Annual Power Research Articles

Energy consumption of ultrasound devices during routine applications and opportunities to save energy and costs

Abstract Objective To determine the real energy consumption, including the idle and off-mode status of ultrasound devices and their multiparametric modes during daily examinations. Material and methods In this study, the electrical power consumption from 9 ultrasound devices and 18 probes used in routine medical practice was measured for a full 24 h over a week. The equipment was located in the neurology and cardiology departments of a large hospital, as well as in a radiology medical practice. The devices were manufactured by different companies and varied in age. Results Short-term measurements recorded the electrical power consumption during patient scans, revealing real power values for the applied modalities, which ranged between a mean of 182.5 W and 415.5 W, depending on the device and application field. Long-term measurements, reflecting the typical working days of these departments, showed total annual electrical power consumption ranging from 344.6 kWh to 1122.6 kWh. Energy-saving possibilities are discussed, highlighting that reducing idle-mode durations can significantly lower electrical costs by saving energy of 3–16%. Conclusion This study is the first to document in detail the power consumption of different ultrasound devices and modalities, including idle and off-mode statuses, during routine use. Key Points Question Which procedures during ultrasound examinations have high power consumption and what is the idle- and off-mode consumption of different devices. Findings Energy consumption can vary greatly depending on the application. Savings potentials of 3-16% could easily be realized in the daily routine. Clinical relevance Exact knowledge of power consumption of a device during off-, idle-, and some often-used active-modes (all are easy and fast to perform) can help to optimize examination scenarios and minimize power consumption and thus energy costs. Graphical Abstract

Dynamic modeling and evaluation of a novel evacuated tube solar collectors-assisted supercritical carbon dioxide Brayton cycle with intercooling and reheating

Abstract The transcritical CO2 Rankine cycle is increasingly recognized as a promising option for power generation in low-grade solar applications. However, there is a liquefaction problem in the condenser due to the CO2’s low condensing temperature. It is very difficult to condense CO2 with the surrounding environment or water. Various approaches, such as implementing a self-condensing transcritical CO2 Rankine cycle, utilizing liquid natural gas, or incorporating CO2 mixtures, have been proposed to address this issue, but these solutions add complexity to the system. A more effective and simpler alternative is to adopt the supercritical CO2 Brayton cycle for low-grade applications. In this study, a novel solar energy-based supercritical carbon dioxide Brayton cycle with reheating and intercooling is proposed. For the heating and reheating process, two collector groups comprised of a total of 20 evacuated solar collectors are utilized. The plant is analyzed in terms of energy and exergy, taking into account Isparta, Turkey’s meteorological data. From the analysis, it is determined that the carbon dioxide temperature could reach a maximum of 265.32 °C. The annual solar energy that falls on the solar collector is determined to be 17,697 kWh, while the annual power generation by the cycle is found to be 547 kWh. The results show that the input heat and the net power are greater than 1.5 kW and 0.3 kW, respectively, for most of the year. Moreover, the solar-based supercritical carbon dioxide Brayton cycle’s energy efficiency is calculated as 3.1%, and only the Brayton cycle’s energy efficiency is found as 11.4%. Graphical abstract

The environmental challenge of HPC: finding green power and cooling solutions for supercomputers

In today's world, High-Performance Computing (HPC) is driving scientific research forward at an astonishing rate, but behind every top HPC device lies a high-load power grid, which has sparked deep concern among environmentalists. This study develops a mathematical model to evaluate the power consumption of global HPC equipment and quantify its environmental impact, providing a basis for energy optimization and sustainable development. By systematically analyzing the global environmental impact of HPC through a series of models focused on energy consumption and related emissions, we first created a GPU survival function to estimate the global number of HPC devices in 2023. Using Monte Carlo simulation and Markov chain models, we estimated the power consumption of individual HPC centers under both full load and average utilization conditions, subsequently calculating the total annual power consumption of global HPC centers. Next, we developed models to estimate the total carbon emissions from global HPC energy consumption, considering various energy production methods and energy mix scenarios. Additionally, we created a gray prediction model to forecast the GPU market value in 2030, combining it with the GPU survival function to predict the number of global HPC centers in 2030. We also developed an electricity price fluctuation model to account for increased energy demand from other sectors and analyzed the environmental impact of global HPC centers in 2030 under different energy mix structures. Furthermore, we extended the model to assess the impact of increasing renewable energy (specifically wind energy) to 100% in the energy mix, evaluating its potential to reduce carbon emissions. Finally, we conducted a sensitivity analysis, incorporating seawater cooling for HPC centers and artificial intelligence to dynamically adjust GPU power based on wind speed predictions.

Research on Annual Power Balance and Short-term Optimal Scheduling Considering Abandoned Water Power

With the rapid growth of my country’s new energy installed capacity, the phenomenon of water abandonment, wind abandonment, and light abandonment in the power system has gradually intensified. Especially in areas rich in hydropower resources, the problem of water abandonment is particularly prominent. In order to effectively solve the problem of abandoned water and improve the utilization rate of hydropower, this paper studies the annual power balance and short-term optimal scheduling problem considering abandoned water. Firstly, this paper analyzes the current situation of water abandonment in power system at home and abroad and its impact on power grid operation, combined with the actual operation data of a hydropower station in China, constructs an annual power balance model, and adopts multi-objective optimization method to coordinate and optimize the power balance and water abandonment. The research shows that considering the abandoned hydropower, the waste of hydropower resources can be effectively reduced by reasonable power balance, and the regulation ability and power supply reliability of the power grid can be improved. This paper also combines the optimization algorithm of short-term dispatching to simulate and analyze the dispatching strategy under different load demands and water conditions. The results show that the optimized dispatching strategy can reduce the amount.

A Multifunctional Photothermal Catalyst Enabling Full-Day Sustainable Power and Indoor Air Quality Control.

Solar photothermal catalytic (PTC) purification holds great potential for indoor air pollution control, but efficiently collecting energy at the catalytic interface to maximize solar energy utilization and meet building requirements remains a global challenge. This study develops a novel infrared-light-driven photothermal catalyst, Mn7Co3Ce1Ox, which efficiently utilizes solar and ambient energy, offering three functions: catalysis, heating, and cooling. Furthermore, this study proposes an innovative hybrid system that integrates PTC film, thermoelectric generator (TEG), and metal-organic frameworks (MOFs). Through synergetic effects, the system combines the heating-catalysis-cooling effect of the PTC film with the moisture-induced adsorption/desorption heat of the MOFs, achieving year-round power generation, dehumidification, and air purification. Results show that Mn7Co3Ce1Ox has a full-spectrum solar absorptivity of 94.3% and an atmospheric window emissivity of 95.7%. Under infrared light, the pollutant removal rate on the photothermal catalytic interface reaches 90.9%. Within 4h, the thermoelectric power density increased by 640.1%, the relative humidity decreased by 16.8%, and the clean air volume reached 270.8 m3·h-1·m-2. When the system is applied to building rooftops in 34 provincial capital cities in China, the simulation results show annual power density of 30-105.3 kW·m⁻2, air conditioning energy savings of 11.2-353.5 kW·m-2, and clean air volume of 296.3-1119.3 m3·h-1·m-2.

Optimisation of Dynamic Operation Strategy for a Regional Multi-Energy System to Reduce Energy Congestion

Focusing on the power consumption of a regional multi-energy system with the characteristics of energy congestion in students’ dormitory buildings in the hot summer and warm winter regions of southern China, a practical regional multi-energy system consisting of three subsystems, namely an integrated screw chiller (ISC), a screw ground-source heat pump (SGSHP), and an air-source heat pump (ASHP), was optimised by the operation control strategy. The system’s power consumption and cooling/heating load characteristics during operation were analysed, and changes in the terminal air-conditioning load were simulated. Based on the dynamic cooling and heating load of the building, a two-stage loading strategy was proposed for optimising the system operation. Taking the load demand matching requirement of the system output and the terminal load demand as constraints, a simulation model of the system was developed using TRNSYS 16 software, and the changes in power consumption and the cooling/heating capacity before and after optimisation were analysed. The results show that the optimised system reduced annual power consumption by approximately 19% and increased condensation heat recovery by about 2.3%. The optimised operation control strategy was aligned well with the terminal cooling and heating demands.

Study on offshore wind profile based on neutral equivalent wind speed

To address the issue of extrapolation inaccuracy when the hub height of offshore wind turbines exceeds the measurement height of meteorological masts, this study proposes an offshore wind profile model based on neutral equivalent wind speed by comprehensively considering the Monin-Obukhov similarity theory and sea surface dynamic roughness. First, the effects of wind shear exponent, atmospheric stability, and turbulence intensity on offshore wind resources were investigated. Then, the proposed model was validated using measurement data from an offshore meteorological mast in Dalian. Compared with traditional extrapolation methods, the model yields annual average wind speed and wind power density at hub height that are closer to measured values, with root mean square error and mean absolute error of wind speed being 0.43 m/s and 0.28 m/s respectively. Moreover, the model effectively reflects the influence of sea surface dynamic roughness and atmospheric stability variations on vertical wind speed distribution, overcoming the limitations of conventional wind shear power law. This provides a scientific basis for offshore wind resource assessment and preliminary planning of wind farms

Intelligent building design based on green and low-carbon concept

The integration of modern technology and architectural design in intelligent buildings has led to advancements in functionality and user experience. These developments have also contributed to the pursuit of environmental sustainability, energy conservation, and emission reduction through the implementation of advanced technological systems. Guided by the concept of green and low-carbon, intelligent building design emphasizes the full utilization of renewable energy while utilizing advanced algorithms to optimize energy scheduling in intelligent buildings, achieving green, low-carbon, energy-saving, and emission-reduction goals. Therefore, based on the concept of green and low-carbon, this study optimizes the renewable energy system, lighting control system, elevator control system, and air conditioning control system of intelligent buildings. The experimental findings, utilizing a paradigmatic intelligent office building in Shanghai as a case study, demonstrated that the solar wind complementary power generation system of the building attained an annual power generation of 609,380 kWh. This amount satisfied 60% of the building's electricity requirement, thereby signifying a substantial breakthrough in conventional building energy supply methodologies. The lighting system adopted intelligent time lighting dual-mode control, reducing energy consumption by 10.1%. The optimization of the elevator group control algorithm could achieve an average monthly power saving of 6100 kWh. The air conditioning system reduced energy consumption by 7238 kWh/month through a load forecasting model. The results showed that the intelligent building energy optimization system established in the study, through multi-system algorithm linkage, improved overall energy efficiency by 23% compared to traditional solutions. This method provides a reusable technical paradigm for smart city emission reduction.

Two-phase integrated investment evaluation of clean energy: an empirical analysis of “Photovoltaic+Rice-Wheat” project in China

PurposeThis paper primarily aims to (1) Develop a two-phase investment assessment framework based on the RO method for the PVRW project. (2) Utilize least squares Monte Carlo (LSMC) to simulate how key factors affect the investment value and the best time to invest in the PVRW project. (3) Conduct sensitivity analysis to determine which factors influence the choice of the whole project investment.Design/methodology/approachA two-phase investment evaluation framework for PVRW projects is constructed using RO theory. Compared with the traditional NPV model, this method can accurately evaluate the project value under uncertain conditions and determine the optimal investment time. Incorporating the two-phase uncertainties of PVRW projects and three cooperation investment modes, the optimal investment strategies are provided for investors.FindingsIn the first phase of the PVRW project, while immediate investment under all three operation investment modes can yield returns, it is not the optimal timing. Investors should opt for the cooperative operation mode and delay investment by nine years to achieve the optimal return of 614 m CNY, rather than choosing the independent or lease operation modes. In the second phase of the PVRW project, investors are suggested to transfer to the lease operation mode to achieve the optimal investment value of 1.23 bn CNY for the entire project. Sensitivity analysis results indicate that in both phases of the project, increases in the unit’s initial investment cost and the unit’s O&M cost of the PV system lead to a decrease in the project’s investment value. Conversely, the increase in annual power generation hours enhances the project’s investment value and advances the optimal investment timing. The higher volatility in CO2 prices is shown to slightly increase the project’s value. Agricultural production costs play a significant role in determining investment strategies. When these costs decrease by approximately 32.70%, the independent operation mode is recommended. Changes in agricultural product prices can also lead to a shift in the first phase investment strategy. When agricultural product prices decrease by approximately 7%, investors should transition from Mode 2 to Mode 3 during the first phase.Research limitations/implicationsDue to the long lifecycle of agrivoltaics projects and the variability of meteorological conditions, integrating annual power generation hours into the proposed framework will further promote the effectiveness and accuracy of project investment decisions. Besides, when the operating model is switched from Phase 1 to Phase 2, the conversion costs are not taken into account in the operating costs of the Phase 2 project.Practical implicationsFor the farmers: Given the combined effects of uncertainties, a phased investment strategy that incorporates both leasing and cooperative operation models could be highly advantageous. Additionally, increasing agricultural revenue can strengthen investors’ confidence in long-term project investment in an independent operation mode. Therefore, investors should focus on the potential for enhancing crop yields through technological innovations, such as efficient irrigation systems and crop variety improvements. These measures can effectively reduce risk and ultimately improve the overall investment outcome.Social implicationsFor policymakers: Local governments should prioritize increasing agricultural subsidies or providing incentives to lower production costs. Reducing these costs can indirectly enhance the profitability of agrivoltaics projects and make the independent operation model more attractive to investors. This approach would support sustainable agricultural development while encouraging greater private investment in renewable energy.Originality/valueThis study has proposed a four-stage integrated approach combined with cost-benefit analysis, uncertainty measurement, two-phase real options (TPRO) and sensitive analysis to evaluate the investment of the PVRW project. Based on the case study of the PVRW project in Jiangsu Province, the proposed integrated approach is shown to assist investors in choosing the optimal investment mode for the PVRW project.

Integration of windmills into irrigation systems of agricultural territories: increasing the efficiency of water use and sustainability of agrarian ecosystems in the Saratov region

The paper considers the integration of wind generators into irrigation systems of agricultural areas as a way to improve energy and water efficiency. Particular attention is paid to the Saratov Oblast, which has favorable wind resources and a significant need for sustainable irrigation technologies. Calculations of capacity and annual power generation by wind turbines installed in different areas of the region, including Balakovo, Volsk and Engels districts, are presented. The economic feasibility of the project is shown, including payback periods and annual electricity savings. The results of the study demonstrate that the use of wind generators to power pumping stations can reduce water use costs and increase the sustainability of agro-ecosystems through the use of renewable energy sources. It was found that Balakovo district is the most promising in terms of wind potential and minimum payback period (2.9 years). The obtained conclusions emphasize the importance of integration of modern technologies in the agricultural sector to achieve environmental and economic sustainability.

Optimal configuration of islanded microgrid capacity considering energy utilization and power supply reliability

Abstract The inherent periodicity, randomness, and volatility of renewable energy sources such as ocean energy pose substantial challenges to the energy supply stability and self-sufficiency of isolated island microgrids. This paper aims to determine the optimal capacity and evaluate the techno-economic benefits of independent microgrids on remote islands in the East China Sea. Specifically, considering a hybrid energy microgrid system comprising photovoltaic panels, wind turbines, marine power generation devices, battery energy storage systems, and diesel generators. The optimal configuration of this model is determined using an enhanced sparrow search algorithm, with constraints ensuring stable microgrid operation and maximizing the utilization rate of renewable energy resources. The objective is to achieve the lowest annual comprehensive cost. The results of the example verify that the improved algorithm optimizes the microgrid configuration and controls the renewable energy reduction rate and annual power shortage rate at 1.93% and 2.42%, respectively.

Research on the Position Optimization of Tower Solar Heliostat Field Based on Optical Efficiency

Tower solar thermal power generation technology has multiple advantages such as high efficiency, environmental protection, rich resources, and economic feasibility, which is an important part of clean energy development. However, the power efficiency of tower solar thermal power generation system has obvious fluctuation and instability due to the arrangement mode, the size of each mirror and the distance between them. In the heliostat field, if all the heliostats have the same size and installation height, how to determine the location of the absorption tower and the location and size of the heliostat to maximize the annual average heat output per unit mirror area is a problem to be solved. The Campo layout is first used to generate the dense heliostat field as the initial mirror field before optimization. The optimized arrangement of the Campo layout is obtained by changing the distance between the heliostat and the central absorption tower and the distance between the heliostat and the adjacent heliostat. Secondly, the position coordinates of the initial absorber and the size of the heliostat were taken as decision variables. Taking the actual situation and the comprehensive efficiency of the heliostat field as the basic constraints, the constraint of the number of the heliostat is further analyzed. The optimization model was established by taking the formula of annual average thermal power output per unit mirror area as the objective function. In the Campo layout, the adaptive gravitational search algorithm is used to solve the experiment, and finally the relevant parameters under the optimization arrangement are obtained, which maximizes the annual average thermal power output per unit mirror area when the helostat field reaches its rated power.

Feasibility and case studies on converting small hydropower stations to pumped storage

Hydropower, as a controllable energy source, plays a crucial role in supporting essential functions such as peak shaving, frequency regulation, and load reserve within modern power systems, thereby enhancing the overall economic efficiency and safety of these systems. This study utilizes data from small hydropower stations and advanced software algorithms to preliminarily evaluate the feasibility of converting conventional small hydropower stations in Zhejiang Province into pumped storage hydropower stations, with the province serving as the focal research area. Through comprehensive analysis and field investigations, Jiangshantou Hydropower Station has been selected as the pilot site for this conversion initiative. The proposed conversion scheme has been assessed, and predictions regarding annual operating hours, power generation, and energy consumption have been formulated. The analysis indicates that Jiangshantou Pumped Storage Hydropower Station will serve as the primary mechanism for power regulation. Furthermore, a small-scale integrated hydropower-wind-solar power system is proposed to ensure stable system output, improve the input-output ratio, and enhance the efficiency of renewable energy utilization.Optimal locations for development have been identified, including a 6-hectare photovoltaic installation situated approximately 3.5 km from the dam, alongside a nearby elevated site suitable for wind energy generation. Tools such as SolarGIS and the Global Wind Atlas were employed to assess the solar and wind resources in the area, revealing that the site possesses abundant and stable solar resources, as well as favorable indicators for wind energy, making it an ideal candidate for photovoltaic and wind energy development. This research establishes a comprehensive framework for the conversion of conventional hydropower stations into pumped storage facilities, offering a model for medium-small scale pumped storage and distributed generation technologies. It is recommended to implement photovoltaic forecasting systems at the PV site to achieve more precise control over photovoltaic output and enhance the responsiveness of the pumped storage station to fluctuations in solar power.

Investigation on the Design of High‐Performance Photovoltaic Roof System With the Efficient Luminescent Solar Concentrator

ABSTRACTIn this study, we have fabricated the efficient luminescent solar concentrators (LSCs) with the chemical raw materials of B2O3–SiO2–ZnO, Cs2BIBIIIX6, and copper‐based halide, and after integrating with the silicon‐based solar cell, the optoelectronic conversion efficiency of this device with the area of 32 × 32 cm2 could achieve the high value as 10.89%. Due to the high absorptance and transmittance of LSCs, these devices are very suitable for the application of building integrated photovoltaic (BIPV). A simulation model of the photovoltaic roof system was constructed with PVsyst software by using the 32 × 32 cm2 LSCs as the basic unit. In addition, the performance of photovoltaic roof systems with varied string structures, assembled angles (0° and 30°) and operating status of LSCs are explored, these results indicate that the best string structure of the LSCs working at different operating status. Moreover, the annual power generation capacity of the photovoltaic roof system assembled at 0° could achieve 22,152 kWh, which is 4.70% higher than that of the photovoltaic roof system assembled at 30°. These results could give a reference for the practical construction and optimization of BIPV.

A simplified evaluating model on building external sun-shading devices by demonstrated simulation for designers

ABSTRACT The complex evaluation of sun-shading device regulation has obstructed the promotion of energy-saving building design. This study explored the benefits of installing external fixed shading to reduce indoor heat gain in office buildings in Taiwan. By creating an office building model and incorporating simulation factors such as climate zones, window-to-wall ratio, external shading forms, and shading depths, the annual air-conditioning power consumption of the building model was estimated using the energy simulation software, eQUEST. A table listing the benefits of installing external fixed shading to reduce air-conditioning power consumption and regression formulas for air-conditioning power consumption density were proposed. These can assist architectural designers conveniently evaluating the energy-saving efficiency of buildings using external sun-shading devices during the planning process. The results indicate that under the same shading depth, the energy-saving benefits of installing lattice shading are greater than those of horizontal shading. The simplified evaluation model would greatly enhance the promotion of energy-saving building design.

Investigation of sea current velocity and power potential in the North Aegean sea

This study aims to assess the marine hydrodynamics and the potential power of sea currents by simulating the probability distribution functions of the sea current velocity values. For this aim, hourly sea current velocity and direction data measured from the Çanakkale (Turkey) measurement station in the North Aegean Sea were used. These data were measured during two separate periods: January 1 – March 24, 2017, and March 25 – December 31, 2019. First, the vertical structure of the sea currents up to 50 m depth was determined. Then, frequency distributions of hourly sea current velocities were modeled by using the Weibull, Rayleigh, and Exponential probability density functions. According to the results obtained at 5, 10, 20, 30, 40, and 50 m depths below the sea surface level, the annual sea current velocity was 28.8 ± 0.395, 26.1 ± 0.388, 19.4 ± 0.339, 16.1 ± 0.324, 17.5 ± 0.344, and 24.7 ± 0.622 cm/s, respectively, in this sea. Furthermore, the annual sea current power potential was calculated as 30.0, 25.4, 15.0, 12.2, 15.0, and 88.2 W/m2 for 5, 10, 20, 30, 40, and 50 m depths, respectively. The results demonstrated that the Weibull distribution model was the best fit for the sea current velocity in this sea.

A Stochastic Process-Based Approach for Power System Modeling and Simulation: A Case Study on China’s Long-Term Coal-Fired Power Phaseout

Power systems hold huge potential for emission reduction, which has made the modeling and pathway simulations of their decarbonizing development a subject of widespread interest. However, current studies have not yet provided a useful modeling method that can deliver analytical probabilistic information about future system behaviors by considering various uncertainty factors. Therefore, this paper proposes a stochastic process-based approach that can provide analytical solutions for the uncertainty ranges, as well as their changing momentum, accumulation, and probabilistic distributions. Quantitative probabilities of certain incidents in power systems can be deduced accordingly, without massive Monte Carlo simulations. A case study on China’s long-term coal-fired power phaseout was conducted to demonstrate the practical use of the proposed approach. By modeling the coal-fired power system at the unit level based on stochastic processes, phaseout pathways are probabilistically simulated with consideration of national power security. Simulations span from 2025 to 2060, presenting results and accumulated uncertainties for annual power amounts, full-process emissions, and carbon efficiencies. Through this modeling and simulation, the probabilities of China’s coal-fired power system achieving carbon peaking by 2030 and carbon neutrality by 2060 are 91.15% and 42.13%, respectively. It is expected that there will remain 442 GW of capacity with 0.18 Gt of carbon emissions in 2060.

Global optimization of photovoltaic tilt angles: reducing solar power losses using reanalysis data

Abstract Solar photovoltaic (PV) systems play a crucial role in addressing the growing demand for clean energy and mitigating climate change impacts. However, PV system performance is heavily influenced by the incident solar radiation on panel surfaces, with suboptimal tilt angles leading to significant power losses. Despite the critical importance of tilt angle optimization, many existing PV installations worldwide operate suboptimally due to simplified estimation methods or lack of site-specific optimization. This study presents a novel hybrid approach combining empirical and computational methods to determine optimal annual and monthly PV panel tilt angles using long-term hourly ERA5 reanalysis radiation data. Our results validate the effectiveness of ERA5 data for global tilt angle optimization, demonstrating a strong correlation with established cubic relations. Analysis of spatial and temporal patterns of optimized tilt angles reveals the influence of latitude, local atmospheric conditions, and seasonal variations on optimal PV panel inclination. A comprehensive assessment of the global PV inventory in 2018 shows that 44.6% of installed capacity is located in regions with solar power losses exceeding 1%, resulting in a total loss of 6154 GWh yr−1—equivalent to Luxembourg’s annual electricity consumption. Comparison between optimized tilt angles and those estimated using empirical cubic schemes reveals significant discrepancies in some regions, with annual power losses surpassing 3% when using empirical methods. These findings underscore the importance of accurate, location-specific tilt angle optimization to minimize solar power losses and maximize global PV inventory performance. Our research highlights the potential for substantial energy yield improvements through widespread adoption of optimized tilt angles in PV system design and retrofitting, contributing to enhanced renewable energy production and accelerated progress towards global sustainability goals.

Comparative analysis of building-applied and building-integrated photovoltaic system performance utilizing c-Si, CIS, and CdTe technologies in rural residences applications in cold regions of China: A case study in Xuzhou

With the intensification of the global energy crisis, the application of photovoltaic (PV) technology in the field of architecture has gradually become an important direction for sustainable building design. Especially in cold regions, how to choose the right photovoltaic technology and system type to improve energy efficiency is one of the current research hotspots. This paper investigates the performance of building integrated photovoltaics (BIPV) and building applied photovoltaics (BAPV) systems, as well as different photovoltaic (PV) technologies (including c-Si, CIS, and CdTe), for rural residences in cold regions. The study uses a representative rural residence in Xuzhou, China, as the benchmark model, with the installed capacity of the PV system set at 9.0 kW p. By evaluating key performance parameters, including annual power generation, yield factor, performance ratio, and system losses, the study provides a comparison of the BAPV and BIPV systems with different PV technologies. The results reveal that the c-Si-based BIPV system exhibits the lowest annual power generation and performance ratio, with the highest losses. In contrast, the CdTe-based BAPV system performs the best in terms of annual power generation and performance ratio, while also demonstrating the lowest losses. Overall, among these two systems, the BAPV system surpasses the BIPV system in overall efficiency; and at the technological level, CdTe technology outperforms both CIS and c-Si technologies.

Layout analysis for floating offshore wind farms considering wake interference

Offshore wind farms have been gradually developed as deep-sea and large-scale farms in search of abundant and stable wind energy. Compared with fixed wind farms, floating offshore wind farms require additional consideration of wave loads, cable loads, and platform motions. To accomplish a fast and accurate simulation of floating wind farms, a coupled analytical model is proposed in this paper. This model couples platform motions, wake interference, single turbine dynamics, and wind farm modeling. The performance of wind farms with different layouts is simulated and compared, and the turbine spacing and wind farm layout angle are optimized. By studying an 80 MW floating wind farm in a certain sea area, it is found that a reasonable layout angle can improve the overall wind farm efficiency and increase the annual power generation by up to 3.61 GW h per year (1% improvement).