Power Station In China Research Articles

Life cycle assessment of typical tower solar thermal power station in China

In light of the growing environmental awareness and the sustainable development consideration in energy policies, the environmental impacts of concentrating solar power (CSP) have attracted significant attention. Considering that the site selection of CSP stations and databases used for evaluation has an important impact on the environment, the objective of this study is to assess the impact of concentrating solar power tower (CSP-T) station with thermal storage devices in the geographical context of China from environmental perspective by the life cycle assessment (LCA) method. To achieve this goal and ensure the reliability of the research results, a 2 × 50 MW capacity, double tank solar nitrate energy storage, and 12-h energy storage time CSP-T station in Dunhuang, Gansu, was selected. In addition, its model was constructed using the eFootprint online platform, assessing the environmental impacts of the CSP-T station according to the cradle-to-grave system boundary. Moreover, the impact assessment was performed in terms of key metrics, such as energy payback time (EPT), carbon cost of electricity (CCOE), carbon flow analysis, and environmental benefits of energy conservation and emission reduction. The results showed that the production stage is the most significant source of environmental impact in the life cycle of the CSP-T station, with the condensing system and heat storage system contributing 50.17 % and 47.64 % respectively. It can be found that the EPT of the CSP-T station is estimated at 4.88 years, accounting for 16.25 % of the operation cycle of the thermal power station, and varies depending on the station's location. It can be reduced to 3.19 years in places such as North Africa with abundant light intensity. Furthermore, the CCOE of the CSP-T station is 0.04 kg CO2/kWh. Overall, CSP-T station has over 95 % environmental benefits for energy conservation and emission reduction for most indices compared to thermal power station. Although the Chemical Oxygen Demand (COD) index is slightly lower, it still reaches 82.67 %. To promote the ecological development of the CSP-T station in China, this study usually includes a brief comment or relevant improvement recommendations after each comparative analysis.

Study on Conventional Island Retrofit Strategies for Converting Coal-Fired Power Plants to Nuclear Power Stations in China

The conversion of coal-fired power plants to nuclear power stations is a potential method for decarbonizing coal power and offers a pathway for low-carbon development in China’s power industry. This paper focuses on retrofitting China’s coastal coal-fired power stations and compares the potential nuclear reactor technologies for the retrofit: China’s mainstream pressurized water reactor and the commercially operated fourth-generation high-temperature gas-cooled reactor (HTGR). The analysis compares the degree of matching between the two technologies and coal-fired power stations in terms of unit capacity, thermal system parameters, unit speed, structural dimensions, and weight, which significantly impact the retrofit scheme. The results indicate that HTGR is more compatible with coal-fired power plants and is recommended as the type of nuclear reactor technology to be retrofitted. The study selected the 210 MWe High-Temperature Gas-Cooled Reactor Pebble-Bed Module (HTR-PM) as the reactor technology for retrofitting a typical 300 MW class subcritical coal-fired unit. Based on the concept of subcritical parameters upgrading, the potential analysis and strategy study of retrofit is carried out in terms of the turbine, the main heat exchange equipment, the main pumps, and the main thermal system pipelines in the conventional island. The results indicate that the conventional island of the HTR-PM nuclear power plant has significant potential for retrofitting, which can be a crucial research direction for nuclear retrofitting of coal-fired power plants.

Short-term photovoltaic power forecasting with feature extraction and attention mechanisms

The uncertainty of weather conditions has always been a major challenge limiting the performance of photovoltaic (PV) power prediction. Enhancing the accuracy and stability of PV power prediction is crucial for optimizing grid operation. In response to this challenge, this study introduces a hybrid model that integrates an attention mechanism with the Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory Network (BiLSTM). This model aims to mitigate the adverse impact of weather variability on the accuracy of PV power prediction by effectively extracting key features from multidimensional time series data. Additionally, through ablation experiments, this research further assesses the contribution of each model component to performance. Validated with actual data collected from a 1 MW PV power station in China, our proposed model demonstrates significant performance advantages compared to eight advanced prediction models. Ablation study results reveal that removing the CNN component led to a 58.2% increase in MAE and a 53.9% increase in RMSE, while the removal of the attention mechanism resulted in an 83.8% increase in maximum error. These findings underscore the substantial enhancement in prediction accuracy achieved through the integration of CNN and BiLSTM, and the introduction of the attention mechanism significantly boosts the model's prediction stability.

A 10-m national-scale map of ground-mounted photovoltaic power stations in China of 2020

We provide a remote sensing derived dataset for large-scale ground-mounted photovoltaic (PV) power stations in China of 2020, which has high spatial resolution of 10 meters. The dataset is based on the Google Earth Engine (GEE) cloud computing platform via random forest classifier and active learning strategy. Specifically, ground samples are carefully collected across China via both field survey and visual interpretation. Afterwards, spectral and texture features are calculated from publicly available Sentinel-2 imagery. Meanwhile, topographic features consisting of slope and aspect that are sensitive to PV locations are also included, aiming to construct a multi-dimensional and discriminative feature space. Finally, the trained random forest model is adopted to predict PV power stations of China parallelly on GEE. Technical validation has been carefully performed across China which achieved a satisfactory accuracy over 89%. Above all, as the first publicly released 10-m national-scale distribution dataset of China’s ground-mounted PV power stations, it can provide data references for relevant researchers in fields such as energy, land, remote sensing and environmental sciences.

Removal of anionic dyes from wastewater using fly ash based adsorbent

Facing the great challenge of increasing solid waste and huge amount of wastewater, “treating the wastes with wastes” seems to be a proper and sustainable development method. Fly ash, a typical solid waste, has attracted much attention for its high-value applications. In this study, three types of fly ash were sampled from different power stations in China and used for multiple anionic dyes wastewater adsorption. According to the static adsorption, fly ash sourced from Chifeng (CF) was identified as Class C with a total amount of SiO2, Al2O3, and Fe2O3 of 67.65% via chemical composition analysis, and presented best adsorption performance on Reactive Brilliant Red K-2BP, Congo Red 4BS, and Acid Brilliant Red KN. Moreover, the pseudo-second-order kinetic fitted the adsorption processes of KN and 4BS with the theoretic adsorption capacity of 39.35 and 39.85 mg/g, respectively. However, the pseudo-first-order kinetic better described the adsorption process of K-2BP with the theoretical adsorption capacity of 43.24 mg/g. For the dynamic adsorption, the decolorization rate of K-2BP on CF increased from 82.6% to 96.5% as the flow velocity increased from 10 to 70 rpm. The metal cations on CF, such as Fe3+ and Al3+, could hydrolyze and work as flocculants and coagulants to remove dye molecules from wastewater. This study provides a research case and an application potential for the resource reutilization of fly ash to treat printing and dyeing wastewater.

Life Cycle-Based Carbon Emission Reduction Benefit Assessment of Centralized Photovoltaic Power Plants in China

Developing clean energy is the key to reducing greenhouse gas (GHG) emissions and addressing global climate change. Photovoltaic energy systems are considered to be clean and sustainable energy resources due to their wide distribution and easy deployment. However, the environment can still be impacted during the processes from the production to recycling of such systems. Therefore, this study was conducted based on the whole life-cycle analysis to establish a mathematical model for carbon emissions during the processes of production, transportation, and waste disposal of photovoltaic power systems. The main conclusions are as follows. (1) The carbon emissions of a centralized photovoltaic power station with a unit installed capacity of 1 kWp during its entire life cycle would be 2094.40 kg, while the carbon recycling period would last 1.89 years, which would be shorter than the expected life cycle of a photovoltaic system of 25 years, indicating significant environmental benefits. (2) The calculated results from 2022 showed that the newly constructed centralized photovoltaic power stations in China could reduce carbon dioxide emissions by 31,524.26 tons during their life cycles, and their carbon emissions from 1 kWh are approx. 1/10 of those of thermal power generation, which is significantly lower than that of thermal power generation. (3) From the perspective of the soil carbon sequestration capacity and opportunity cost, the economic cost of carbon emissions from the new centralized photovoltaic power stations in China in 2022 was 1.083 billion yuan. (4) The analysis of the relationship using the Granger causality test revealed that, with a lag of one period and a significance level of 5%, the carbon emissions from the new centralized PV power stations from 2013–2022 were the Granger cause of the added value from the secondary industry in China, while the added value from the secondary industry was not the Granger cause of the carbon emissions from the new PV power stations. The findings of the performed study could increase the utilization rate of photovoltaic energy by ensuring it is a secure sustainable low-carbon emission resource, while also reducing the impact of climate change on the planet and promoting individual well-being and social development.

Geochemical and H–O–Sr–B isotope signatures of Yangyi geothermal fields: implications for the evolution of thermal fluids in fracture-controlled type geothermal system, Tibet, China

High-temperature hydrothermal systems are mainly distributed in the north–south graben systems of southern Tibet as an important part of the Mediterranean–Tethys Himalayan geothermal belt in mainland China. As the largest unit capacity and second stable operating geothermal power station in China, Yangyi is the fracture-controlled type geothermal field in the center of Yadong–Gulu Graben. In this paper, hydrogeological and hydrochemical characteristics, isotope composition (δD and δ18O, 87Sr/86Sr and δ11B) of borehole water, hot springs, and surface river samples were analyzed. From the conservative elements (such as Cl− and Li+) and δD and δ18O values, the geothermal water of the Yangyi high-temperature geothermal field is estimated to be of meteoric origin with the contributions of chemical components of the magmatic fluid, which is provided by partially molten granite as a shallow magmatic heat source. According to logging data, the geothermal gradient and terrestrial heat flow value of the Yangyi high-temperature geothermal field are 6.48 ℃/100 m and 158.37 mW m−2, respectively. Combining the hydrothermal tracer experiment, 87Sr/86Sr and δ11B ratios obtained with gradually decreasing reservoir temperatures from the Bujiemu stream geothermal zone to Qialagai stream geothermal zone, we suggested the deep geothermal waters were mixed with local cold groundwater and then flow northeastward, forming the shallow reservoir within the crushed zone and intersect spot of faults in the Himalayan granitoid. Furthermore, in the process of ascent, the geothermal water is enriched in K+, Na+, and HCO3− during the interaction with underlying Himalayan granitoid and pyroclastic rocks that occur as wall rocks. The detailed description and extensive discussion are of great significance for the further exploitation and utilization of north–south trending geothermal belts in Tibet.

Dynamic Modeling of Flue Gas Desulfurization Process via Bivariate EMD-Based Temporal Convolutional Network

Sulfur dioxide (SO2) can cause detrimental impacts on the ecosystem. It is well known that coal-fired power plants play a dominant role in SO2 emissions, and consequently industrial flue gas desulfurization (IFGD) systems are widely used in coal-fired power plants. To remove SO2 effectively such that ultra-low emission standard can be satisfied, IFGD modeling has become urgently necessary. IFGD is a chemical process with long-term dependencies between time steps, and it typically exhibits strong non-linear behavior. Furthermore, the process is rendered non-stationary due to frequent changes in boiler loads. The above-mentioned properties make IFGD process modeling a truly formidable problem, since the chosen model should have the capability of learning long-term dependencies, non-linear dynamics and non-stationary processes simultaneously. Previous research in this area fails to take all the above points into account at a time, and this calls for a novel modeling approach so that satisfactory modeling performance can be achieved. In this work, a novel bivariate empirical mode decomposition (BEMD)-based temporal convolutional network (TCN) approach is proposed. In our approach, BEMD is employed to generate relatively stationary processes, while TCN, which possesses long-term memory ability and uses dilated causal convolutions, serves to model each subprocess. Our method was validated using the operating data from the desulfurization system of a coal-fired power station in China. Simulation results show that our approach yields desirable performance, which demonstrates its effectiveness in the IFGD dynamic modeling problem.

Preface

The 2022 2nd International Conference on Energy, Power and Advanced Thermodynamic Systems (EPATS 2022) was successfully held in Nanjing, China in July 22-24, 2022 in the form of online conference. Energy, along with electricity, has become an indispensable part of our life, and they change the way we live. Under such a background, EPATS 2022 focused on the latest innovations and knowledge in energy and power engineering, stimulated new ideas and promoted collaborations in these areas.We had the honor of inviting both Prof. Lim Yun Seng from Universiti Tunku Abdul Rahman, Malaysia and Prof. M.Shahidul Islam from Universiti Malaysia Sarawak, Malaysia to serve as our Conference Chairmen. 120 individuals and enterprises all over the world attended the conference. Divided into three parts, the conference agenda covered keynote speeches, oral presentations, and online Q&A discussion. Firstly, keynote speakers were each allocated 30-45 minutes to hold their speeches. Then in the oral presentations, the excellent papers selected were presented by their authors one by one.During the conference, we were greatly honored to invite four sophisticated keynote speakers to address their speeches. Among them, Assoc. Prof. Sen Guo from North China Electric Power University delivered a thought-provoking speech on the topic: Comprehensive Performance Evaluation of Pumped Storage Power Station in China. In this research, a hybrid novel fuzzy multicriteria decision-making (MCDM) method combining the fuzzy best worst method (BWM) and fuzzy TOPSIS was proposed for the comprehensive performance evaluation of pumped storage power stations in China. Additionally, Prof. Zhenbin Zhang from Shandong University, China presented us his report: Cooperative-Predictive Control of Hybrid Microgrids. This report provided possible control solutions for further MG-based power grid, and presented the latest progress and contribution of his team in this field. Three research aspects were discussed, including predictive control of power converters in the primary layer, cooperative control of multiple distributed generators in the secondary layer as well as cooperative control between the AC and DC heterogeneous sub-grids. The wonderful and dramatic speeches of each keynote speaker had triggered heated discussion. Moreover, every participant praised this conference for disseminating useful and insightful knowledge.We are glad to share with you that we received lots of submissions from the conference and we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewing them. These papers feature but are not limited to the following topics: Energy Storage Technology, Self-Healing of the Power Grid, Power Grid Coordination, Engineering Thermodynamics, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication.On behalf of the conference organizing committee, we would like to express our heartfelt appreciation to all the keynote speakers, peer reviewers, and all the participants. Especially, we would like to acknowledge the Journal of Physics: Conference Series, for the efforts of all the colleagues in publishing this paper volume. We firmly believe that all the attendees have had fruitful discussions and gained valuable knowledge, and will enjoy the opportunity for future collaborations.Committee of EPATS 2022List of Committee member is available in this Pdf.

Solar photovoltaic program helps turn deserts green in China: Evidence from satellite monitoring

Solar energy is considered one of the key solutions to the growing demand for energy and to reducing greenhouse gas emissions. Thanks to the relatively low cost of land use for solar energy and high power generation potential, a large number of photovoltaic (PV) power stations have been established in desert areas around the world. Despite the contribution to easing the energy crisis and combating climate change, large-scale construction and operation of PV power stations can change the land cover and affect the environment. However, few studies have focused on these special land cover changes, especially vegetation cover changes, which hinders understanding the effects of the extensive development of solar energy. Here, we used Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA) based on Landsat images to monitor changes in vegetation abundance before and after the PV power stations deployment. To reduce the interference of PV shading on vegetation abundance estimation, we improved the vegetation (VG) fraction from SMA and developed the Photovoltaics-Adjusted Vegetation (PAVG) fraction for vegetation abundance measurements in PV power stations. Results show that PV power stations in China's 12 biggest deserts expanded from 0 to 102.56 km2 from 2011 to 2018, mainly distributed in the central part of north China. The desert vegetation in the deployment area of PV power stations presented a significant greening trend. Compared to 2010, the greening area reached 30.80 km2, accounting for 30% of the total area of PV power stations. Overall, the large-scale deployment of PV power stations has promoted desert greening, primarily due to government-led Photovoltaic Desert Control Projects and favorable climatic change. This study shows the great benefits of PV power stations in combating desertification and improving people's welfare, which bring sustainable economic, ecological and social prosperity in sandy ecosystems.

Thermal performance analysis of a solar-driven supercritical CO2 split-flow recompression Brayton cycle

ABSTRACT Solar is a clean and renewable energy, and is considered as the desired heat source of supercritical CO2 Brayton cycle. The heliostat field and cavity receiver of DAHAN tower solar thermal power station in China are used for analyzing the geometric relations between the sun, heliostat field and the receiver. The ray-tracing method is applied to establish a model to calculate the heat flux distribution of heating surface in the receiver. According to the absorbed heat, the supercritical CO2 split-flow recompression Brayton cycle model can be built via the Aspen HYSYS software. The uneven distribution on the heating surfaces represents a higher heat flux at the center of the spot and a lower heat flux away from the spot. The maximum heat flux is 224 kW·m−2 at 9:00 am, 349 kW·m−2 at 12:00 noon, and 215 kW·m−2 at 3:00 pm. Based on this distribution, the thermal efficiency of DAHAN tower solar thermal power station can be obtained by modeling. Compared with the steam Rankine cycle, the thermal efficiency of supercritical CO2 Brayton split-flow recompression cycle has a 50% increment. Subsequently, the effects of the split-flow ratio, the inlet temperature and pressures of turbo expander and main compressor, and the heat absorption on the thermal performance of system are obtained. Finally, the optimal parameters are obtained as follows: the split-flow ratio is 0.605, and the inlet pressures of turbo expander and main compressor are 24 and 7.9 MPa, respectively. These interesting findings are particularly significant for the application of supercritical CO2 split-flow recompression Brayton cycle system and the operating parameters’ selection in solar thermal power generation stations.

Chemical Speciation and Leaching Behavior of Hazardous Trace Elements in Coal Combustion Products from Coal-Fired Power Stations in China.

This paper reports on the chemical speciation and leaching behavior of a selected group of hazardous trace pollutants in lignite and lignite-petcoke blend co-combustion products from three power stations in China. The evaluation of speciation results showed that, during combustion, oxidizable elements, mainly As and Mo, bound to organic matter and sulfides in coals were mostly transferred to easily water-soluble forms or to slightly acidic states in the ashes. This manner was the most readily bioavailable condition for such an environment. The evaluation of the leaching results shows that the use of petroleum coke as co-fuel has an impact on the ash composition and on the leaching behavior of some inorganic trace pollutants such as Mo and V. The leaching results compared to the European waste acceptance criteria for landfills reveal that the Mo and As’ leaching yield brand the coal combustion products as materials that necessitate preventative measures to reduce their potential leaching. Future work will be focused on the application of our novel chemical stabilization method to these coal ashes to reduce the mobility of elements such as Mo and As, and other potentially leachable elements, and on the use of the resulting ash with aggregate products as a substitute for concrete production.

A Hybrid Novel Fuzzy MCDM Method for Comprehensive Performance Evaluation of Pumped Storage Power Station in China

Considering the goals of carbon peaking and carbon neutrality, along with their related policies, pumped storage power stations are set to develop quickly in China. The comprehensive performance of pumped storage power stations must urgently be evaluated, which can help investors in decision making and provide a reference for policymakers. In this paper, a hybrid novel fuzzy multicriteria decision-making (MCDM) method combining the fuzzy best worst method (BWM) and fuzzy TOPSIS was proposed for the comprehensive performance evaluation of pumped storage power stations in China. The fuzzy BWM was utilized to determine the criteria weights describing the comprehensive performance of pumped storage power stations, while the fuzzy TOPSIS was used to rank the comprehensive performance of pumped storage power stations. The index system for the comprehensive performance evaluation of pumped storage power stations in China incorporated economic, social, and environmental aspects. The comprehensive performance of four pumped storage power stations in China was empirically evaluated using the proposed hybrid novel fuzzy MCDM method, and the results indicate that pumped storage power station PSPS2 exhibited the best comprehensive performance, followed by pumped storage power stations PSPS1 and PSPS4, whereas pumped storage power station PSPS3 had the worst comprehensive performance. A sensitivity analysis and comparative analysis were also conducted. The results indicate that the proposed hybrid novel fuzzy MCDM method, combining the fuzzy BWM and fuzzy TOPSIS for comprehensive performance evaluation of pumped storage power stations, is robust and effective.

An Enhanced Ubiquitous-Joint Model for a Rock Mass With Conjugate Joints and Its Application on Excavation Simulation of Large Underground Caverns

A conjugate jointed rock mass (CJRM) is a rock mass with two sets of intersecting joints formed from intact rock under shear. Its mechanical properties and excavation-induced hazards of large underground caverns are different from those of common rock masses because of the unique geological origin thereof. To demonstrate numerically the excavation responses of CJRM, the ubiquitous-joint model is enhanced by consideration of the specific mechanical behaviors of the rock mass. In the enhanced model, CJRM is considered as the composite of columns of rock and two sets of weak planes of joints. The local coordinates, failure modes, and failure sequences of the rock columns and joints are redefined based on the composite characteristics of CJRM, and the failure criteria and plastic potential functions are accordingly modified. The enhanced model is verified numerically by triaxial compression tests and then employed to simulate the excavation of large underground caverns of a pumped storage power station in China. Results show that the modification of the local coordinate system, failure modes, and failure sequences made in the enhanced model is suited to the simulation of the mechanical behaviors of CJRM. Compared with the original ubiquitous-joint model, the enhanced model allows better predictions of the distribution of plastic zones and magnitudes of deformations in simulating underground excavations in CJRM and helps to assess the excavation-triggered hazards more accurately.

Analysis on the Trading Path of Carbon Emission Rights of Village-level Photovoltaic Poverty Alleviation Power Stations in China

Photovoltaic poverty alleviation is a pioneering initiative in the organic combination of China’s poverty alleviation and new energy development. As a landmark project of China’s targeted poverty alleviation, it is characterized with rapid effects, steady profits, precise poverty alleviation and environmental-friendliness. Developing the photovoltaic poverty alleviation power station project into a greenhouse gas emission reduction project that meets the national requirements is not only an innovative measure to consolidate and expand the achievements of poverty alleviation, and continuously promote rural revitalization, but also an effective way to practice green and low-carbon development and promote “Carbon Peak•Carbon Neutrality”. Based on the summaries and analysis of the development of China’s photovoltaic poverty alleviation and carbon trading market and the situation of carbon emission trading pilot, this paper sorts out the relevant policies of poverty alleviation’s participation in carbon trading, studies the participation mode and trading process of village-level photovoltaic poverty alleviation power station, scientifically calculates the additional economic benefits brought by Chinese Certified Emission Reduction (CCER) trading for village-level photovoltaic poverty alleviation power station, and puts forward some policy recommendations on rationally optimizing carbon trading procedures and improving work efficiency. Keywords: Photovoltaic poverty alleviation, Carbon market, Carbon trading, Implementation path DOI: 10.7176/PPAR/11-5-01 Publication date: June 30 th 2021

Evaluating fuel consumption factor for energy conservation and carbon neutral on an industrial thermal power unit

Energy conservation was crucial for operating one industrial power device unit, because the better energy management was beneficial for decreasing the cost during the operation. On the other hand, in a carbon-neutral context, decreasing the Greenhouse gas (GHG) emission was as important as the energy conservation. In this paper, the direct method of the evaluation on the fuel consumption for the energy management was investigated. The fuel consumption factor for the energy conservation was studied in terms of ten different types of the single fuel consumption factor, the average value of the single fuel consumption factor, and the total fuel consumption factor. The result showed that the maximum of the fuel consumption factor was from the backpressure in the turbine part. The fuel consumption factor decreased from 12.65 g/kWh to 9.23 g/kWh after the optimization during the operation. The effect for the energy conservation could reach over 80%, and the cost saving for the optimization could be over 4.65 million US dollars for one year on one power station in China. the goal on the analysis of the fuel consumption factor was controlling the use of the coal, and thus also controlling the CO2 emission.

Exploration on planning and development of pumped storage power stations in China

Our country has a vast territory and a large population, with the rapid development of economic society, electricity load continues to grow, and the difference between peak and valley load continues to grow also. Pumped Storage Power Station is the most mature large-scale energy storage method at present, and it is an important part of the new power system with new energy as the main body. In order to adapt to the rapid development of wind power, solar power and other new energy, and meet the requirements for safe and stable operation of nuclear power, ensure the safe and reliable operation of the power system, it is necessary to reasonably support and accelerate the construction of pumped storage power stations.

Analytical method for estimating leakage of reservoir basins for pumped storage power stations

Pumped storage power stations are increasingly constructed around cities to provide electric power and ensure grid stability. However, the upper reservoirs are typically located on mountaintops, and the reservoir leakage, which directly affects the economic benefits, is typically difficult to estimate. Therefore, to calculate the leakage within a short period, a one-dimensional simplified analytical method for estimating the leakage of pumped storage power station reservoir basins is proposed based on the stable seepage theory and Darcy’s law. Formulae are derived to calculate the seepage flux of the reservoir basin with different groundwater levels, which can be below or above the bottom of the reservoir basin. The reliability of this analytical method was validated using numerical analysis with regard to a pumped storage power station in China, and the relative errors between the analytical results and the numerical results are less than 5%. The proposed method is beneficial for engineering decision-making and design before the construction of pumped storage power stations.

Water seepage detection using resistivity method around a pumped storage power station in China

To detect water seepage and ensure the safety of Pumped Storage Power Station (PSPS) facilities, we apply the electrical resistivity method to evaluate the leakage when the water level is on the rise. We check whether there is a leakage channel near the cavern group of the underground powerhouse. We conduct the field survey and integrate the results with regional geological data to determine the distribution of faults and large cracks. Granite intrusions generate a variation of high and low resistance phases, representing granite porphyry and tuff, respectively. The interface between the two lithologies is the location of the fault zone. In general, the apparent resistivity of two does not change much, indicating that the rock masses are relatively stable. The internal fractures of the rock masses are not developed, and there is no visible water content. However, from the location of the lithological contact interface, the rock mass is broken. Therefore, we recommend that before constructing the lower reservoir, anti-seepage treatment should be carried out.

Research on benefit evaluation method of pumped storage power station

The development of pumped storage power stations in China is relatively short, and there is a lack of objective evaluation of the system benefits of pumped storage power stations, which leads to the problems of inaccurate functional positioning, single investment mode, and imperfect electricity price mechanism of pumped storage power stations in China, hindering the healthy development of pumped storage power stations. In order to solve this problem, this paper establishes the benefit evaluation system of pumped storage power station, selects economic benefit, technical benefit, social benefit and environmental benefit as evaluation indexes, and constructs the benefit evaluation model based on order relation analysis and entropy weight method.