Showing papers on "Solar power published in 2022"

Environmental impact of renewable energy source based electrical power plants: Solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic

Abstract: Renewable energy source (RES) based electrical power plants are widely considered green and clean due to their contribution to decarbonizing the energy sectors. It is apparent that RESs do not produce carbon dioxide, however their significant negative impacts on the environment are still found and cannot be ignored. In this paper, the environmental impacts of RES based power plants are analyzed through a comprehensive review considering solar thermal, solar photovoltaic, wind, biomass, geothermal, hydroelectric, tidal, ocean current, oceanic wave, ocean thermal, and osmotic effects. Solar thermal power is well known as concentrated solar power. A strength, weakness, opportunity, and threat (SWOT) analysis is carried out and discussed for all RES based power plants. Comparative SWOT analyses for solar photovoltaic and concentrated solar power plants are presented. The comparative environmental impact analyses for all existing RES based power plants are tabulated for various attributes. These attributes include but are not limited to human health, noise, pollution, greenhouse gas emission, ozone layer depletion, toxification, flooding, impact on inhabitants, eutrophication, dried up rivers, and deforestation. Based on the analysis, it is found that careful selection of RES for electrical power plants is necessary because improper utilization of RES could be very harmful for the environment.

A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality

Abstract: The ability to forecast solar irradiance plays an indispensable role in solar power forecasting, which constitutes an essential step in planning and operating power systems under high penetration of solar power generation. Since solar radiation is an atmospheric process, solar irradiance forecasting, and thus solar power forecasting, can benefit from the participation of atmospheric scientists. In this review, the two fields, namely, atmospheric science and power system engineering are jointly discussed with respect to how solar forecasting plays a part. Firstly, the state of affairs in solar forecasting is elaborated; some common misconceptions are clarified; and salient features of solar irradiance are explained. Next, five technical aspects of solar forecasting: (1) base forecasting methods, (2) post-processing, (3) irradiance-to-power conversion, (4) verification, and (5) grid-side implications, are reviewed. Following that, ten potential research topics for atmospheric scientists are enumerated; they are related to (1) data and tools, (2) numerical weather prediction, (3) forecast downscaling, (4) large eddy simulation, (5) dimming and brightening, (6) aerosols, (7) spatial forecast verification, (8) multivariate probabilistic forecast verification, (9) predictability, and (10) extreme weather events. Last but not least, a pathway towards ultra-high PV penetration is laid out, based on two recently proposed concepts of firm generation and firm forecasting. It is concluded that the collaboration between the atmospheric science community and power engineering community is necessary if we are to further increase the solar penetration while maintaining the stability and reliability of the power grid, and to achieve carbon neutrality in the long run.

Potential contributions of wind and solar power to China's carbon neutrality

Abstract: China's goal of being carbon-neutral by 2060 requires a green electric power system dominated by renewable energy. However, the potential of wind and solar alone to power China remains unclear, hindering the holistic layout of the energy development plan. Here, after taking temporal matching of supply and demand (60 min), land use, and government policy into account and assuming lossless transmission, we demonstrate that deploying wind and solar capacity of 2495 and 2674 GW, respectively, within flexible and optimized grids can meet ∼67% of electricity demands by all society sectors for 2050 (∼6.3% curtailment rate), even without other costly power sources or storage. Spatially explicit configurations of the grids are provided simultaneously to support this achievement. The resulting green electricity supply of 10.4 PWh per year help secure China's carbon-neutral goal and reduces 2.08 Mt SO2 and 1.97 Mt NOx emissions annually. Our findings recommend policymakers accelerate exploiting complementary wind and solar power as the dominant source of energy.

A review of very short-term wind and solar power forecasting

Abstract: Installed capacities of wind and solar power have grown rapidly over recent years, and the pool of literature on very short-term (minutes- to hours-ahead) wind and solar forecasting has grown in line with this. This paper reviews established and emerging approaches to provide an up-to-date view of the field. Knowledge transfer between wind and solar forecasting has benefited the field and is discussed, and new opportunities are identified, particularly regarding use of remote sensing technology. Forecasting methodologies and study design are compared and recommendations for high quality, reproducible results are presented. In particular, the choice of suitable benchmarks and use of sufficiently long datasets is highlighted. A case study of three distinct approaches to probabilistic wind power forecasting is presented using an open dataset. The case study provides an example of exemplary forecast evaluation, and open source code allows for its reproduction and use in future work.

End-of-life management of solar PV waste in India: Situation analysis and proposed policy framework

Abstract: Increasing energy demands and commitments in relation to climate change have accelerated the deployment of solar power globally, especially in India. Grid-connected solar capacity in the country has increased ∼11 times in just five years, from 2.6 GW in March 2014 to 28.18 GW in March 2019. However, this development has inevitably also led to the emergence of significant volumes of solar photovoltaic (PV) waste, which will only increase in the upcoming years, a considerable challenge for its waste management system. The environmental and human health risks associated with the unscientific dumping of solar PV waste have been well established in the existing literature, presenting the need to develop an effective strategy to manage this emerging waste stream. This paper presents a review of literature about India's solar PV waste management sector with a view to understanding the ground realities and identifying challenges and barriers that hinder the adoption of a regularised strategy for its management using the DPSIR framework approach. It goes on to propose a regulatory framework aimed at mainstreaming the end-of-life (EOL) management of solar PV waste in India after evaluating strategies that have already been used worldwide. In line with the Extended Producer Responsibility (EPR) concept, a multistakeholder, multi-sectoral and systematic approach has been adopted to develop a specific regulatory framework for India. The framework was subjected to a SWOT analysis to evaluate its functionality. The SWOT analysis indicates that one of the critical strengths of the framework is that it is based on a participatory approach to be adopted by all stakeholders for managing this emerging waste stream.

A novel long term solar photovoltaic power forecasting approach using LSTM with Nadam optimizer: A case study of India

Abstract: Solar photovoltaic (PV) power is emerging as one of the most viable renewable energy sources. The recent enhancements in the integration of renewable energy sources into the power grid create a dire need for reliable solar power forecasting techniques. In this paper, a new long‐term solar PV power forecasting approach using long short‐term memory (LSTM) model with Nadam optimizer is presented. The LSTM model performs better with the time‐series data as it persists information of more time steps. The experimental models are realized on a 250.25 kW installed capacity solar PV power system located at MANIT Bhopal, Madhya Pradesh, India. The proposed model is compared with two time‐series models and eight neural network models using LSTM with different optimizers. The obtained results using LSTM with Nadam optimizer present a significant improvement in the forecasting accuracy of 30.56% over autoregressive integrated moving average, 47.48% over seasonal autoregressive integrated moving average, and 1.35%, 1.43%, 3.51%, 4.88%, 11.84%, 50.69%, and 58.29% over models using RMSprop, Adam, Adamax, SGD, Adagrad, Adadelta, and Ftrl optimizer, respectively. The experimental results prove that the proposed methodology is more conclusive for solar PV power forecasting and can be employed for enhanced system planning and management.

Thermodynamic and economic analysis of a novel combination of the heliostat solar field with compressed air energy storage (CAES); a case study at San Francisco, USA

Abstract: In spite of the various important features of the compressed air energy storage (CAES), this technology suffer from some environmental effects because of the burn of fossil fuels in the combustor that reduces its widespread use. To address this problem, a novel green and effective concept based on the combination of the CAES with the concentrated solar power and absorption chiller is introduced. This hybridization not only helps the further development of both the CAES and solar sites as a type of renewable energy, but it also simultaneously generates power, cooling capacity, and hot water that are the main components for reducing peak energy demand, especially in hot climates. Thermodynamic analyses revealed that this combination results in a round trip efficiency and an exergy efficiency of 67.5 and 45.6%, respectively. In addition, solar receiver tower, heliostat field, and pressure regulator are the equipment with the highest exergy destruction. To approve the economic feasibility of the proposed system, a precise economic analysis was done for the case study of San Francisco, USA, concluding that the system has a payback time of 1.7 years and profitability of $231 M during the 30 years of its service time.

Completed Review of Various Solar Power Forecasting Techniques Considering Different Viewpoints

Abstract: Solar power has rapidly become an increasingly important energy source in many countries over recent years; however, the intermittent nature of photovoltaic (PV) power generation has a significant impact on existing power systems. To reduce this uncertainty and maintain system security, precise solar power forecasting methods are required. This study summarizes and compares various PV power forecasting approaches, including time-series statistical methods, physical methods, ensemble methods, and machine and deep learning methods, the last of which there is a particular focus. In addition, various optimization algorithms for model parameters are summarized, the crucial factors that influence PV power forecasts are investigated, and input selection for PV power generation forecasting models are discussed. Probabilistic forecasting is expected to play a key role in the PV power forecasting required to meet the challenges faced by modern grid systems, and so this study provides a comparative analysis of existing deterministic and probabilistic forecasting models. Additionally, the importance of data processing techniques that enhance forecasting performance are highlighted. In comparison with the extant literature, this paper addresses more of the issues concerning the application of deep and machine learning to PV power forecasting. Based on the survey results, a complete and comprehensive solar power forecasting process must include data processing and feature extraction capabilities, a powerful deep learning structure for training, and a method to evaluate the uncertainty in its predictions.

Progress in research and technological advancements of thermal energy storage systems for concentrated solar power

Abstract: A global transition towards more sustainable production and consumption systems has led to an increasing share of renewables in the energy market. Renewables, majorly solar PV and wind power are accounted for around 10 % of the global power production in 2020. In this context, concentrated solar power (CSP) technologies are seen to be one of the most promising ways to generate electric power in coming decades. However, because of the intermittent nature of solar energy, one of the key factors that determine the development of CSP technology is the integration of efficient and cost-effective thermal energy storage (TES) systems. TES system not only plays a crucial role in bridging the gap between energy supply and demand but also increases the performance and reliability of energy systems and plays a crucial role in energy conservation. Though there have been many reviews on TES system, however the existing literature is either over 5 years old or focus on thermal storage materials for low temperature applications. To bridge this gap, this work presents a comprehensive review on the actual state of all major components of cutting-edge TES technologies for CSP application and condenses all the available information and categorizes them considering the main functional parts and remarking the current research progress in each part as well as the future challenging issues. It intends to understand and explain the foundations of the innovative concepts, future research directions and strategies developed over the past 10 years to tune the engineering and thermal sciences of TES systems. Insight into classes of TES storage materials with details on geometrical configurations, design parameters, physical properties, operational issues, cost, technology readiness level, suitability to CSP application and comparative assessment of various TES systems is provided.

Critical Review of Data, Models and Performance Metrics for Wind and Solar Power Forecast

Abstract: Global climatic changes and increased carbon footprints provided the main impetus for the decrease in the use of fossil fuels for electricity generation and transportation. Matured manufacturing technologies of solar PV panels and on-shore and off-shore windmills have brought down the cost of generation of electricity using solar energy on par with conventional fossil fuel. Initially, solar and wind power generation was envisioned for microgrids, serving small local communities. However, advancements in power electronics have now facilitated large solar and wind farms to be integrated with main power grids. In this context, hosting capacity, which is the amount of distributed energy resources a grid can accommodate, without significant infrastructure up-gradation, has gained importance. In determining the hosting capacity at a particular location, the uncertainties of wind and solar power generation play a role. Effective forecasting models using time-series weather data can be built to predict wind and solar power generation. This forecast is essential to ensure proper grid operation and control when renewable energy sources are already installed. The forecast is also useful in the planning stages for investment decisions and distribution system planning. While long-term forecasts are rarely needed for the operation of integrated grids, accurate short-term predictive models are necessary for scheduling. This paper presents an extensive review of various forecast models available in the literature. The study mainly focuses on the short-term forecast, providing a critical review of the duration of data used in each model and a synoptic comparison of their performance indices.

Application of choosing by advantages to determine the optimal site for solar power plants

Abstract: Solar energy is a critical component of the energy development strategy. The site selection for solar power plants has a significant impact on the cost of energy production. A favorable situation would result in significant cost savings and increased electricity generation efficiency. California is located in the southwest region of the United States of America and is blessed with an abundance of sunlight. In recent years, the state's economy and population have expanded quickly, resulting in an increased need for power. This study examines the south of California as a possibly well-suited site for the constructing large solar power plants to meet the local electricity needs. To begin, this article imposed some limits on the selection of three potential sites for constructing solar power plants (S1, S2, and S3). Then, a systematic approach for solar power plant site selection was presented, focusing on five major factors (economic, technological, social, geographical, and environmental). This is the first time that the choosing by advantages (CBA) method has been used to determine the optimal sites for solar power plant construction, with the possible sites ranked as S2 > S1 > S3. The results were then compared with traditional methods such as the multi-criteria decision-making method. The findings of this study suggest that the CBA method not only streamlines the solar power plant site selection process but also closely aligns with the objectives and desires of the investors.

Geopolymer Concrete Performance Study for High-Temperature Thermal Energy Storage (TES) Applications

Abstract: Solar energy is an energy intermittent source that faces a substantial challenge for its power dispatchability. Hence, concentrating solar power (CSP) plants and solar process heat (SPH) applications employ thermal energy storage (TES) technologies as a link between power generation and optimal load distribution. Ordinary Portland cement (OPC)-based materials are widely used in sensible TES, but their use is limited to operation temperatures below 400 to 500 °C because of thermal degradation processes. This work proposes a geopolymer (GEO)-based concrete as a suitable alternative to OPC concrete for TES that withstands high running temperatures, higher than 500 °C. To this end, thermophysical properties of a geopolymer-based concrete sample were initially measured experimentally; later, energy storage capacity and thermal behavior of the GEO sample were modeled numerically. In fact, different thermal scenarios were modeled, revealing that GEO-based concrete can be a sound choice due to its thermal energy storage capacity, high thermal diffusivity and capability to work at high temperature regimes.

A Novel Multiport Converter Interface for Solar Panels of CubeSat

Abstract: Maximization of solar energy harvest and miniaturization of dc–dc converters are essential for low earth orbit (LEO) CubeSats, which are constrained by volume and weight restrictions. The state-of-the-art electric power system (EPS) architectures utilize several individual dc–dc converters to maximize solar energy harvest but it has a tradeoff with miniaturization as it requires several inductors. The main objective of this article is to propose a single-inductor-based multiport converter topology for the LEO CubeSat's EPS. The proposed topology interfaces the photovoltaic (PV) panels to the energy storage system and a control strategy have been developed to extract maximum solar power from each PV panel under wide varying irradiation conditions of the LEO CubeSat. The proposed topology consists of series-connected half-bridge modules fed by PV panels and their output is supplied to the energy storage system via a boost converter. The principle of operation is introduced followed by steady-state analysis and converter dynamics analysis. The performance of the proposed converter is verified for several case studies with an experimental prototype developed based on 1U CubeSat specifications.

Does solar energy reduce poverty or increase energy security? A comparative analysis of sustainability impacts of on-grid power plants in Burkina Faso, Madagascar, Morocco, Rwanda, Senegal and South Africa

Abstract: The United Nations has identified 17 Sustainable Development Goals (SDGs) that need to be addressed to ensure a peaceful and sustainable existence for all living species on planet earth. To a large extent, the SDGs are interconnected, so that addressing one can simultaneously influence another; here, we explore the role of photovoltaic energy technology in combating climate change and its potential advantages in alleviating poverty in six African countries. In this context, photovoltaic solar power plants which produce “green” electrical power from solar radiation may contribute to the achievement of several of these goals. This article analyzes the extent to which the operation of on-grid solar power plants found in Burkina Faso, Madagascar, Morocco, Rwanda, Senegal, and South Africa is a vector for sustainable development. Our results give us the opportunity to identify the role of governments in enhancing solar PV sustainability for poverty alleviation. Our methodology is both qualitative and quantitative. We pursued six case studies, performed a thorough grid analysis (seven categories of impacts analyzed at local, regional, national, and international levels), and defined a sustainability index specific to solar power plants. According to the sustainability model derived from our results based on contextual and structural variables, we found that, unless appropriate adjustments are made, grid-connected photovoltaic solar power plants have a limited impact on sustainable development and poverty abatement, especially at the local level. For a video summary of this paper, please visit: https://www.polymtl.ca/magi/en/research-presentation-carole-brunet-phd.