy allocation improved comparing to the MG-EMS without consideration of uncertainty.

Providing energy management of a fuel cell–battery–wind turbine–solar panel hybrid off grid smart home system

It is important that smart home can use produced energy more effective and obtain optimum economy as well as provide ease of use. With use of fuel cell (FC) as main energy source in an off grid smart home that supplied by alternative energy sources (AES), more quality, economic and eco-friendly energy can be achieved. This off grid smart home system can use auxiliary energy sources with FC to supply instantaneous power and sustainable energy. Therefore, it is needed to develop energy management algorithms (EMA) for AES in smart home systems. These algorithms can be able to respond user's preferences and needs and also enable to benefit optimally from AES. In line with these requirements in this study, an EMA for a smart home, which is equipped with FC, battery, solar panel and wind turbine is presented. A fuzzy logic controller is designed for EMA. The proposed system is tested in MATLAB/Simulink and obtained results of the simulation are analyzed and discussed.

Optimization of photovoltaic power system: a comparative study

This paper presents a comparative study of P&O, fuzzy P&O and BPSO fuzzy P&O control methods by using MATLAB software for optimizing the power output of the solar PV grid array. The voltage, power output and the duty cycle of the solar PV array are well presented and analyzed with an algorithm. The model consists of 66 PV Cells connected parallel and 5 PV cells connected in series to make solar PV array. The BPSO Fuzzy method generates 43.4820 MW output power more than P&O method and 150 KW more than P&O fuzzy method. This also shows that the time response of the photovoltaic system reduces to perturbations and insures the continuity of the operation at the time in response to the continued maximum power point. It also eliminates the fluctuations around MPPT. Simulation results also revealed that BPSO fuzzy P&O controller is more effective as compare with P&O and fuzzy P&O models.

Power Quality Improvement of Single Phase Grid Connected Photovoltaic System

Abstract: This paper presents a single-phase grid-connected photovoltaic power system with the capability of maximum power point tracking (MPPT) of photovoltaic (PV) array and reactive power compensation. The non linear characteristics of the proposed modified p-q theory have been improved with the help of maximum power point tracking (MPPT) controller. MPPT controller helps to feed the inverter with maximum power from the solar grid, for switching pattern generation hysteresis controller is used. The simulation results developed in MATLAB/Simulink software, verify the performance and advantages of the proposed system used to integrate the single phase grid to photovoltaic for enhancing the power quality. Also the proposed scheme has been verified in laboratory setup for its real time implementation.

Power quality improvement for grid interconnected solar PV system using neural network control algorithm

This paper deals with neural network control algorithm-based grid connected to solar photo voltaic (PV) system consisting of DC-DC converter, solar PV with maximum power point tracking (MPPT) controller, three-leg voltage source converter (VSC), ripple filter at PCC, interfacing inductor and three phase grid connected to three phase linear/nonlinear loads. The reference solar-grid current for three-leg VSC are estimated using neural network control algorithm. The neural network based on least mean square (LMS) control algorithm is also known as adaptive linear element to estimate reference fundamental grid currents. A three phase non-isolated zigzag transformer is connected to solar grid PCC for neutral current compensation. The proposed solar PV grid connected system maintains UPF at the grid, reactive power compensation for ZVR operation along with load balancing, neutral current compensation and harmonic compensation. In the proposed solar PV system, MPPT is obtained using DC-DC boost converter and DC bus voltage is controlled by using DC bus proportional integral (PI). The neural network control algorithm based solar PV system is modelled in MATLAB R2013a along with SIMULINK.

Research on evaluation method for operation economy and technology of regional smart energy grid

Establishing regional grid will not only help sufficient and efficient utilisation of multiple kinds of energies in local regions but also be helpful to increase effectively the utilisation efficiency of the power grid and guarantee secure and reliable power supply. This study is to evaluate coordinated operational technology and economy. First, analysing the operation characteristics of the regional energy grid including those of wind–solar power generation, local grids and load, large-scale energy storage, tail-gas power generation and the correlation between wind/photovoltaic (PV) power generation and power load. It researches the coordinated operation technologies and integrated control scheme of wind power, PV power, energy storage, gas power, grids and load. Also, it analyses the operation economy of regional energy grid, and studies economy of integrated operation including wind power, PV power, energy storage, gas power, grids and load, in the region, by calculating the sensitivity of a series of evaluation indexes. Finally, taking the energy grid of a region in northwest as an example, it evaluates technical economy and comes up with a feasible plan for regional energy grid projects.