A simple, sensorless and fixed reconfiguration scheme for maximum power enhancement in PV systems

This paper discusses about one of the possible solutions to overcome the influence of dust on the surface of solar PV panel. A decrease in power output with the increase in particle deposition has been identified in large scale solar PV power generation where there were many numbers of solar panels connected in the form of arrays and each array requires a robot to carry out efficient cleaning with in stipulated time. Autonomous automatic cleaning operation along with self-control and monitoring of accumulated dust with proper coordination through networking between robots is prerequisite option to attain efficient cleaning system in large scale solar power plants. To accomplish the same, selection of appropriate communication technology for real time wireless networking of solar cleaning robots with low power consumption and data delay to operate over wide area is required. Here an attempt had been made to bring in an automated robot cleaning system using low power wide area network (LPWAN) based on a network of ESP 8266 Node MCU’s associated with a set of sensors under different configurations which showed successful results for implementation in industrial scale large solar PV power plants.

A newly constructed 10MW solar photovoltaic power plant in Qinghai province China is examined for the latest cost benefits evaluation in this research, the RETScreen analysis software tool is used for the energy production estimation, financial feasibility analysis and environmental benefit analysis. Initial results show high solar PV potential in Qinghai province China, 20GWh power electricity generation can reduce more than 18,000 tons of CO2 emissions annually. Although current LCOE of PV power is still double than fossil fuel electricity, but the investment of solar PV is motivated by governmental subsidy policy, the payback of the solar PV project became attractive under the new market environment, the IRR could reach more than 20%, with further material cost decrease, efficiency improvement and continues subsidy policy, the solar PV power will be a trend of renewable energy in China. The GHG emissions reduction is another driving reason to encourage solar PV power development in China.

This paper introduces the simulation and analysis of a three-phase large-scale grid-connected solar Photovoltaic (PV) system in order to assess the effect of integrated PV grid-connected mode on the power quality of the utility grid. The study takes into account the effect of solar system power variation as well as the PV inverter's introduction of penetrating harmonics into the system. The simulation of the system is done in MATLAB software using the SIMULINK environment and is tested by the Pysyst program. Where it is done in real-time with an actual case study on a 1620-kW PV array connected to an 11-kV grid via a three-level Voltage Source Converter (VSC). The technical data was recorded, and the system's power quality was examined. The grid-connected PV system's Performance Ratio (PR) is assessed to determine the PV system's reliability and grid connectivity.

A novel on-time partial shading detection technique for electrical reconfiguration in solar PV system

Renewable energy has made a significant contribution to energy markets in recent years. An abundance of Photovoltaic (PV) array installations attests to solar power’s expanding role in the renewable energy sector. Partial shadowing/mismatch situations are a risk for PV arrays that can cause significant power losses and reduce the lifetime of the solar panels. A partially shaded PV array’s power-voltage characterization exhibits many local maxima, one of which is the global maximum power point. The effects of mismatch conditions on the PV array are lessened by Reconfiguration strategies, that are further categorized into Static and Dynamic Reconfiguration strategies. This article offers a variety of the puzzle patterns that may be found in the literature that are based on the Mathematical based Static reconfiguration strategies. Mathematical based reconfiguration technique use a mathematical rule to reconfigure PV arrays. By implementing these reconfiguration strategies, it was discovered that power production could be enhanced while at the same time, shade was better spread.

Performance study on a grid connected 20 kWp solar photovoltaic installation in an industry in Tiruchirappalli (India)

Performance evaluation of large solar photovoltaic power plants in Spain

Variations in photovoltaic (PV) module current-voltage curves result in a power loss in PV arrays often referred to as mismatch loss (MML). As a means of reducing MML, newly fabricated PV modules are sorted to meet a set tolerance for variation in overall maximum power output with respect to a given module’s rated power. Starting with flash test data sets for two different polycrystalline PV modules and a simulated sorting procedure, Monte Carlo techniques were used to generate a large number of artificial PV arrays. The MMLs for each of these arrays were then calculated to assess the sorting procedure’s ability to reduce MML. Overall MMLs were quite small (0.001–0.01%). Sorting by Imp resulted in the most consistent MML reductions. Sorting by Vmp yielded insignificant results. Sorting by Pmp yielded significant MML reduction in only one of the two PV module data sets. Analysis was conducted to quantify if additional sorting on top of what both manufacturers had already done would make economic sense. Based on high level economic analysis, it appears that additional sorting yields little economic gain; however, this is highly dependent upon manufacturer sorting cost.

To achieve economic competitiveness and move quickly towards grid parity with fossil electricity, parabolic trough CSP power plants, especially recent projects, are usually deployed on large scales (∼100MW). This makes the operation and maintenance (O&M) of those plants more challenging. This paper presents an innovative solution developed by the startup Farasha Systems to help optimize O&M within those large solar power plants. This solution is based on processing visible and thermal images taken from the solar field. The solution mainly consists of an embedded system with thermal and visible cameras as well as a built-in computer. Also, in this work, the methodology used to perform such inspection is introduced together with examples of inspection results during its practical applications in NOORoI Parabolic Trough CSP Plant in Ouarzazate, Morocco.

Review on hybrid geothermal and solar power systems

The growing interest in solar energy has led to large photovoltaic (PV) energy parks in today's world. Though the commonly used total‐cross‐tied (TCT) interconnection scheme reduces mismatch losses (MLs), the occurrence of partial shading on massive PV arrays (PVAs) reduces the output power. It invokes numerous local maximum power points (LMPPs) on the power–voltage (P–V) profiles. To counteract the undesired LMPPs, reconfiguration of PVAs is done either through electrical or physical reconfiguration methods. In this respect, physical relocation scheme is more economical for better distribution of partial shade. A novel greater‐than‐SuDoKu (GTS) topology is presented in this paper for achieving physical rearrangement of PV modules amalgamated with TCT interconnection scheme. For analysis, five shading cases are considered and obtained results are compared with conventional TCT and 10 newly established methods. In general, the proposed GTS strategy has shown its eminence in receiving a smoother P–V characteristic, enhanced efficiency, better fill factor, and reduced MLs, which ranges up to 1343 W. Moving forward, herein, the efficacy of the proposed reconfiguration scheme is validated, under the influence of partial shading conditions, through an experimental lab prototype for a 3 × 3 PVA.

The output power from the photovoltaic (PV) array decreases and the array exhibit multiple peaks when it is subjected to partial shading (PS). The power loss in the PV array varies with the array configuration, physical location and the shading pattern. This paper compares the relative performance of a PV array consisting of a short string of three PV modules for two different configurations. The mismatch loss, shading loss, fill factor and the power loss due to the failure in tracking of the global maximum power point, of a series string with bypass diodes and short parallel string are analysed using MATLAB/Simulink model. The performance of the system is investigated for three different conditions of solar insolation for the same shading pattern. Results indicate that there is considerable power loss due to shading in a series string during PS than in a parallel string with same number of modules.

Predictive control technique for solar photovoltaic power forecasting

Parabolic trough solar technology is the most proven and lowest cost large-scale solar power technology available today, primarily because of the nine large commercial-scale solar power plants that are operating in the California Mojave Desert. These plants, developed by Luz International Limited and referred to as Solar Electric Generating Systems (SEGS), range in size from 14–80 MW and represent 354 MW of installed electric generating capacity. More than 2,000,000m2 of parabolic trough collector technology has been operating daily for up to 18 years, and as the year 2001 ended, these plants had accumulated 127 years of operational experience. The Luz collector technology has demonstrated its ability to operate in a commercial power plant environment like no other solar technology in the world. Although no new plants have been built since 1990, significant advancements in collector and plant design have been made possible by the efforts of the SEGS plants operators, the parabolic trough industry, and solar research laboratories around the world. This paper reviews the current state of the art of parabolic trough solar power technology and describes the R&D efforts that are in progress to enhance this technology. The paper also shows how the economics of future parabolic trough solar power plants are expected to improve.

Due to the increasingly evident climate change and the recent energy crisis triggered by regional conflicts, the exploitation of renewable energy has become one of the pressing tasks today. In light of this background, today the photovoltaic (PV) market is booming globally. This makes the management and maintenance of solar PV panels a new area of business, as neglecting it may not only lead to significant financial losses but also the failure to combat climate change and the energy crisis. In fact, in the long service life of solar panels, they do face many risks that may degrade their power generation performance, damage their structures, or even cause the complete loss of their power generation capacity. It is hoped that these problems can be found and resolved as soon as possible. However, in reality, this is a challenging task as a large solar power plant may contain hundreds of thousands of solar PV panels. To address this issue, a smart solar panel condition monitoring technique is studied in this paper with the aid of the U-Net neural network and Support vector machine (SVM). The research result has shown that using the developed technique, the thermal infrared images that are remotely collected by drones from solar power plants can be rapidly and automatically processed, analysed and classified with reasonable accuracy. This is of great significance to further improve the asset management skills in solar power plants.