PV Facilities Research Articles

Impact of the climate change on the site suitability for solar farms: Case study of Cameroon

It is widely agreed that in the coming decade the Earth's climate will undergo significant changes, which will considerably affect the ecosystems and populations in various ways. In this study, the climate change impact on the suitability of the recommended sustainable locations for siting solar PV facilities in Cameroon is assessed based on the downscaled climate projections and the geographic information system integrated with a multi-criteria decision-making technique. Spatial tools are used to identify the potential locations by extracting the constraint areas. The analytical hierarchy process is applied to weigh the criteria (climate, orography and vegetation) and calculate a land suitability index (LSI) to evaluate potential sites. Based on the Coordinated Regional Downscaling Experiment, the change in LSI towards the end of century is assessed considering two climate change scenarios, one optimistic and the other pessimistic. Results show that 13.7% of the study area is suitable for installing utility-size PV power plants with the highly suitable areas located mainly in the Extreme-North region of Cameroon. Under the RCP2.6 and RCP8.5 climate change scenarios, a very slight change in LSI (−5% ≤ LSI ≤ 5%) is projected for most of the potential sites across the country.

Comparative Life-Cycle Assessment of Electricity-Generation Technologies: West Texas Case Study

This comparison of five power plants in West Texas is intended to provide various decision-makers and stakeholders with a holistic picture of the life-cycle environmental impacts associated with these power plants. A key contribution of this analysis is that we assumed all power plants generate the same amount of electricity over a 30-year life, taking a 500 MW combined-cycle gas turbine (CCGT) plant as a benchmark. Also, in two cases, we added battery storage to wind and solar PV facilities to render them nearly as dispatchable as the CCGT. We included the entire supply chain supporting electricity generation, which encompassed raw material sourcing, processing, manufacturing, operations, and product end of life, also called “cradle to grave”. We report on 18 environmental impacts using ReCiPe midpoint (H) impact assessment. The supply chains are global, and impacts are felt differently by host communities across the world. The results can help stakeholders identify hotspots across numerous supply chains with the highest environmental impacts. We discuss some remedial measures and challenges to inform future analysis by the research community.

Design and development of an automated application for the analysis of monitoring data of Grid Connected Photovoltaic installations

The aim of this paper was to design and develop an application for automating the operating point of grid-connected the analysis photovoltaic of (PV) installations. This application integrates data from all of the devices that monitor information on PV installations, such as environmental sensors, inverters and meters, and it automates the storage, treatment and easy access to all information. The application is comprised by a Relational Data Base Management System (RDBMS), with a common database to store the technical data of the various components of each PV installation, and a database for each of the installations to be analyzed, linked among them and with the previous one, where data from monitoring and calculated magnitudes would be stored. Moreover a software named S·lar was developed to determine, from monitored data, some standard magnitudes related to performances and losses of PV installation components at different time scales, and to visualize in a graphical and numerical way all the stored information. This tool enables to analyze PV facilities installed by small companies, with different configurations and technical specifications, in order to control and improve their production and maintenance, based on a more comprehensive and detailed study of their real operation.

Eventual Increase in Solar Electricity Production and Desalinated Water through the Formation of a Channel between the Mediterranean and the Dead Sea

Currently, the Israeli energy industry faces the challenge of a considerable increase in solar electricity production. As a relatively isolated system, the significant expansion of solar electricity may cause problems with electricity quality. Electrical storage installation can resolve this problem. In Israel’s situation, the optimal solution could be the creation of a channel between the Mediterranean and the Dead Sea. The channel can solve three closely related problems: the increased production of desalinated water for domestic, industrial, and agricultural needs; the prevention of a permanent Dead Sea level decline and its imminent disappearance; the development of hydro-pumping electrical storage stations; and the creation of numerous PV facilities in the Negev area for national electricity generation. However, detailed analysis should be conducted for the estimation of the possible increase in solar electric generation with consideration of a stochastic PV outcome and the potential ability to use the Dead Sea for the brine discharge of electrical hydro-storage plants.

Decarbonization roadmap for China’s energy sector in the context of carbon futures trading: An energy-environment-economy assessment perspective

By virtue of the hedging and price discovery function, carbon futures trading may help carbon market function more effectively. Is it necessary to establish carbon futures trading in China? The authorities have endorsed the idea since 2015, however, the scheme has not yet started; no antecedent pre-assessment quantitative research has been carried out. Therefore this study that attempts to fill this gap in the literature, could be of real significance. Through deriving a potential decarbonization roadmap, this study tries to give some clues pertaining to the converted mitigation strategy imposed by carbon futures trading in China. A model chain has been proposed, which is composed of the Optimal Production Decision-making Model for Producers, Life Cycle Impact Assessment, Monetization, and Genetic Algorithm based optimization, to quantify the environmental benefits (including improvements to human health, ecosystem damage and increased temperature induced GDP losses) of the assumed mitigation trajectories. By setting the maximization of environmental benefits as the objective, the optimal decarbonization roadmap with carbon futures trading is derived. Results show that the optimal emission reductions for power enterprises (covered by the carbon market) for the next 10 years (2021–2030) are around 3.27 billion tonnes CO2e. If 36% of this amount is assigned to previously discussed mitigation trajectories, it is found that 106.98 GW ultra-super critical units, 160.85 GW mono-Si PV facilities and 167.26 GW doubly-fed induction generator wind capacity should be installed. Overall environmental benefits are 4.6 trillion CNY2018, over 5% of China’s 2018 GDP. Results demonstrate the optimal emission reductions and potential decarbonization roadmap for China’s power enterprises (those covered by the carbon market) under the context of carbon futures trading, which can be an important reference for the authorities and therefore encourage the establishment of the scheme.

Optimising generation and energy storage in the transition to net zero power networks

As electricity networks plan to achieve net-zero emissions, the role of private behind-the-meter (BTM) generation and storage becomes increasingly important. Two key questions arise for planners: how much BTM will there likely be in the longer term; and what impact will this have on network generation and storage? The combination of high insolation and reducing cost of small-scale solar PV systems in Western Australia has led to a rapid and ongoing take-up of private generation which already supplies around 20% of demand (around one third of houses have rooftop solar), and declining midday network loads, which will likely become negative before 2030 at some times of day and year. However, the market operator has consistently underestimated the rate of private penetration, leading to inadequate planning for the future network. Most published research focusses on network scale renewable generation but neglects the impact of private generation and storage. In contrast, this article presents a model of the integrated system to 2050, projecting the likely scale of BTM generation and identifying the optimal form of network renewable energy and storage to achieve net zero emissions. By 2050 BTM generation will likely supply around 50% of the total annual demand of 54,000 GWh pa. Given the diurnal and seasonal shape of the resulting network load and projected renewable generation costs, onshore wind energy will be the most cost optimal generation source, supplemented by smaller capacity offshore wind, wave and solar PV facilities. Network storage in the form of batteries and pumped hydro will be required, but significant curtailment will still be necessary to optimally match supply with demand. Network generation and storage costs per MWh of network load into the future are likely to be similar to, or lower than existing costs (∼$85/MWh) with the range of technologies considered in this study.

Determinants of the distribution of utility-scale photovoltaic power facilities across the globe

Photovoltaic power (PV) is the fastest-growing source of renewable electricity. Making reliable scenarios of PV deployment requires information on what drives the spatial distribution of PV facilities. Here we empirically derive the determinants of the distribution of utility-scale PV facilities across six continents, using a mixed effects logistic regression modelling approach relating the occurrence of over 10 000 PV facilities to a set of potential determinants as well as accounting for country and spatially correlated random effects. Our regression models explain the distribution of PV facilities with high accuracy, with travel times to settlements and irradiation as the main determinants. In contrast, our results suggest that land cover types are not strong determinants of the PV distribution, except for Asia and Africa where the PV distribution is related to the presence of agriculture, short natural vegetation and bare land. For Europe and Asia a considerable part of the variance in PV distribution is explained by inter-country differences in factors not included in our fixed determinants. Relevant determinants identified in our study are in line with the main assumptions made in cost of electricity (COE) maps used in the IMAGE integrated assessment model (IAM). However, we found correlations (Spearman ρ) of −0.18–0.54 between our PV probability maps and IMAGE’s COE maps. These may partly be explained by conceptual differences between our empirically-derived probability maps and the COE maps, but we also recommend using higher-resolution maps of PV potential and COE computations such as used in IAMs.

IoT-Based Data Logger for solar systems applications

A data logger is an electronic device that senses temperature, relative humidity, and other characteristics such as voltage and pulse by combining analog and digital measurements with programming methods. Thus, data acquisition systems (DAQSs) are frequently used in PV facilities to capture all system data to analyze and optimize plant performance. The major purpose of the project is to create a low-cost DAQS. The suggested monitoring system has been used to continuously gather and display the electrical output characteristics of a stand-alone PV system. PV produced voltage, current, and power are examples of such parameters. Furthermore, because the PV module short circuit current is directly proportional to the molar concentration, the global solar radiation may be determined by monitoring it. The proposed system is considered a good solution for collecting the system database to be ready for the analysis and optimization of the PV plant’s performance. The configurations of software and hardware of the proposed system are presented, and the proposed system's performance is tested when integrated with a small size PV system.

Local and Regional PV Power Variability in the Northeastern U.S.: Implications for Simplified Utility Flicker Screening Analyses

This paper presents new evidence supporting the development of a screening threshold to evaluate the impact aggregations of solar PV facilities in the northeastern United States can have on voltage deviations in the distribution grid (often called flicker). Using measurements from solar irradiance meters and customer-sited monitoring equipment for residential and light commercial solar systems in Central New York along with data from the Measurement and Instrumentation Data Centers at the Oak Ridge National Laboratory, Elizabeth City State University, and Bluefield College, we present multiple lines of support for the adoption of a flicker screening threshold equivalent to a 5% change in voltage resulting from a full-on to full-off transition of a solar facility. This approach is based on both the newer flicker perception limits in IEEE 1453-2015 and the previous limits derived from the flicker curves in IEEE 519-1992 and is consistent with recent draft recommendations from the Electric Power Research Institute (EPRI) for use in New York. Measurements of correlations between fluctuations at different sites along with a model for high densities of solar facilities are applied to allow the impact of multiple systems on a single feeder to be taken into account while maintaining the simplicity of a single screening threshold.

Analysis of the Net Metering Schemes for PV Self-Consumption in Denmark

The current Danish regulatory framework BEK 999/2016 for hourly net settled new PV facilities is analysed in detail, evaluating the technical and economic differences between the several envisioned schemes. In addition to the saved cost of the self-consumed energy, the transmission system operator (TSO) tariffs and the public service obligation (PSO) tax are avoided for the self-consumed energy. Advantages regarding the electricity tax and VAT can also be obtained but according to a more varied casuistry, with a particular incentivizing effect for the residential customers. The installation-connected type group 2 is found the cheaper scheme and the billing concepts responsible for its minor cost are identified. This analysis is expected to contribute to discerning the different economic outcomes of the various schemes, helping to take informed investment decisions. Transcending the local value, some common characteristics of this complex framework that can also be found in other regulations may ease the comprehension of the leverage points and the policy instruments for modulating the economic results of the facilities and in this way also their path of deployment.

PV power prediction in a peak zone using recurrent neural networks in the absence of future meteorological information

As the majority of daily PV power outputs is mostly obtained in a peak zone around noon, hourly PV power output prediction in a peak zone is considered as an essential function for more sophisticated operations of PV facilities. However, the prediction of PV power output in a peak zone is a challenging problem since meteorological information is continuously changing and difficult to obtain for a particular area. In addition, due to only using the meteorological information observed in the morning to estimate PV power outputs around noon, the input features which are utilized as a shorter horizon from the horizon of the prediction are making the problem even more complex. Therefore, this study proposes two PV power output prediction model by using long short-term memory (LSTM) and gate recurrent network (GRU). In particular, unlike the previous methods, the proposed models attempt to understand the hidden sequential patterns of PV power outputs based only on the information captured in the morning without utilizing future meteorological information observed around noon during training. The experiment results using a real-world dataset indicate that the proposed models perform better PV power prediction in the peak zone than conventional models.

Analysis of the Influence of Terrain Orientation on the Design of PV Facilities with Single-Axis Trackers

This paper investigates how to optimally orient the photovoltaic solar trackers of an axis parallel to the terrain, applying the sky model of Hay–Davies. This problem has been widely studied. However, the number of studies that consider the orientation (inclination and azimuth of the terrain) is very limited. This paper provides an examination of incident solar irradiance that can be extended to terrain with variable orientation and in consideration of different azimuths of the axis of rotation. Furthermore, a case study of the south of Spain is provided, considering different inclination and orientation terrain values. The results obtained in this study indicate, as a novelty, that for lands that are not south facing, the rotation axis azimuth of solar trackers should be different from zero and adjusted to the same direction as the land azimuth in order to maximize energy production. Annual energy production is sensitive to changes in the rotation axis azimuths of solar trackers (an influence of around 3% of annual energy production).

An integrated GIS and robust optimization framework for solar PV plant planning scenarios at utility scale

Today, the overall goal of energy transition planning is to seek an optimal strategy for increasing the share of renewable sources in existing power networks, such that the growing power demand is satisfied at manageable short/long term investment. In this paper we address the problem of PV penetration in electricity networks, by considering both (1) the spatial issue of site selection and size, and (2) the temporal aspect of hourly load and demand satisfaction, in addition with the investment and maintenance costs to guarantee a viable and reliable solution. We propose to address this spatio-temporal optimization problem through an integrated GIS and robust optimization model, that allows handling of the ubiquitous dependencies between resource and demand time variability and the selection of optimal sites of renewable power generation. Our approach contributes to the integration of the multi-dimensional and combinatorial aspects of this problem, gathering geographical layers (regional or national scale) and temporal packing (hourly time stamp) constraints, and cost functions. This model computes the optimal geographical location and size of PV facilities allowing energy planning targets to be met at minimal cost in a reliable manner. In this paper, we illustrate our approach by studying the penetration of large-scale solar PV in the French Guiana’s power system. Among the results, we show for instance that: (1) our approach performs geographical aggregation with real contextual data, i.e. balances the intermittency of RE sources by spreading out the corresponding installations (location + size) across the territory; (2) the total installed PV capacity can be doubled by removing the 35% penetration limit on intermittent power without exceeding hourly demand; (3) the safest investment scenario is below 30MW of new PV facilities (≈45M€ and 2 plants), though it is theoretically possible to install up to 45MW (>120M€ and 11 plants).

Long short-term memory recurrent neural network for modeling temporal patterns in long-term power forecasting for solar PV facilities: Case study of South Korea

The sites selected for solar PV facilities significantly affect the amount of electric power that can be generated over the long term. Therefore, predicting the power output of a specific PV plant is important when evaluating potential PV sites. However, whether prediction models built with data from existing PV plants can be applied to other plants for long-term power forecasting remains poorly understood. In this case, topographical and meteorological conditions, which differ among sites and change over time, make it challenging to accurately estimate the potential for energy generation at a new site. This study proposes a monthly PV power forecasting model to predict the amount of PV solar power that could be generated at a new site. The forecasting model is trained with time series datasets collected over 63 months from 164 PV sites with data such as the power plant capacity and electricity trading data, weather conditions, and estimated solar irradiation. Specifically, a recurrent neural network (RNN) model with long short-term memory was built to recognize the temporal patterns in the time series data and tested to evaluate the forecasting performance for PV facilities not used in the training process. The results show that the proposed model achieves the normalized root-mean-square-error of 7.416% and the mean absolute-percentage-error (MAPE) of 10.805% for the testing data (i.e., new plants). Furthermore, when the previous 10 months’ data were used, the temporal patterns were well captured for forecasting, with a MAPE of 11.535%. Thus, the proposed RNN approach successfully captures the temporal patterns in monthly data and can estimate the potential for power generation at any new site for which weather information and terrain data are available. Consequently, this work will allow planning officials to search for and evaluate suitable locations for PV plants in a wide area.

A Control Scheme without Sensors at the PV Source for Cost and Size Reduction in Two-Stage Grid Connected Inverters

In order to reduce the cost of PV facilities, the market requires low cost and highly reliable PV inverters, which must comply with several regulations. Some research has focused on decreasing the distortion of the current injected into the grid, reducing the size of the DC-link capacitors and removing sensors, while keeping a good performance of the maximum power point tracking (MPPT) algorithms. Although those objectives are different, all of them are linked to the inverter DC-link voltage control loop. Both the reduction of the DC-link capacitance and the use of sensorless MPPT algorithms require a voltage control loop faster than that of conventional implementations in order to perform properly, but the distortion of the current injected into the grid might rise as a result. This research studies a complete solution for two-stage grid-connected PV inverters, based on the features of second-order generalized integrators. The experimental tests show that the proposed implementation has a performance similar to that of the conventional control of two-stage PV inverters but at a much lower cost.

Self-sufficient renewable energy supply in urban areas: Application to the city of Seville

This paper proposes a methodology that, using only publicly available information, assesses the capacity of urban agglomerations to be self-sufficient and energy sustainable. The methodology evaluates the potential of the urban surface to accommodate thermal and PV solar facilities, as well as the energy storage requirements on a year-round basis. When applied to the city of Seville, considering not only the current electricity demand but also the one arising from the electrification of both urban transport and the entire thermal energy currently supplied by gas, the conclusion is that it is possible to have a self-supplied energy system based almost exclusively on PV and thermal panels. Given the high cost of seasonal storage, the resulting system is economically unviable, so it makes sense to keep the transmission grid as a back-up system to feed power into the city at certain times of the year (up to 8% of annual consumption). In the case study, the renewable energy comes mainly from PV facilities roof-mounted (72%), or ground-mounted in the surrounding urban lots (25%), plus a modest contribution from biogas (wastewater). A discussion is included regarding the role of regulated utilities, that should be reconsidered in the light of these upcoming scenarios.

Model and Analysis of Integrating Wind and PV Power in Remote and Core Areas with Small Hydropower and Pumped Hydropower Storage

Small hydropower (SHP) and pumped hydropower storage (PHS) are ideal members of power systems with regard to integrating intermittent power production from wind and PV facilities in modern power systems using the high penetration of renewable energy. Due to the limited capacity of SHP and the geographic restrictions of PHS, these power sources have not been adequately utilized in multi-energy integration. On the one hand, rapidly increasing wind/PV power is mostly situated in remote areas (i.e., mountain and rural areas) and is delivered to core areas (i.e., manufacturing bases and cities) for environmental protection and economic profit. On the other hand, SHP is commonly dispersed in remote areas and PHS is usually located in core areas. This paper proposes a strategy to take advantage of the distribution and regulation features of these renewable energy sources by presenting two models, which includes a remote power system model to explore the potential of SHP to smooth the short-term fluctuations in wind and PV power by minimizing output fluctuations as well as a core power system model to employ PHS to shift the surplus power to the peak period by maximizing the income from selling regenerated power and minimizing output fluctuations. In the proposed first model, the cooperative regulation not only dispatches SHP with a reciprocal output shape to the wind/PV output to smooth the fluctuations but also operates the reservoir with the scheduled total power production by adjusting its output in parallel. The results of a case study based on a municipal power system in Southwestern China show that, with the proposed method, SHP can successfully smooth the short-term fluctuations in wind and PV power without influencing the daily total power production. Additionally, SHP can replace the thermal power production with renewable power production, smooth the thermal output, and further reduce the operation costs of thermal power. By storing the surplus power in the upper reservoir and regenerating the power during the peak period, PHS can obtain not only the economic benefit of selling the power at high prices but also the environmental benefit of replacing non-renewable power with renewable power. This study provides a feasible approach to explore the potential of SHP and PHS in multi-energy integration applications.

Is floating photovoltaic better than conventional photovoltaic? Assessing environmental impacts

ABSTRACTPhotovoltaic (PV) solar energy installations are growing all over the world as a promising renewable alternative to generate electricity. However, many studies have highlighted some drawbacks associated with the installation and operation of conventional solar energy power plants. Thus, floating photovoltaic (FPV) systems have been emerging as a new concept in solar energy to lessen negative environmental impacts caused by allocation of conventional PV facilities. This paper is an overview of the potential negative and positive environmental impacts caused by photovoltaic systems with particular interest on large-scale conventional and floating photovoltaic. This study addresses and compares the impacts at all phases of project implementation, which covers planning, construction, and operation and decommissioning, focusing on ambient located in the tropics. The overall impacts associated with project allocation such as deforestation (for the project implementation and site accessing), bird mortality, erosion, runoff, and change in microclimate are expected to have higher magnitudes for the implementation of conventional PV facilities. The results highlight advantages of FPV over conventional PV during the operational and decommissioning phases as well. Though, further studies are required to assess both qualitative and quantitative aspects of installations in similar areas.

Big Data Analysis and Processing for Remote Control of PV Facilities

Big Data Analysis and Processing for Remote Control of PV Facilities

Adfreeze Forces on Lightly Loaded Pile Foundations of Solar PV Farms in Cold Regions

Renewable energy generation through utility scale ground mounted solar photo-voltaic systems has gained steady popularity with increasing number of such facilities being constructed in various regions worldwide. Solar PV systems are very popular in the province of Ontario in Canada and strong growth in this sector is led by the popular initiatives of the Government of Ontario which offers extremely attractive rates for generation of renewable energy through Ontario Hydro’s popular Feed-In Tariff (FIT) Program. Many other countries offer incentives on such generation of renewable energy while many governments aim at increasing the percentages of renewable energy in their systems tremendously. Most ambitious plan has recently been launched by the state of Hawaii to deploy 100% of renewable energy in their grid by 2045. Solar PV systems are a cheap source of renewable energy as the energy released by the sun is harnessed as electricity by the solar photo-voltaic panels which is fed to the main transmission systems after raising its voltage. The costs of solar photo-voltaic panels meanwhile have also kept downward trends while the manufacture of various types of solar panels has multiplied rapidly. These renewable energy generation facilities are fully sustainable being completely recyclable on completion of their design/ contract period. Typical utility scale ground mounted solar PV facilities usually comprise of solar PV panels mounted on series of racking tables supported on foundations mostly comprising of partially embedded steel pipes. The governing loads for the foundations of these lightly loaded solar PV structures are usually frost loads in areas facing extremely cold winters. In fine grained soils like silty/ clayey soils, large adfreeze stresses develop due to penetrating frost deep into the soil resulting into uplift of foundation piles. Typical winter conditions in Ontario are harsh with extreme frost conditions in most areas which poses unique issues for design and construction of such foundations. Being a relatively newer technology, codes and standards for design and testing of such lightly loaded solar PV structures are still in the formulation stages. Frost heaving and its effects often create adverse conditions for these structures thereby affecting the production and continuous supply of renewable energy. Due to larger depths of frost penetration in extreme winter conditions, understanding the action of frost and related development of adfreeze stresses on these lightly loaded pile foundations is extremely important. Calculating reasonable frost depths and thereby the design loads is an important part of pile design for such facilities while the contractors tend to save on pile lengths to save on costs and compromising the structural design. Many such Solar PV facilities have experienced frost uplift of foundation piles either during the construction phase or during its lifetime. Since frost heave is more of a serviceability related issue, unfactored adfreeze loads without any factor of safety is a usual tendency by the EPC contractors. This paper investigates the frost depths and adfreeze stress related issues with the foundation piles of solar PV facilities hence the governing design forces on these piles and suggests appropriate frost related design stresses for the foundation piles. The authors have been heavily involved in design/ design reviews, pile selection/ design and pile load testing in the majority of the solar PV farms in Canada and US along with rehabilitation of piles affected by frost [1,2,3].