Electrical Energy Demand Research Articles

Evaluation and Optimization Based on Exergy in Kamojang Geothermal Power Plant Unit 3

The quality of production well from the Kamojang geothermal power plant unit 3 diminishes annually, whereas there has been a substantial rise in the demand for electrical energy in the region. This research focuses on optimizing the vacuum pressure in the main condenser by employing exergy analysis, a methodology grounded in the principles of the second law of thermodynamics. Exergy analysis offers insights into each system component's exergy efficiency and irreversibility. Furthermore, an energy assessment is conducted to offer insights into each component's energy consumption or utilization. Energy and exergy rates are computed for every state and component within the power plant, encompassing the steam receiving header, separator, demister, turbine, main condenser, inter condenser, after condenser, and cooling tower. The exergy analysis findings reveal that the exergy rate derived from the production well amounts to 95327 kW, generating 52882 kW of electricity and producing a system exergy efficiency of 55.47%. The turbine experiences the highest irreversibility, totaling 12874 kW. Adjustments are made to the main condenser vacuum pressure to optimize the system, aiming to identify the optimal setting that maximizes both exergy efficiency and power output. The optimization outcomes indicate that reducing the vacuum pressure in the main condenser leads to enhanced exergy efficiency and increased power output. The optimal vacuum pressure obtained is 0.1 bar, resulting in the highest exergy efficiency and output power of 57.42% and 54738 kW, respectively, with the lowest irreversibility of 32751.07 kW.

KAJIAN EKONOMI PEMANFAATAN PLTS ATAP DI GEDUNG RUMAH JABATAN GUBERNUR PROVINSI BALI

To meet the high demand for electrical energy, an alternative solution that can be applied is the use of New and Renewable EnergyIndonesia targets to achieve Net Zero Emissions (NZE) by 2060. Planning for a rooftop PLTS at the Office of the Governor of the Province of Bali is expected to be able to assist in the expansion of PLTS in the Province of Bali in terms of strengthening Governor Regulations/Regional Regulations that support the use of Solar Power Plants. The design of the rooftop PLTS at the Bali Province Governor's Office Building was carried out using 4 scenarios. Scenario 1 is a design that utilizes the roof area facing the north side. Scenario 2 is by utilizing the roof area only to meet the peak load of the building. Scenario 3 is a design that utilizes the entire roof area of the building that best meets the criteria. Meanwhile, scenario 4 is scenario 2 but uses a microinverter device. The Scenario 2 PLTS design is studied economically because the return on investment is the fastest compared to the other scenario PLTS designs. Based on the economic feasibility analysis of the investment, scenario 2 design has a Net Present Value (NPV) of Rp. 158,771,001, Profitability Index (PI) of 1.32 and a Discounted Payback Period (DPP) of 10.7 years.

A COMPARATIVE STUDY ON GRID ENERGY AND RENEWABLE SOLAR ENERGY SYSTEM

Solar energy is one of the most abundant energy resources on Earth. It is a renewable energy resource that can provide suitable power for our needs. It’s also continuously growing in popularity nowadays since it can provide significant benefits to human and environment. The use of solar energy is a great way to contribute to a cleaner future. This renewable resource is a clean and safe alternative energy solution that can help reduce the production of harmful pollution. Hence, utilizing solar power can be an excellent way to fight climate change and help reduce your home’s carbon footprint. It is also necessary to look into as day by day the demand for electrical energy is increasing. We can't rely on conventional energy sources for meeting this increasing demand as they are depleting. So it is necessary to find an alternative method to harness the energy that we are lacking. Solar energy generation seems to be a promising technology for this dilemma. It is environmental friendly and infinite source of energy. Photovoltaic systems can be broadly classified into two-an on-grid system or an off-grid system. The energy generated from a solar PV system is based on several factors like irradiance, types of solar PV used and temperature. Analysing the existing system efficiency is of prime importance for the characterization of the problems and for the improvements. This study deals with the performance analysis of an on-grid and off-grid system. The analysis is carried out by modelling an existing system in MATLAB/SIMULINK which is already in operation. It can be extended to analyse the grid stability. This study aims the quantification of various performance parameters like power output, losses in the system, system efficiency and the total energy transfer.

Design and Performance Analysis of an Air-Based Photovoltaic/Thermal Collector in Winter

The most basic needs of the buildings in which we spend almost all of our time are electricity and heat demands. Especially in cold climatic regions, it is very important that both electrical energy and heating energy demand are met through the same system. The use of photovoltaic (PV), is increasing rapidly. Photovoltaic panels can transform solar energy into electrical energy with less than 20% performance. Photovoltaic-thermal(PV/T) collectors which can be mounted on facades of buildings or used as building envelopes, are one of the solar energy applications. With this collector, both electric energy and thermal energy demand is produced from solar energy. In our work, Photovoltaic panel and some kind of solar air collector have been taken into consideration. In order to determine the behavior of the air-based photovoltaic-thermal collector, an experimental setup and a measurement system have been established. The experimental setup consists of this measurement system, sensors that obtain data, and a data storage unit that can transmit temperature, humidity, and radiation data to the computer at the desired frequency. In order to determine the performance of the air-based PV/T collector, the efficiencies of both the PV and the solar air collector were calculated separately. To determine the performance of this collector, calculation criteria’s and model has been determined. When creating this model, the problem has been considered as time-dependent under irregular conditions. The theoretical analysis model, which was established to determine the performance of the air-based PV/T collector, was evaluated according to the winter climatic conditions of Izmir-Turkey.

Feasibility of supplying electrical energy demands with off-grid hybrid renewable systems to supply a small hotel in the desert

<p align="justify">Considering the world’s ever-increasing need for energy, as well as the limited resources, pollution, and climate change caused by fossil fuels, it shows the necessity of using renewable energies more than ever. Iran has many tourist attractions. It is difficult to supply energy to welfare places in some of these areas due to the long distance from the city or the vulnerable environment, so their energy supply system is designed independently of the grid. Using a diesel generator to supply electricity can be considered the first solution for a hotel’s off-grid system, but this scenario has high costs and causes pollution. The second way is to use renewable energies such as wind and solar, but these energies are not stable due to weather conditions. One suggestion to overcome the periodicity of renewable energy sources such as the sun and wind is to develop a hybrid energy system in which excess electrical energy can be converted and stored. These resources, together with energy storage, can provide a system with better reliability that is suitable for off-grid applications. In the third case, the diesel generator can be combined with renewable energy. In this article, the electricity supply is for a small hotel with an area of 3995 m<sup>2</sup> located in the Varzaneh desert of Isfahan province. The average electrical load required is 1530 kWh/day, and the peak load is 118.76 kW. The simulation of the system has been done with HOMER software, and the results have been categorized based on the three scenarios mentioned as well as the total net present cost of the system. With the obtained results, it is clear that the most optimal system is one with a combined supplier of a diesel generator, a photovoltaic panel, a wind turbine, and battery storage. The NPC value of this system is $1,995,016; the renewable rate is 87.1%; and its emissions are 84% lower than in the case where only the diesel generator supplier has them.<strong><em></em></strong></p>

Biomass and bioenergy potentials of bioresidues: assessment methodology development and application to the region of Lafões

AbstractBioenergy research aims to uncover the potentials of biological residues. Regional-specific characterization of such potentials is needed to improve the use of local resources, decisions on bioenergy conversion routes, and services within global efforts against climate change. The definition and calculation of the theoretical and technical biomass and bioenergy potentials are keys for developing sustainable use pathways at a regional level. The present work develops a methodology where theoretical framework, quantification methods, and values for the necessary parameters, to assess regional biomass and bioenergy potentials, are considered. The region of Lafões (Portugal) is the case study to illustrate the application of the methods, resulting in three bioresidue categories (agricultural by-products, forestry residues, and municipal waste) and two bioenergy conversion routes (biochemical and thermochemical). The biochemical conversion route revealed a technical energy potential of 765 TJ yr−1, comparing favourably with the 543 TJ yr−1 achieved by the thermochemical route. Also, the environmental and economic performances, associated with the implementation of bioenergy technologies, are possibly better achieved through the biochemical route, to be assessed through life cycle analyses and life cycle costing. Regardless of action priorities, the two conversion routes combined can potentially cover the entire current electrical energy demand of the region. This should also be appraised with expectations in mind for both flexible bioenergy services (with other renewables) and for bioenergy usage in applications which are difficult to defossilize.

STUDI POTENSI PLTS ATAP DI MAKASSAR UNTUK MENINGKATKAN PENGGUNAAN ENERGI TERBARUKAN DAN MENGURANGI EMISI KARBON

Indonesia is located below the equator and has high exposure to sunlight throughout the year, providing great potential for generating electrical energy from solar sources. The demand for electrical energy in Indonesia continues to increase every year, so that it is very important to take advantage of the abundant potential of solar energy to become a source of renewable energy for power generation. This study focuses on analyzing the potential and effectiveness of using solar power and the challenges in its use, especially in the Makassar area. Solar power can generate up to 112,000 GWp of electricity or the equivalent of 89,600,000 MW. One of the challenges faced in using solar panels is the high material and installation costs, as well as people's dependence on conventional electricity. The Indonesian government has set a target to obtain 23% of the total electricity capacity from renewable energy sources by 2025. One solution is to use a rooftop solar system which can directly convert solar radiation into electrical energy. The energy generated from the Rooftop PLTS system can be stored in a battery that is controlled by a regulator and used at night. The use of on-grid PLTS or Rooftop PLTS can provide the advantage of saving PLN's electricity by 39.9% to 110.5%. It can be concluded that using energy from solar panels in a month can produce carbon gas emissions by 3.3% or carbon gas emissions are reduced by up to 96.7%.

Battery electric vehicle energy demand in urban energy system modeling: A stochastic analysis of added flexibility for home charging and battery swapping stations

The successive upsurge in the penetration rate of battery electric vehicles (BEV) in the transport sector stresses electricity grids. Concurrently, batteries in BEVs add flexibility, while the reintroduction of battery swapping stations challenges home charging with regards to added flexibility. To address research gaps regarding the role of BEV charging systems in urban decarbonization pathways, this paper introduces an innovative modeling approach that reflects the implications of home charging and battery swapping stations in urban environments and accounts for the stochasticity of vehicle use.The developed method is demonstrated using a case study that comprises a sample residential area equipped with rooftop PV. The comparison of home charging and battery swapping stations shows that both approaches allow significant increases of self-consumption of locally provided electricity over conventional opportunistic home charging, with battery swapping stations evincing the highest increase in flexibility. This increase in added flexibility might, however, not justify a system-wide introduction of battery swapping stations for BEVs, as required surplus batteries and industry-wide standardization entail added efforts over home charging.Policy recommendations derived by this work support building regulations regarding the installation of charging stations and the utilization of PV rooftop potentials considering the anticipated market penetration of BEVs and the possibility to share electricity within local energy hubs.

POTENSI LOGAM TANAH JARANG DI DALAM ABU BATUBARA

Coal is a fossil fuel that is still used as fuel for Steam Power Plants (PLTU). The greater the demand for electrical energy, the greater the need for coal to meet the fuel needs of the PLTU. The combustion of PLTU produces combustion residue in the form of fly ash and solid ash. Fly ash has its own problem level compared to solid ash. The issue of air pollution, sources of disease and radioactive pollutants are the negative impacts of fly ash left over from burning coal. Coal ash is formed from compounds that do not burn in the coal combustion process including the presence of rare earth metals (LTJ). LTJ is a valuable element which in certain levels can be processed into valuable goods. Separation of LTJ in coal can reduce the ash content and improve the quality of coal, so it is necessary to know the potential of LTJ contained in coal ash. The coal sample tested was coal from PT Bukit Asam Tanjung Enim Mining Unit. Identification of LTJ elements in the ash at the PLTU using XRD, ICP and SEM analysis. There is element Cerium (Ce) 55.3 ppm in fly ash and 22.6 ppm in bottom ash, element yttrium (Y) 36 ppm in fly ash and 10.7 ppm in bottom ash, element Lanthanum (La) 27.3 ppm on fly ash and 10.5 ppm on bottom ash. Neodymium (Nd) 26.1 ppm in fly ash and 6.9 ppm in bottom ash. Finally, there is an element of Samarium (Sm) 1.4 ppm in fly ash and 0.7 ppm in bottom ash. There is a promising potential for rare earths in coal ash, but for levels below 500 ppm it is still not feasible to manage, so it is necessary to enrich the rare earths first.

Electricity Energy Demand in Banjarnegara District for the Year 2021-2030 Using Linear Regression Method and Leap Software

Electricity demand is expected to increase from year to year. Central Java's electricity demand in 2013 reached 18.205 GWh with a total of 8.092.964 customers. This energy demand has increased in 2018 to 22.945 GWh with a total of 10.011.388 customers. Continuous use of electricity, both directly and indirectly, will also affect economic needs and people's welfare. It is estimated that electricity sales will continue to increase in line with the growth of customers who will also continue to increase. In predicting the need for electrical energy, various forecasting methods are commonly used to predict the need for electrical energy, such as the Regression Method, Time Series Method, Causal Method, Neural Network Method, and Dynamic System Analysis Method. In predicting the need for electrical energy there are advantages and disadvantages of the forecasting method. Based on the availability of data, this research analyzes forecasting the demand for electrical energy in Banjarnegara district using the regression and time series method which is applied using LEAP software. The results show that the total demand for electrical energy using the regression method in 2030 will reach 50.616 GWh while the LEAP software in 2030 will be 59.677 GWh.

Fault Detection on Power Transmission Line Based on Wavelet Transform and Scalogram Image Analysis

Given the massive increase in demand for electrical energy, particularly owing to global climate change and population expansion, as well as the development of complicated electrical systems due to the urgent need for a sophisticated component to enhance power delivery, it becomes important to adopt a smart and contemporary approach that is also appropriate for the aim of protecting transmission lines (TLs) and ensuring the continuous delivery of electric power to customers. Consequently, a unique and highly reliable approach for identifying faults in TLs is presented in this work, which employs Wavelet Transform and is evaluated using Matlab simulation. Wavelets of various kinds were utilized to demonstrate their dependability. Furthermore, utilizing this approach has shown itself to be highly successful and has yielded spectacular results even when it is used on a complicated electrical network. Moreover, many types of faults were presented and afterward evaluated and verified for the network in various settings, which also demonstrated their potential to recognize faults within a relatively short space of time. This innovation will alter the idea of fault detection by providing a complete and integrated model for detecting faults in a TL, and it may be regarded as a revolution in the renewal of core principles in TL protection.

Wind Energy Assessment Using Weibull Distribution with Different Numerical Estimation Methods: A Case Study

The demand for electrical energy is increasing every day, which is one of the critical challenges facing the world today. Hence, the necessity of turning to clean renewable energy sources that are not harmful to the environment as an alternative to the traditional generation based on fossil fuels has become more important than ever before. Wind power is one of the renewable sources that provides a clean solution to generate electricity. In this context, the Kingdom of Saudi Arabia announces renewable energy projects to generate 9 GW from wind in 2032. Hence, the aim of this paper is to investigate the most suitable method of Weibull parameter estimation in order to predict wind characteristics and employ it for wind energy assessment in the Qassim region located in the center of the country. In this study, wind data is collected from NASA's forecasts of global energy resources for 2010–2015 based on their availability at altitudes of 10m and 50m and analyzed by using six different methods for Weibull parameter estimation: the graphical method (GM), standard deviation method (SDM), energy pattern factor method (EPF), moment method (MM), alternative maximum likelihood method (AMLM), and novel energy pattern factor method (NEPF). The efficiency of each method is tested by calculating the root mean square error (RMSE) and the relative wind power density error (RPDE). The comparison shows that the most appropriate method for estimating wind power density in the country is the Moment Method (MM), with the lowest RPDE ratio equal to 0.2018%. It has been found that the wind power density in the Qassim region falls into the class 1 category, as it is less than 100 W/m2 at a height of 10m and less than 200 W/m2at an altitude of 50m. The results show the region is only suitable for small off-grid projects. Doi: 10.28991/ESJ-2023-07-06-024 Full Text: PDF

Short-term Electric Energy Load Forecasting of Ankara Region Using Artificial İntelligence Methods

While energy, which is an indispensable part of everyday life, maintains its importance and place in socio-economic structures of countries, importance of electricity energy, as an important component of energy, is increasing its gravity exponentially. Importance of electricity energy demand maintains its increasing trend in line with growing population, urbanization, industrialization, becoming widespread of technology and welfare. While meeting electricity energy demand, correct and effective load forecasting is needed in order to ensure operational safety without losing the stability of voltage, frequency and power flows within the limits determined under the real time conditions of electric power systems, operate and plan secure and low-cost electricity transmission systems and supply sustainable, reliable, high quality and affordable electricity to consumers. In recent years, use of the artificial intelligence models are quite common in many areas of the power system analysis and control, static and dynamic security analysis, dynamic load modelling and alarm processing and error diagnostics. Therefore, in this study, hybrid artificial neural network model optimized with genetic algorithm has been proposed to perform short-term load forecast since fairly good forecasting results are being obtained especially for non-linear complex problems. The proposed short-term load forecasting model has been tested by making 24 hours load forecasting using actual load data of Ankara Region in Turkey. The results obtained from the proposed model have been compared with classical ANN. In this study, for short-term electric load forecasting based on artificial neural networks and genetic algorithm an adaptive hybrid system has been proposed. Using artificial neural network based on Genetic Algorithm (GA) a new approach for short-term electric load forecasting has been developed. This proposed hybrid algorithm has been implemented for short-term load forecasting. In the proposed model, the actual forecast was made by ANN, Genetic Algorithm is used to select the most appropriate activation function for each node of ANN. Thus, it has been observed that network error decreased even more than classical ANN. The results show that hybrid ANN gives better result than classical ANN. So, the accuracy of the proposed model for short-term load forecasting has been increased. These results showed that the proposed model has a higher accuracy rate than the classical ANN in the short-term load forecasting.

Power-to-liquid versus biomass-derived kerosene: a comparative study

Power-to-Liquid (PtL) kerosene is considered by many experts as the only viable option to achieve a large scale decarbonization of the aviation sector in the near-medium term. In the PtL process carbon dioxide of renewable origin or from ambient air and green hydrogen are combined to produce a liquid fuel that can replace fossil kerosene. For this purpose the Fischer-Tropsch pathway and the methanol pathway are available. On the other hand, more production pathways are available when using a biomass feedstock. The aim of this work is to compare the power and biogenic routes for the production of sustainable kerosene in terms of performance and requirements. Indeed, there is a lack of studies in the literature that directly compare the two options, i.e. biofuels and e-fuels, on a common basis. Accordingly, simulation models are built in this work for both routes to calculate the yield of kerosene and co-products, the hydrogen demand, the flows of carbon dioxide, the electricity and thermal energy demands. The simulation outputs are compared against the results of the relevant studies in the literature. The expectation from this comparative study is to highlight the criticalities of each route and, possibly, any opportunity to overcome them by exploring any synergy between the different routes.

Monitoring and control of IoT-based building electrical load limit

The Demand for electrical energy continues to increase. However, excessive electrical energy consumption can lead to tripped circuits and escalated costs. We developed a prioritised sockets system to avoid electrical trips and excessive power consumption. The PZEM-004T sensor in the master circuit can measure electrical power with deficient error, and the ACS712 sensor in the slave circuit can measure electrical current with an accuracy of 99.85%, making these sensors suitable for monitoring. Additionally, the non-priority sockets can interrupt the power flow when the power exceeds the limit while the priority socket remains active. The mobile application can display real-time historical data and control the switching of prioritised sockets. This system consists of 3 subsystems: the master circuit, the slave circuit, and the mobile application. The priority socket’s current cannot be interrupted. In contrast, the non-priority system can be interrupted when the electrical power load reaches 375 Watts. The mobile application controls the switching of prioritised sockets and monitors the incoming electrical power loads. They connected this system to the internet for proper functioning.

Decarbonisation pathways of the cement production process via hydrogen and oxy-combustion

Decarbonising cement production is of profound importance for meeting global greenhouse gas emission reduction targets and mitigating the impact of climate change. This study evaluates various technical options for achieving deep decarbonisation in a clinker production facility by utilising hydrogen (H2) as an alternative fuel to replace fossil fuels and by integrating an oxy-combustion technique with carbon capture and storage (CCS). Using Aspen Plus process simulations, we examined the extent of decarbonisation and assessed the thermal and electrical energy demands. This was achieved by incorporating an amine-absorption-based CO2 capture to a conventional natural gas fuelled reference plant, implementing oxyfuel-combustion of natural gas, and exploring four different scenarios for replacing fossil fuel with H2. In these scenarios, H2 was assumed to be produced through on-site water electrolysis, which also supplied oxygen for oxyfuel combustion, potentially eliminating the need for an air separation unit (ASU). The processes utilizing H2, except for the case of indirectly heated pre-calcination, employed oxyfuel combustion. The results indicate that the natural gas-fuelled oxyfuel-combustion process had the lowest total energy input at 4.92 GJ/t clinker, approximately 35% lower than that of the reference plant. Processes using H2 reduced energy demand by 11% in the H2-d scenario and 33% in the H2-a scenario. However, the process with indirect calcination required 6.24 GJ/t clinker, about 8% more H2 fuel than direct calcination but helped eliminate the need for an ASU. The results also reveal that greater H2 substitutions led to higher total process energy requirements due to the inefficiencies of the electrolysis process. While the H2-using processes could reduce the CO2 generation by up to 559 kgCO2/t clinker, this represents only about 27.6% of the CO2 reductions relative to the reference plant. These findings underscore the limitation of fuel substitution alone in cement production and emphasize the need for innovations in raw materials and the adoption of CCS to achieve deeper decarbonisation in cement industries.

Analysis of Electrical Energy Consumption in Office Buildings of the Institute Technology of Sumatra in Energy Conservation and Efficiency Efforts

Electrical energy is one of the basic human needs in carrying out various activities or daily activities, especially in office buildings such as office buildings of state higher education institutions, namely the Sumatra Institute of Technology (ITERA). Office buildings are the third highest consumer of electrical energy after shopping centers and hotels. The high demand for electrical energy requires the user sector to make efficiency in energy use. Before making efficiency, it is necessary to know the profile of electrical energy consumption including energy consumption intensity (ECI) and significant energy users. Therefore, in this study, an analysis of electrical energy consumption in each ITERA office building was carried out, through observation and interviews according to SNI / ISO 50002: 2018 energy audit procedures. The results obtained show that the total energy use of the 6 largest buildings (A, B, C, D, E, and F) in May 2023 is 144768 kWh and from the calculation of the ECI value is in the very efficient category (7.44 kWh/m2/month). From 6 existing buildings, there are 3 buildings that are very efficient, 1 building is efficient, and 2 buildings are quite efficient. Then, significant energy users were found by 83% in building C AC. Recommendations for saving energy in the effort of energy conservation and efficiency that can be done include, making changes in habits / patterns of use of electrical energy user equipment, especially in air conditioners and dispensers, so as to save electricity 2-21%, and retrofitting refrigerant AC types of split ducts and cassettes that still use R-22 with MC-22 which can save electricity 15-25%.

Research on Improving the Performance of Waterborne Surface Insulation Paint

With the rapid development of China's economy, the demand for electric energy in society is increasing, which puts forward higher requirements for the structure and scale of the national power network. High voltage direct current transmission is considered a new technology that can effectively alleviate the problems of power resource allocation and transmission. Insulation technology is an important part of high-voltage DC transmission and transformation technology. Currently, research on external insulation components such as silicone rubber sleeves is relatively mature, and there is relatively little research on DC internal insulation components such as epoxy poured insulators. Under direct current conditions, the surface of insulation materials is prone to charge accumulation effects, resulting in significant differences in insulation and flashover characteristics compared to AC insulation materials.

Design of piezoelectric nanogenerator based onBiFeO3/epoxy resin with potential application for wearable electronic devices

AbstractGrowing demand for electric energy in newly developed electronic systems causes increasing interest in research on piezoelectric nanogenerators (PENGs). Design and fabrication of such devices is challenging, considering cost of materials used in their construction. This is the main reason why intensive research has begun on 0‐3 composites with piezoelectric properties. One of the most promising constituent materials for composites fabrication are polymers, due to their low cost and easy processing. Herein, we present fabricated wearable PENG with good impact and vibration energy conversion properties. Correlation between matrix stiffness and piezoelectric properties of 0‐3 type composite is proposed. It was found that composite with 10 wt.% of BiFeO3particles exhibits power output density for vibrations, finger tapping, and air stream pressureP = 11.12 nW cm−3,P = 4.83 μW cm−3, andP = 769.2 μW cm−3, respectively. Decrease in stiffness of epoxy matrix results at least in two‐times lower power output density for this same PENG. The obtained results demonstrate that the fabricated BFO/epoxy composites show the wide applicability and potential to be integrated with other functional devices, for example, as a part of wearable devices in smart shoes.

H2/CO production via high temperature electrolysis of H2O/CO2 coupling with solar spectral splitting at a tunable cut-off wavelength

Solar driven CO2/H2O splitting is a promising path for large-scale and long-term solar energy conversion and storage. In this work, a thermodynamic model of solar driven high-temperature CO2/H2O electrolysis was established, with the full solar spectrum split at a tunable cut-off wavelength for meeting the electrical and thermal energy demands of the process at a high efficiency. Compared with the system without spectral splitting, the solar-to-H2 efficiency can be significantly improved from 36.0 % to 45.5 % by introducing spectral splitting. Besides, the optimal electrolysis temperature can be largely lowered, from 1623 K to 1323 K due to the significant reduction of the solar radiation input for electricity generation. The exergy efficiency of CO2 electrolysis was shown to be higher than that of H2O electrolysis due to the higher molar exergy of CO compared to H2, although the first-law efficiency of H2O electrolysis is higher at Tele < ∼1200 K. A high concentration ratio of the solar-thermal process can lead to both high solar-to-fuel efficiency and high optimal electrolysis temperature because of the reduction of reradiation loss. The electrolysis temperature and the use of excessive CO2/H2O were shown to have an important effect on both the efficiency and the optimal cut-off wavelength because they are closely related with the thermal and electrical energy demands of the whole process. The optimal cut-off wavelength can be as low as 540 nm at electrolysis temperature of 1873 K (Tele = 1873 K) and excessive H2O coefficient of 6 (r = 6), and increases to the working limit of the photovoltaic material (900 nm in this work) as the electrolysis temperature and excessive coefficient decrease to Tele < 1023 K and r < 2.