Solar Energy Resources Research Articles

Facile preparation of a novel core-shell fiber S-scheme C/CoS2@BiOBr heterojunction photocatalyst for efficient degradation of Congo red under visible light

Generally, it is of great scientific significance to improve the utilization of solar energy resources. However, it is still a huge challenge at present. For this reason, the construction of photocatalysts with heterostructures is an effective way. In this paper, a novel core-shell fiber-like C/CoS2@BiOBr S-scheme heterojunction with visible light response was rationally designed by in-situ reduction of MOF through anion exchange strategy. Density functional theory (DFT) calculation and characterization analysis show that the internal electric field is formed between C/CoS2 and BiOBr after contact. This is beneficial to charge transfer and separation, and the S-sheme transfer path endows the separated electrons and holes with large redox potential to participate in the reaction directly. Moreover, the addition of BiOBr significantly enhanced the visible light absorption of the composites and improved the photochemical properties. It is worth noting that C/CoS2@BiOBr has excellent catalytic ability, and the optimal value of photodegradation of Congo red (CR) reaches more than 99 % within 15 min of visible light irradiation. Consequently, the active species were •O2- and h+. •O2- play a dominant role in the photocatalytic process. The space charge transfer and possible separation mechanisms of the new heterostructures are further proposed. This study provides some new ideas for the preparation of efficient water purification photocatalysts.

Hybrid offshore wind–solar energy farms: A novel approach through retrofitting

Due to the inherent variability of the power output of offshore wind farms, their integration into electrical grids poses a challenge to their stability and leads to significant balancing costs. Combining wind and solar power may be expected to mitigate the power output variability. In addition, a number of synergies can be realised—shared infrastructure, shared crews and vessels for operations and maintenance, and last but not least, optimum use of scarce marine space. The objective of this work is to investigate this hybrid approach and, in particular, to determine the optimum capacity of the solar energy subsystem given a certain installed capacity of the wind energy subsystem. Three case studies are considered in Europe and China. Each of them is an existing wind farm that could be retrofitted with floating solar PV. After assessing the local wind and solar energy resources, the optimal size of the floating solar array is calculated with a view to smooth the aggregated power output of each farm. Subsequently, the benefits of this hybrid approach are demonstrated from various perspectives. It is found that a much larger solar array is required for a wind farm with a large installed capacity, but the specific optimal size depends more on the local wind and solar resources. The novelty of this paper lies in its exploration of retrofitting existing offshore wind turbines with floating solar PV systems from the perspective of addressing the variability challenge for the currently operating wind farms. This study could serve as a guideline for project designs aiming to retrofit existing offshore wind farms with solar PV technology, thus reducing balancing costs and facilitating the penetration of offshore renewable energy into national power grids.

Multi-Combination Method for Intelligent Remote Sensing of Solar Energy Resources in Different Regions

Solar energy is the main means of new energy development, which has the characteristics of a clean, safe and wide range of resources, but there are problems of large differences in radiation and heat in the process of solar energy collection, and how to effectively utilize solar energy resources is the focus of current research In order to improve the utilization effect of solar energy resources, this paper proposes a multi-component remote sensing analysis method based on remote sensing. Firstly, the solar energy resources were quantitatively analyzed to construct the solar energy resource utilization set. Then, with the help of multiple combination indicators such as solar trajectory, direct inclination, and light intensity, intelligent remote sensing judgment was carried out on solar energy resources. Finally, compared with a single measurement method, the utilization accuracy, utilization amount and utilization cost of solar energy resources are verified. The results show that the multivariate combination method can remotely sense solar energy resources in different regions and times, with a control rate of 56%, and a solar energy utilization set with an increase rate of 20%. Moreover, the multi-combination method can expand the control area of solar energy resources, and the expansion rate can be increased by 10%. Therefore, the multi-combination method can improve the utilization rate of solar energy resources, reduce labor costs and management costs, and increase power generation, which is better than a single measurement method.

Study of a Novel Updraft Tower Power Plant Combined with Wind and Solar Energy

This study presents a novel solar updraft tower power plant (SUTPP) system, which has been designed to achieve the simultaneous utilization of solar and wind energy resources in desert regions, in response to the pressing demand for sustainable and efficient renewable energy solutions. The aim of this research was to develop an integrated system that is capable of harnessing and converting these abundant energy sources into electrical power, thereby enhancing the renewable energy portfolio in arid environments. The methodology of this study involved the design and construction of a prototype SUTPP, comprising a 53 m high tower, a 6170 m2 collector, five horizontal-axis wind turbines, and a thermal energy storage layer made up of pebbles and sand. The experimental setup was meticulously detailed, and experiments were conducted to collect data on the system’s performance under various environmental conditions. Subsequently, three-dimensional numerical simulations were performed to explore the effects of ambient wind speed and solar radiation on the output power of the SUTPP. The results indicate that the output power of the system increases with the increase in ambient wind speed and solar radiation. The impact of solar irradiation on output power was observed to diminish as ambient wind speeds increased. Notably, as the inlet wind speed rose from 4 m/s to 12 m/s, the output power showed a substantial increase of 727%. The numerical simulations revealed that ambient wind speed has a more pronounced effect on power output compared to solar radiation. Furthermore, it was found that the influence of solar radiation is significant at low wind speeds, with its impact decreasing as wind speed increases. This research provides essential guidance for the design and engineering of highly efficient solar thermal energy utilization projects, representing a significant advancement in the field of renewable energy technology deployment in desert environments.

Reconstructing 10-km-resolution direct normal irradiance dataset through a hybrid algorithm

Evaluating, mapping, and monitoring high-quality Direct Normal Irradiance (DNI) is crucial for the design, financing, and operation of solar power plants, especially those utilizing concentrating technologies. In China, limited number of first-class meteorological stations provide DNI observations. To bridge this gap, this study has reconstructed a comprehensive 41-year (1982–2022) daily DNI dataset for China (CHDNI). This dataset integrated CMA ground-based observations with ERA5 and MERRA-2 reanalysis data, employing a spatial resolution of 10 km. The data was processed using the REST2 radiation transfer model combined with Stacking ensemble machine learning. Validation with ground-based measurements indicated that the Stacking model exhibited high and consistent performance. This was evidenced by its sample-based cross-validation results, showing a correlation coefficient (R) of 0.92, a root-mean-square error (RMSE) of 32.04 W/m2, a mean absolute error (MAE) of 23.68 W/m2, and a global performance indicator of 3.86. Among the four analyzed DNI products (CERES, ERA5, SWGDN, and CHDNI), CHDNI demonstrated the closet alignment with ground observations, evidenced by the least deviation (MAE = 21.67 W/m2 and RMSE = 31.00 W/m2) and the highest R value (0.92). Aerosol optical depth and cloud cover emerged as the primary factors influencing the quality and accuracy of DNI products under clear-sky and total-sky conditions. The spatial distribution of DNI across China is complex, showcasing DNI values ranging from 25.82 W/m2 to 194.22 W/m2, with an average value of 98.08 W/m2 over 41-year. This dataset is a valuable resource for analyzing regional climate change, photovoltaic applications, and solar energy resources assessment.

Theoretical and experimental analyses and optimizations of direct coupling photovoltaic-thermoelectric systems

A photovoltaic-thermoelectric (PV-TE) system is modeled theoretically and demonstrated experimentally. Mathematical formulations of the system are proposed according to energy conservation and finite-time thermodynamics, which can be applicable to analyze and optimize the system that consists of commercial photovoltaic (PV) cells and thermoelectric generators (TEGs). The genetic algorithm is introduced to maximize the system's power by optimizing multiple parameters. In Yan'an City, which is located in the northern Shaanxi Province in northwest China, the actual solar irradiance is recorded for almost a full year and the proposed model is verified. Theoretical and experimental results are analyzed and compared. It is found that there are several independent structure parameters in the PV-TE systems and they should be optimized simultaneously to maximize the performance. The PV-TE system's maximum theoretical average power of 0.343 W is 2.69 % greater than the solo PV cell's maximum theoretical power of 0.334 W. The measured average power of the system of 0.317 W is 0.32 % more than that of a solo PV cell of 0.316 W. The duration of strong lighting in Yan'an City reaches 8 h every day for nearly one year and the irradiation intensity can approach 1000 W/m2. The solar radiance is weakly affected by the seasonal changes of four seasons but is greatly affected by rainy days and cloud thickness. The research findings can serve as a helpful guide for the specific implementation of the PV-TE system and exploitation of solar energy resources in northwest China.

Multi-criteria decision-making approach in assessing the key barriers to the adoption and use of SWH in West Africa–Combination of modified Delphi and Fuzzy AHP

Africa faces a significant energy crisis, with over 600 million people lacking access to affordable and reliable power to meet their energy demands, despite the continent's vast solar energy potential. Several studies have indicated the high potential of solar water heaters (SWH) in various African countries in Africa due to the enormous solar energy resource. However, the diffusion and use of the same in Africa, especially in the West African sub-region, have been very slow compared to other sub-regions. This study thus assesses the barriers that affect the adoption and use of SWH systems using the Delphi method and the Fuzzy Analytical Hierarchy Process to prioritize and rank them for decision-making. The study identified five main barriers and prioritized them in the order of financing, gender, and market-related barriers (51 %), political, policy, and regulatory barriers (19 %), technical barriers (14 %), socio-cultural and public awareness barriers (11 %), as well as lack of standardization and quality assurance (6 %). The high cost of finance as well as difficulties in accessing finance prevent private sector investment, which ultimately affects the large-scale use of the SWH system in the sub-region. Also, the uneducated and a section of the educated do not fully appreciate the merits of the SWH system. This paper is expected to inform academics, practitioners, and regulators on future efforts to adopt for the SWH technologies in Africa, and to improve policies and strategies for their adoption across the continent.

Evaluation and correction of solar irradiance in Somaliland using ground measurements and global reanalysis products

Properly understanding solar irradiance can help accurately quantify the solar energy resource and guide sustainable development projects, particularly where measured solar data are scarce or suffer from detrimental data quality issues. This study aims to assess and improve solar global horizontal irradiance (GHI) data from a diverse range of global reanalysis datasets by utilizing measured data from two ground weather stations located in Somaliland. A comprehensive evaluation framework is employed, combining various statistical and regression error metrics, whereas bias correction methods are implemented. The comparative study covers several analytical facets such as the hourly, daily and monthly data analysis before and after correction along with analyzing the seasonal variations, clear-sky and all-sky conditions. The analysis revealed pattern of an overall underestimation of GHI with varying degrees of accuracy in the estimated GHI datasets before and after correction. The annual ranges for rMBE, rMAE, rRMSE and R2 extend from 3–31%, 12–33%, 19–53% and 0.797–0.979, respectively, across all datasets for six-hourly data in the two observed stations. Following bias correction, the ranges for rMBE, rMAE, rRMSE reduce to is 0%, 8–31%, 11–34% and R2 increase to 0.897–0.984 respectively. While certain datasets such as MERRA-2 and SARAH-2 demonstrate close alignment with ground data before correction, other especially ERA5-Land exhibit exceptional improvement after the bias correction.

A comparative study of machine learning approaches for an accurate predictive modeling of solar energy generation

Solar energy prediction poses a challenging task that necessitates robust models and precise data to accurately forecast solar energy yield, especially in grid areas with high photovoltaic shares. Existing methods often rely on statistical or physical models, which have limitations in capturing the complex and non-linear relationships between weather variables and solar power generation. In this paper, we address this issue by comparing and evaluating different learning models, ranging from artificial neural networks (ANNs) and random forest models to long- and short-term memory (LSTM) networks, to predict the PV energy yield based on weather forecast data. A methodology has been developed to evaluate various models using real-world datasets from a large-scale industrial solar project, incorporating historical photovoltaic data, meteorological data, and solar irradiation data. The experimental results showed that the Random Forest Algorithm (RFR) consistently outperforms other algorithms, providing a mean absolute error (MAE) of 0.06 and a root mean square error (RMSE) of 0.15 when applied to historical meteorological datasets. The accuracy of the learning model was improved by combining meteorological data with a solar irradiation dataset to obtain an MAE of 0.03 % and an RMSE of 0.09 %. Validation analysis showed the proposed model is effective in both forecast accuracy and stability. The proposed methodology can provide valuable information to PV system operators, grid managers, and energy planners, facilitating the optimization of solar energy resources.

Progress on Material Design and Device Fabrication via Coupling Photothermal Effect with Thermoelectric Effect.

Recovery and utilization of low-grade thermal energy is a topic of universal importance in today's society. Photothermal conversion materials can convert light energy into heat energy, which can now be used in cancer treatment, seawater purification, etc., while thermoelectric materials can convert heat energy into electricity, which can now be used in flexible electronics, localized cooling, and sensors. Photothermoelectrics based on the photothermal effect and the Seebeck effect provide suitable solutions for the development of clean energy and energy harvesting. The aim of this paper is to provide an overview of recent developments in photothermal, thermoelectric, and, most importantly, photothermal-thermoelectric coupling materials. First, the research progress and applications of photothermal and thermoelectric materials are introduced, respectively. After that, the classification of different application areas of materials coupling photothermal effect with thermoelectric effect, such as sensors, thermoelectric batteries, wearable devices, and multi-effect devices, is reviewed. Meanwhile, the potential applications and challenges to be overcome for future development are presented, which are of great reference value in waste heat recovery as well as solar energy resource utilization and are of great significance for the sustainable development of society. Finally, the challenges of photothermoelectric materials as well as their future development are summarized.

Assessment of site suitability for centralized photovoltaic power stations in Northwest China's six provinces

Northwest China has abundant solar energy resources and extensive land, making it a pivotal site for solar energy development. However, restrictions on site selection and severe weather conditions have hindered the establishment and operation of photovoltaic (PV) power stations. Previous studies have not considered meteorological factors when evaluating site suitability, leading to research gaps in identifying suitable areas and establishing indicator systems. We aimed to address these gaps by considering seven factors constraining the construction of centralized PV power stations (CPPS) and developing an indicator system based on terrain, climate, soil, and economic factors. Furthermore, we conducted analyses to quantify the solar energy generation potential (SEGP), carbon emissions reduction benefits, and land utilization potential at different sites. The findings indicate that areas rated as very suitable and extremely suitable comprised the largest proportion (62.35%) of site suitability. The correlation between site suitability and electricity consumption was largely non-significant, highlighting the need for enhanced coordination. Additionally, we forecast the electricity consumption in Xinjiang, Gansu, Inner Mongolia, Qinghai, Ningxia, and Shaanxi for 2030 to be 56.62, 19.86, 54.54, 13.59, 15.96, and 33.34 ( × 1011 kWh), respectively, with corresponding carbon emissions reduction potentials of 20.2, 7.1, 19.4, 4.8, 5.7, and 11.9 ( × 109 kg). Consequently, PV carbon reduction and land utilization potential are substantial.

Evaluation of food-water-energy sustainable development in China’s western frontiers during 2010–2021

ABSTRACT Food, water, and energy (FWE) are foundational resources that sustain human well-being and societal advancement. The examination of climate change effects on FWE resources is imperative, particularly in regions abundant in natural resources but ecologically fragile. In this context, we investigated the spatiotemporal changes of FWE resources in China’s western frontiers, where both resource wealth and climate vulnerability are critical. This study proposes an innovative approach to comprehensively analyze the dynamics of food production, surface water, and solar energy from 2010 to 2021 by integrating easily accessible and widely applicable variables, and utilizing remote sensing and statistical data within a sustainable development framework. The results show that: (1) both crop yield and cropland area display an upward trend; (2) the expansion of overall surface water area in Xinjiang is mainly driven by changes in precipitation and temperature, while in Xizang, such a relationship is not evident; (3) Xinjiang and Xizang have advantages in solar photovoltaic (PV) development due to their abundant solar resources. Our results suggest that such spatiotemporal dynamics in food production, surface water and solar energy resources can intuitively reflect the sustainable development status of FWE resources in China’s western frontiers.

Measuring the Costs of Renewable Resources and Their Role in Reducing the Costs of Available Resources in The Iraqi Economic Units

As a result of the developments witnessed by the world and technological progress in all fields and its trend towards preserving the environment and its resources and reducing pollution in it, which required the economic units to search for resources to help them reduce costs and protect the environment from pollution while preserving its non-renewable resources, and in order to address this problem, the researcher determined the costs of available resources (non-renewable) for the production of electrical energy, which constitutes the largest proportion of indirect costs, Therefore, the research was launched to reduce these costs by replacing non-renewable resources with renewable resources in order to reduce costs on the one hand, protect the environment on the other hand, and help preserve non-renewable resources for future generations. To achieve this goal, the researcher carried out the field pension for Al-Mamoon factory in order to determine energy costs Electric using non-renewable resources, as well as field visits to obtain information from the Free Lights Company for Solar Energy and General Trading in order to determine the costs of renewable resources represented by solar energy. One of the most important results of the research was the is that the best resource of the six resources for generating electrical energy is the solar energy resource, it is safe and available in abundance and does not pose a threat to humans and the environment, Also, the findings of the current research revealed that investing in solar cells leads to an increase in investment costs, but at the same time leads to reducing the costs of use over its life of 30 years as a result leads to reducing the costs of producing electrical energy.

The effect of adding layers of date stones on the profitability of brackish water solar desalination process

Lately, there has been a pronounced and alarming up tick in the global demand for fresh water, resulting in a limited availability of this precious resource. Solar desalination emerges as a promising solution, particularly for supplying the sparsely populated desert regions in the southern regions of Algeria, where plentiful solar energy and subterranean brackish water resources are present.The current paper seeks to optimize the performance of traditional solar stills and elevate the quality of distilled water by incorporating layers of blackened date stones as an additional heat storage medium. Date stones, typically discarded post-date consumption, undergo a process of washing and blackening before being introduced in two forms (stone and powder). They are then uniformly distributed across the horizontal surface of solar still’s absorber.Three solar stills of identical design featuring glass sides were designed, manufactured, and subjected to testing to compare their productivity with that of a control unit. Experimental trials conducted at Ouargla University reveal significant enhancements the inclusion of a single layer of date stones (approximately 2.210 kg/ (m2 of absorber area)) leads to a remarkable 45.66 % increase in yield. Conversely, an equivalent amount (≈ 504 g) of date stones in powder form results in a 29.42 % improvement in yield. Notably, the distillate quality is substantially enhanced in both cases contrasted with the conventional setup.

Optimal design of a combined Power-Heating-Oxygen system for plateau hotel buildings

The Qinghai–Tibet Plateau of China is a region of low atmospheric pressure and oxygen deficiency, with a high heating demand in the winter; therefore, plateau hotel buildings have a demand for comprehensive power-heating-oxygen loads. Solar energy resources are particularly abundant in plateau areas, where a combined multi-energy system based on solar energy can be designed to meet the demand of plateau hotel buildings for multiple loads. However, currently, there is a relative lack of methods for the optimal design and performance evaluation of combined power-heating-oxygen (CPHO) systems. Thus, this study proposes a CPHO system model for plateau hotels, and provides two operation strategies, i.e., power priority and oxygen priority. Taking the minimum total annual cost of the combined system as the optimization objective, an optimized CPHO system model for plateau hotels has been proposed, followed by a case study of a hotel in Qilian County, Qinghai Province. Results showed that: 1) Compared with the conventional combined power-heating (CCPH) system, the CPHO system saw reductions of 0.8% and 1.3% in its total annual cost under the operation strategies of power priority and oxygen priority, respectively. 2) The energy self-consumption (SC) rates of the CCPH system and CPHO system under the operation strategies of power priority and oxygen priority were 84.8%, 64.2%, and 89.8%, respectively; with power self-sufficiency (PSS) rates of 8.3%, 49.9%, and 29.5%, and oxygen self-sufficiency (OSS) rates of 0.0%, 3.2%, and 4.7%, respectively. 3) The total annual cost of the CPHO system was affected slightly by the cost of photovoltaics (PVs) and energy storage devices, and significantly by the price of oxygen. When the price of oxygen was 8 yuan per normal cubic meter(Nm3) or above, the CPHO system was economically efficient under the operation strategy of oxygen priority. When the price of oxygen was 10yuan/Nm3 or above, the system was economically efficient under both operation strategies.

Design, simulation and investigation of the tri-generation process of fresh water, power and biogas using solar thermal energy and sewage sludge

To address the high demand for energy and fresh water, the effect of global warming and pollution generated by fossil fuels consumption needs to be minimized and replaced with alternative renewable energy. Hybrid renewable energy systems using solar energy and biomass will become more crucial. In this study a new design for continuous production process of power, biogas and fresh water is proposed. The challenge of the present research is to use different sources for energy production from renewable resources simultaneously including solar and biomass to produce power, fuel and fresh water, using 4-stage Multi Effect Distillation (MED) for desalination of seawater. To cope with constant and stable energy production required for renewable solar power plants at night, due to lack of sunlight, co-consumption of hybrid solar and biomass feedstocks is considered in this paper. The associated challenge is discussed by the assessments of Solar Heat transfer fluid (SHTF), Sewage sludge flowrates, biogas production, output waste stream of gasification reactor, power and fresh water production using ASPEN Plus software. The sensitivity analysis was performed to demonstrate the viability of the designed process and the resulting products. The gasification process produced 76.8586 tonh syngas (CO and H2). Also, 34.547 MW of power with about 783 m3h of fresh water were produced with the overall exergy efficiency of 35.51 %, 52.260 MW exergy destruction and desalination efficiency of 52 %. Only 25 MW of solar power were necessary due to proper energy recovery throughout the entire process. The productivity of fresh water production was 50 %. 38908 m2 of Parabolic trough collector (PTC) was needed to supply required solar energy during day light hours. It was revealed that the hybridization of solar & biomass energy resources for producing power, fresh water, and biogas could be a sustainable approach to cope with the increasing demand for fresh water, electricity, and fuel.

The development of fishery-photovoltaic complementary industry and the studies on its environmental, ecological and economic effects in China: A review

The fishery-photovoltaic complementary industry is an emerging industrial model in China that integrates aquaculture with the solar industry. This innovative model involves conducting aquaculture activities while installing photovoltaic modules on the water surface to harness solar energy for electricity generation. However, despite its rapid growth in China, this model lacks substantial scientific data support across various domains. Therefore, based on an analysis of relevant research literature, this study reviews the current development status, environmental and economic effects, as well as challenges faced by the fishery-photovoltaic complementary industry in China. The aim is to provide scientific references for promoting sustainable development within this sector. The findings reveal that existing fishery-photovoltaic complementary industry projects are primarily concentrated in the middle and lower reaches of the Yangtze River and Pearl River Basin. The geographical distribution of these projects is predominantly influenced by local aquaculture areas and available solar energy resources, with a greater impact observed from the former rather than the latter. During summer months when water is shaded by photovoltaic panels, a slight decrease in the average water quality parameters across cases was observed, such as a decrease of 0.2 units in pH, a decrease of 1.06 °C in water temperature, a decrease in dissolved oxygen levels of 0.8 mg/L, inorganic nitrogen content and total phosphorus concentration dropped by 0.08 mg/L and 0.02 mg/L respectively. Conversely, there is a moderate increase noted in total nitrogen and ammonia nitrogen levels. The conclusion of the effect on phytoplankton biomass is not uniform, but it will certainly reduce zooplankton biomass. The impact on the species diversity of the zooplankton community was minimal, and its direction, whether positive or negative, varied depending on the specific aquatic ecosystem. A certain degree of shade is advantageous for the cultivation of shade-loving fish. Through the strategic deployment of photovoltaic panels and the implementation of scientific stocking practices, it is possible to achieve sustained levels of fisheries production. This model also can reduce an average of 978.6 tons of CO2 emissions per megawatt per year through energy production, thus achieving the combined goals of energy conservation and emissions reduction, and ensuring the profitability of power generation. Additionally, compared with the land utilization area of 3.66 hm2 per megawatt of traditional ground-mounted photovoltaics, fishery-photovoltaic complementary only requires 1.64 hm2, which can significantly save land resources by utilizing water surfaces, which mitigates the conflict between land use for agriculture and renewable energy installations. At the same time, research also pointed out that the existence of fishery-photovoltaic complementary will inevitably have some negative impacts on bird communities. Economic analyses indicate that while initial infrastructure costs and long payback periods pose challenges, the overall economic feasibility is promising, especially with governmental support and technological advancements. However, several challenges need to be addressed for further development: these include difficulties associated with infrastructure construction and initial costs, long payback periods; insufficient experience and technical support; as well as a lack of research on ecological and environmental impacts - particularly an urgent need for comprehensive life cycle assessments encompassing both environmental and economic aspects. Future research should focus on life cycle assessments, improved PV technology integration, and optimized aquaculture practices.

카자흐스탄의 재생에너지 정책과 발전 잠재력

Expanding the development of renewable energy sources is recognized as one of the most important tasks in terms of responding to climate change and sustainable development. In addition, the increasing instability of the energy supply chain due to the Ukraine war emphasizes the importance of renewable energy in terms of energy security. Kazakhstan, a leading energy exporter among the FSU countries, has been promoting renewable energy development as a national policy for a long time, but has not shown significant results. In this study, Kazakhstan's strengths and limitations in the renewable energy sector, as well as opportunities for development, were examined by evaluating Kazakhstan's renewable energy development potential in three aspects - natural resources, institutions, and technology - with a focus on solar energy. Kazakhstan has relatively abundant solar energy resources, but the technological/industrial level for the development of the solar energy sector appears to be lagging significantly. However, the institutional level related to renewable energy appears to be higher than the world average, and some areas are higher than the OECD average. In order to expand solar energy development in Kazakhstan, cooperation between countries and attraction of investment are needed, which will be an opportunity for Kazakhstan.

Temporal dynamics and extreme events in solar, wind, and wave energy complementarity: Insights from the Polish Exclusive Economic Zone

The Polish Exclusive Economic Zone (EEZ) in the Baltic Sea is an area of increasing strategic importance for Poland's pursuit of renewable energy, especially offshore wind. This research investigates the complementarity among solar, wind, and wave energy resources within the Polish EEZ to examine these energy sources' temporal dynamics, correlations, and extremes. The primary data source corresponds to a 31-year hourly time series dataset from the ERA5 reanalysis, whose reliability was evaluated through performance metrics. The results from complementarity metrics indicate varying levels of association among the three variable renewable energy resources (VRES) in the EEZ, spanning from weak similarity to weak complementarity. The findings of this research indicate that blackouts are most probable at offshore locations during winter and autumn for renewable power systems integrating wind and solar energy, with over 70 % of occurrences within these seasons. The investigation of extreme events highlights critical elements when evaluating VRES and their complementarity. This understanding aids in effectively planning and managing renewable energy systems, ensuring resilience and reliability under challenging weather conditions. Furthermore, while the complementarity may be consistent throughout the entire Polish EEZ, the feasibility and cost of implementing hybrid power systems can significantly vary between locations.

Optimal cooperative scheduling strategy of energy storage and electric vehicle based on residential building integrated photovoltaic

With the development of photovoltaic (PV) power generation technology, more and more families have begun to use solar energy. However, the uncertainty of solar energy production and user electricity demand has brought huge challenges to the development of efficient energy scheduling strategies. To deal with the uncertainty of electricity behavior, Monte Carlo generates the electricity scenario sets based on real data. According to the principle of minimum average distribution error (ADE), the scene with 200 scenes is selected for scheduling. Then, the Transformer model with random error (RE-Trans) is used to predict solar radiation and outdoor temperature. Through verification, it is found that the Mean Absolute Error (MAE) of the former is 0.389 and the Root Mean Square Error (RMSE) is 0.514. The MAE of the latter is 0.212 and RMSE is 0.413. To make effective decisions in the agent with the environment, a Deep Reinforcement Learning model with self-attention mechanism (SAN-DRL) is designed. The model aims to achieve a dynamic balance between electricity costs, carbon emissions and electricity sales income. Through continuous interaction with the environment, the agent finally obtains the optimal disordered charging and discharging behavior of energy storage systems (ESS) and electric vehicle systems (EVs), which greatly improves the utilization of solar energy resources. Finally, through simulation experiments, the proposed method is compared with both the baseline model and the ideal scheduling. The results demonstrate that the proposed method can reduce electricity costs and carbon emissions by 83.72 % and 72.08 %, respectively. Additionally, it achieves a net income of 38.59 CNY.