In this study the potential for further reduction in greenhouse gas emissions (GHG) of c-Si, multi-crystalline silicon (mc-Si) and CdTe photovoltaic (PV) systems are assessed to inform climate change mitigation in the UK. The amount of CO₂ equivalent released in grams for each kWh of electricity over the lifetime of the PV system (gCO₂-e/kWh) has been assessed using a model to predict the change in GHG as a result of engineering improvements in the PV module and system operation. The scenarios modelled here are for two different locations in the UK (Midlands and South West England) to give a typical range. Similarly a range of carbon intensity in manufacture is considered by taking manufacture in China and the UK. This study considers the impact of; system and inverter lifetimes, continuing trends of increases in module conversion efficiencies and reduction in carbon intensity during manufacture. For most of the scenarios considered the extension of the PV system lifetime to 40 years makes the largest impact while extending inverter lifetime for deployment of thin film PV modules becomes more significant and cannot be ignored. All of the four interventions considered in this study can significantly contribute to a reduction in the carbon footprint of PV by the near term target of 2020. For all three module systems considered the model shows the potential for the carbon footprint to be reduced to one third of the 2012 values giving a range of 11–38 gCO₂-e/kWh, which is within the range of current wind generation in the UK.

Photovoltaic (PV) systems are frequently covered by performance guarantees, which are often based on attaining a certain performance ratio (PR). Climatic and electrical data are collected on site to verify that these guarantees are met or that the systems are working well. However, in-field data acquisition commonly suffers from data loss, sometimes for prolonged periods of time, making this assessment impossible or at the very best introducing significant uncertainties. This study presents a method to mitigate this issue based on back-filling missing data. Typical cases of data loss are considered and a method to infer this is presented and validated. Synthetic performance data is generated based on interpolated environmental data and a trained empirical electrical model. A case study is subsequently used to validate the method. Accuracy of the approach is examined by creating artificial data loss in two closely monitored PV modules. A missing month of energy readings has been replenished, reproducing PR with an average daily and monthly mean bias error of about −1 and −0.02%, respectively, for a crystalline silicon module. The PR is a key property which is required for the warranty verification, and the proposed method yields reliable results in order to achieve this.

In this study, we present the conjugate refractive reflective homogeniser (CRRH) to be used in a 500× Cassegrain photovoltaic concentrator. The CRRH is a dielectric crossed v-trough lined with a reflective film whilst maintaining an air gap between them. This air gap between the two surfaces helps in trapping the scattered light from the refractive geometry and ensures both total internal reflection and standard reflection of the escaped rays. A 10–42% drop in optical efficiency has been shown to occur due to varying the surface roughness of the homogeniser in these ray trace simulations for the Cassegrain setup. The CRRH increased the overall optical efficiency by a maximum of 7.75% in comparison with that of a standard refractive homogeniser simulated within the same concentrator system. The acceptance angle and flux distribution of these homogenisers was also investigated. The simple shape of the CRRH ensures easy manufacturing and produces a relatively uniform irradiance distribution on the receiver. The theoretical benefit of the CRRH is also validated via practical measurements. Further research is required but a 6.7% power increase was measured under a 1000 W/m² solar simulator at normal incidence for the experimental test.

To assess the systemic value and impacts of multiple photovoltaic (PV) systems in urban areas, detailed analysis of on-site electricity consumption and of solar PV yield at relatively high temporal resolution is required, together with an understanding of the impacts of stochastic variations in consumption and PV generation. In this study, measured and simulated time-series data for consumption and PV generation at 5 and 1 min resolution for a large number of domestic PV systems are analysed, and a statistical evaluation of self-consumption (SC) carried out. The results show a significant variability of annual PV SC across the sample population, with typical median annual SC of 31% and inter-quartile range of 22–44%. About 10% of the dwellings exceed an SC of 60% with 10% achieving 14% or less. The results have been used to construct a Bayesian network model capable of probabilistically analysing SC given consumption and PV generation. This model provides a basis for rapid detailed analysis of the techno-economic characteristics and socio-economic impacts of PV in a range of built environment contexts, from single building to district scales.

The annual yield for solar photovoltaic (PV) electricity generation in the UK is calculated for the installed capacity at the end of 2014 and found to be close to 960 kWh/kWp. This value is derived by averaging expected PV yield in different regions of the UK, weighted according to the regionally installed generating capacity from UK government statistics and has an estimated uncertainty of ±5%. The mean generating yield can vary with time as newly deployed PV may change the regional distribution of installed power and the variation over the period 2010–2014 is charted. The installed generating capacity at September 2015 was 8.19 GWp and, based on the above yield, should generate around 7860 GWh of electricity in a typical year or 2.6% of UK consumption (2014). Based on current trends, Solar PV electricity should exceed 3% of UK consumption in 2016.

Deployment of grid-connected photovoltaics (PV) in the UK has increased rapidly. By 2014 there were over 650,000 installations (over 5 GWp), spread over different market segments (on site of existing domestic and non-domestic electricity demand customers, or connected directly to the network, e.g. solar farms). This rapid deployment and diverse market segmentation raises questions about impacts upon the electricity network. Here the authors present a novel geographical information system framework which maps current PV deployment and electricity demand to sensitive spatial resolution and by market segment. This is used to understand how current PV deployment affects power flows between the high-voltage (HV) and low-voltage (LV) network. The analysis reveals that overall, current LV PV generation is significantly below summer daytime LV demand – with over half of the areas investigated showing electricity demand five times greater than peak PV generation. Interestingly a small number of areas exhibit peak PV generation greater than demand, where reverse power flow from LV to HV may occur. The framework is hence capable of identifying the areas where network impacts are likely to occur and will also be useful to consider how integration strategies, such as energy storage and demand response could facilitate further PV deployment.

Large-scale adoption of solar photovoltaics (PV) in the built environment requires automation of roof suitability surveying over large geographical areas. Furthermore, as local PV installation density increases, electricity network operators require clearer information on the overall impact the large number of different rooftop PV systems will have on the stability of the local network. Knowledge of roof features (tilt angle, azimuth angle and area) and localised in-plane irradiance data is essential to meet both of these requirements. Such information is currently not available (except by individual roof surveying by PV consultants) and has to be generated. This study demonstrates the automated extraction of building roof plane characteristics from existing wide-area, aircraft-based light detection and ranging data. These characteristics are then aggregated statistically and scaled-up to produce a UK-wide map of average roof tilt variation. Validation of roof tilt with site measurements taken by four different methods demonstrates a mean absolute error of 3°. For major roof plane azimuth angles, banded into compass octants, accurate detection was achieved in 100% of cases, validated by inspection of aerial photography. This is sufficient for calculating in-plane irradiance for a more detailed automated assessment.

This study deals with the use of a Landsman converter for maximum power point tracking in solar photovoltaic (SPV) array-based water pump driven by a permanent magnet brushless DC (BLDC) motor. The primary function of a DC–DC Landsman converter is to optimise the power output of SPV array and it also provides the safe and soft starting of the BLDC motor with an appropriate control. Amongst various DC–DC converters, Landsman converter meets the desired performance of proposed water pumping system. The starting, dynamic and steady-state behaviours of the SPV array fed BLDC motor driven water pump are presented to demonstrate the novelty of the proposed system. The SPV fed water pumping system under study is simulated using MATLAB/SIMULINK environment and validated on a developed prototype of the system in order to manifest its performance under practical operating conditions.

Solar photovoltaic (PV) system installations are rapidly increasing in distribution networks. These PV systems include power electronic devices which have an influence on the power quality of the grid in the form of harmonic distortion. The aim of this study is the harmonic impact of PV systems on distribution networks. A comprehensive harmonic behaviour analysis has been performed on the IEEE-13 bus distribution network with high PV systems penetration. A certain level of harmonics is also injected into the IEEE network through non-linear loads to resemble a realistic scenario. The investigation has been carried out through simulations of three case studies, namely PV system integrations at a single node in particular with and without the presence of background distortions in the supply and finally PV penetration at multiple nodes with supply distortions. Furthermore, an evaluation study has been conducted at the University of Queensland PV site to validate simulation results. This study has highlighted the PV systems harmonic contributions on real distribution networks and the impact of harmonics propagation on transformer K-factor. Results show that the total harmonic distortions of current and voltage are exceeding the limits when the number of PV systems increases, leading to transformer overloading and heating.

This paper presents an implementation of sliding mode controller (SMC) along with a proportional and integral (PI) controller for a DSTATCOM (Distribution STATic COMpensator) for improving current induced power quality issues and voltage regulation of three-phase self-excited induction generator (SEIG). The use of SMC for regulating the DC link voltage of DSTATCOM offers various advantages such as reduction in number of sensors for estimating reference currents and the stable DC link voltage during transient conditions. The use of PI controller for terminal voltage control gives the error free voltage regulation in steady state conditions. The voltage regulation feature of DSTATCOM offers the advantages of single point voltage operation at the generator terminals with the reactive power compensation which avoids the saturation in the generator. Other offered advantages are balanced generator currents under any loading condition, harmonic currents mitigation, stable DC link voltage and the reduced number of sensors. The SMC algorithm is successfully implemented on a DSTATCOM employed with a three-phase SEIG feeding single phase or three phase loads. The performance of the proposed control algorithm is found satisfactory for voltage regulation and mitigation of power quality problems like reactive power compensation, harmonics elimination, and load balancing under nonlinear/linear loads.

This study explores the integration issues of next-generation high-penetration photovoltaic (PV) systems, where the grid is becoming more decentralised and vulnerable. In that case, the PV systems are expected to be more controllable with higher efficiency and reliability. Provision of ancillary and intelligent services, such as fault ride-through and reactive power compensation, is the key to attain higher utilisation of solar PV energy. Such functionalities for the future PV inverters can contribute to reduced cost of energy, and thus enable more cost-effective PV installations. To implement the advanced features, a flexible power controller is developed in this study, which can be configured in the PV inverter and flexibly change from one to another mode during operation. Based on the single-phase PQ theory, the control strategy offers the possibilities to generate appropriate references for the inner current control loop. The references depend on system conditions and also specific demands from both system operators and prosumers. Besides, this power control strategy can be implemented in commercial PV inverters as a standardised function, and also the operation modes can be achieved online in predesigned PV inverters. Case studies have verified the effectiveness and flexibilities of the proposal to realise the advanced features.

This study presents a novel sensorless model predictive control (MPC) strategy of a wind-driven doubly fed induction generator (DFIG) connected to a dc microgrid. In this configuration, the stator is directly connected to the dc microgrid through a diode rectifier, and the rotor is fed by only a voltage source converter (VSC). This connection structure brings considerable benefits such as simple control scheme and reduced power converter cost. In order to obtain sensorless operation, a simple and effective sensorless position detection technique has been proposed. It is based on the detection of the stator frequency, and it is designed to operate without any machine parameters. Thus, the proposed sensorless method offers as a model-free solution. In addition, the MPC strategy has been used as a current controller to overcome the weaknesses of the inner control loop and to consider the discrete-time operation of the VSC. The proposed control system is robust against machine parameters, speed, and load variations. To verify the dynamic and steady-state performances of the proposed sensorless MPC scheme under various speed and load conditions, experimental studies are performed with 6.4 kW DFIG. Experimental results aim to show that the proposed sensorless MPC strategy works properly at steady state and in transient.

This study deals with photovoltaic power plant modelling and its integration within the distribution network. It presents a simulation model of a whole photovoltaic power plant including the solar cells, boost converter with maximal power point tracking, voltage-oriented control and inductor-capacitor-inductor (LCL) filter. In such a sense, the applied inverter has many advantages such as a controllable power factor and sinusoidal input current, while the switching frequency of the power switch is relatively high. Therefore, it could cause high-frequency harmonics around the switching frequency. The traditional way of solving these problems is the usage of LCL filters, where the basic requirement is to achieve sufficient filtering with inductor and capacitor values as small as possible. In addition, emphasis is given to a comparison between two optimisation methods – particle swarm optimisation and differential evolution that are used for the parameters of proportional–integral (PI) controllers determination. These PI controllers represent the main part of the voltage-oriented control.

This study deals with the development of a control system for voltage and frequency regulation of a micro hydro power generation system, fed by self-excited induction generator (IG). The generation system considers a four-wire three-phase grid, composed by three phases plus neutral conductor, fed by three-phase three-wires IG. The neutral conductor is created from the neutral point of star connection of excitation capacitors bank. The four-wire configuration allows the connection of three-phase loads in star or delta configuration, as well as single-phase loads. The voltage regulation is performed through a four-legs distribution static synchronous compensator (DSTATCOM) shunt connected to the AC bus. It is considered the employment of adaptive control techniques and the compensation of load current unbalances, which offers suitable voltage regulation in conditions of system's parameters variations such as load connection and disconnection, and changes in IG's unmodelled parameters, and voltage unbalance compensation, respectively. Frequency regulation is obtained by electronic load control connected to the DC bus of DSTATCOM. Experimental results were obtained to demonstrate the good performance of the voltage and frequency regulation control system during loads transient, including three-phase and single-phase loads.

The power generation of regular water waves from a horizontal-axis single Savonius rotor is experimentally investigated in an experimental wave flume in the context of the performance assessment of the rotor in intermediate-to-shallow water depths for different parametric conditions. A number of prototypes with multiple blades of 3–5 with the same diameter and blade curvature angle are fabricated in-house and tested to measure both the long-term average torque and power generated at different submergence levels, wave heights and wave periods. The experiments are performed in the wave-current flume equipped with a piston-type wave maker with an active wave absorption capability. The energy performance of the rotor is comparatively assessed for each experimental test case based on quantitative comparison of obtained wave-to-mechanical energy conversion efficiency (ECE) to suggest a possible optimum blade number, positioning and wave physical conditions for the investigated range of wave flow characteristics. It is found that higher ECE values can be achieved at higher wave heights and blade numbers for the lower wave periods when the rotor is placed at the water surface and/or just below the surface. This study provides a proper guideline for performance analysis of such device(s) for further studies.

The conventional algorithm of perturb and observe (P&O) is widely applied due to its simplicity, low cost and easy implementation. However, it suffers from instabilities during rapid changes of weather and/or oscillation around maximum power point (MPP) at steady state. Instabilities occur due to the incorrect decision taken by the conventional P&O algorithm at the first step change in duty cycle during the rapid change in radiation. The reason for the steady-state oscillation is the continuous perturbation and tradeoff between step sizes and the convergence time. This study presents a modified P&O algorithm to overcome such drawbacks. It uses a constant load technique to help the conventional P&O algorithm for recognising the cause of power change and to enable it in taking the right decision at first step change in duty cycle during rapid change of weather. The proposed algorithm is simulated using a single solar photovoltaic module of 80 W and a DC/DC boost converter. It is validated experimentally and implemented within an embedded microcontroller. The experimental setup presents a proposed model-based design methodology that uses measurements’ data for MPP tracking systems’ design. It combines hardware-in-the-loop simulation and prototype testing using actual weather measurements. Simulation and experiments show excellent results.

Variable-step incremental conductance (Inc.Cond.) technique, for photovoltaic (PV) maximum power point tracking, has merits of good tracking accuracy and fast convergence speed. Yet, it lacks simplicity in its implementation due to the mathematical division computations involved in its algorithm structure. Furthermore, the conventional variable step-size, based on the division of the PV module power change by the PV voltage change, encounters steady-state power oscillations and dynamic problems especially under sudden environmental changes. In this study, an enhancement is introduced to Inc.Cond. algorithm in order to entirely eliminate the division calculations involved in its structure. Hence, algorithm implementation complexity is minimised enabling the utilisation of low-cost microcontrollers to cut down system cost. Moreover, the required real processing time is reduced, thus sampling rate can be improved to fasten system response during sudden changes. Regarding the applied step-size, a modified variable-step size, which depends solely on PV power, is proposed. The latter achieves enhanced transient performance with minimal steady-state power oscillations around the MPP even under partial shading. For proposed technique's validation, simulation work is carried out and an experimental set up is implemented in which ARDUINO Uno board, based on low-cost Atmega328 microcontroller, is employed.