Advances in Energy Power and Automation Engineering

Table of Contents

1. Frontmatter

2. Energy Utilization Management and System Optimization

   1. Frontmatter

   2. Sensitivity Analysis of Stratigraphic Parameters on the Yield of CO2-Enhanced Geothermal Systems

      Bin Liu, Chunyang Feng, Kaiwen Hu

      Abstract

      Geothermal energy can help improve the energy mix and reduce carbon emissions. CO₂ can be used as a heat exchange medium in the process of geothermal development, and at the same time, realize the geological storage of CO₂. In this chapter, an enhanced geothermal system (EGS) with coupled thermal–hydraulic–mechanical (THM) containing discrete fractures is developed. Using the sensitivity analysis method, 13 formation parameters controlling the heat production performance of CO₂−EGS were studied with thermal breakthrough time and net heat production rate as target parameters. It is found that the most important parameters affecting the heat production performance of CO₂−EGS are matrix permeability and fracture aperture.

   3. Temporal and Spatial Downscaling of Wind Forecast of New Energy Stations Based on an Optimal Frequency Bias Algorithm

      Gang Liu, Dongmei Yang, Wenjie Ye, Yize Yang

      Abstract

      Accurate wind speed prediction through numerical weather prediction (NWP) can reduce the operating cost of wind farms. To satisfy the demand of wind forecasts of high temporal and spatial resolution for power prediction at wind power stations in Shanxi province, surface wind field forecasts at the new energy stations from the global forecast system (GFS) model are temporally and spatially downscaled from September 1, 2021, to August 31, 2022, in this paper. Results showed that the performance of the downscaled forecast product based on the optimal frequency bias (OFB) algorithm is better than that of the original model forecast for different initial times, lead times, ground levels, and wind speed grades. The threat score (TS) of surface wind speed forecast fluctuates periodically with forecast lead time. In general, 14 PM corresponds to the peak of the TS time series, while 02 AM corresponds to the trough. The TS improvement of the downscaled products initialized at 00 UTC is greater than that initialized at 12 UTC. Furthermore, the improvement is more obvious for wind speed levels that are closer to the ground.

   4. Study on Signal Noise Reduction Based on Wavelet Threshold Technique

      Bohui Zhang, Jinlong Wang, Xiang Zheng

      Abstract

      In the collection of local electrical signals, electrical equipment is in operation, and in the detection process, there will be a certain degree of noise interference, electromagnetic interference, or other interference. So the original signal received will be biased due to interference. Therefore, how to solve the noise processing of the original local emission electrical signals. In this paper, we thoroughly investigate noise reduction techniques based on wavelet threshold methods. We give an overview of wavelet theory and introduce the basic principle of the wavelet transform and its application in signal processing. In the experimental part, the methods of Dmey wavelet global default threshold denoising, Haar soft SUR threshold denoising, and DB3 wavelet fixed threshold are used to denoise and analyze the noise reduction effect under different threshold treatment methods.

   5. Neural Network PID-Based Frequency Control Strategy for Energy Storage Participating Loads

      JunJie Lv, Hong Wang, Zhijie Wang

      Abstract

      With the goal of “double carbon” and the deepening of China’s power system reform, the operating characteristics of the power system are more complex and variable. The demand for frequency control of traditional thermal power units and hydropower units is growing. Load frequency control (LFC) is one of the important means of frequency control in the power system. Its primary goal is to keep the system frequency within zero steady-state error. A neural network proportional-integral-derivative (PID)-based energy storage participation LFC strategy is proposed for the load frequency problem of two types of units. First, the traditional closed-loop LFC models of thermal and hydroelectric units are established according to the frequency response characteristics of the traditional units; then, the energy storage system used for the frequency regulation of the power system is selected, and the corresponding frequency response model is established. Finally, an LFC controller design method based on a neural network PID algorithm is studied, and the simulation results show that the proposed neural network PID control method has better response characteristics compared with the traditional PI control.

   6. A Small Sample Load Recognition Method Incorporating SE Attention Mechanism

      Junwei Zhang, Zhukui Tan, Bin Liu, Jipu Gao

      Abstract

      With the implementation of the dual carbon policy, user-side energy management is an important carbon reduction initiative. Load identification is an important customer-side energy management method, and after obtaining the voltage and current information of the customer side, the hidden information is mined by machine learning and other methods. However, the sample entries on the customer side are small, and it is difficult to train a conventional network with better results. Therefore, this chapter proposes a small-sample load identification method that combines the squeeze-and-excitation (SE) attention mechanism. It first constructs colored V-I trajectory maps based on voltage and current signals of conventional users and then constructs a neural network model for trajectory map classification. The SE attention mechanism is added to the network so as to give more attention to the channels containing more information, thus improving the classification effect. Finally, the effectiveness of the proposed method is verified by classifying appliances using the WHITED dataset. The proposed method plays an important role in small sample load recognition information mining.

   7. Research on Optimization Configuration of Distributed Integrated Energy System Based on Latin Hypercube Method

      Huang Ao

      Abstract

      This chapter proposes a planning method based on an improved solution algorithm to minimize the energy cost and thus realize the optimal configuration of the system for example a distributed integrated energy system (IES) in a certain region. The model takes into account the technical and economic parameters of the equipment, the user’s multi-energy load profile, the minimization of the system energy cost as the goal, and the comprehensive consideration of the equipment capacity configuration as well as the economic operation. The uncertainty analysis of the equipment parameters is solved by adopting the Latin hypercube sampling (LHS) method for the key equipment parameters, and the Monte Carlo algorithm is improved by combining with the convex optimization method to solve the above planning problems, and the global optimal results are found. The optimization results show that the proposed method can improve the operation efficiency of model solving and effectively reduce the operation cost of the system, which verifies the feasibility of the method.

   8. Numerical Simulation and Defect Optimization in CZTSSe Solar Thin-Film Cells Implementing MoS2 as HTL Layer

      Tao Wang, Yuming Xue, Luoxin Wang, Tianen Li, Hongli Dai

      Abstract

      CZTSSe is a promising clean photovoltaic material; however, in fact, the power conversion efficiency (PCE) of CZTSSe solar cells is still far below the maximum theoretical efficiency, and one of the important reasons is the crystallographic factors that limit the performance of CZTSSe. In this chapter, SCAPS-1D is used to simulate the performance of CZTSSe cells with MoS₂ as the HTL layer, focusing on the simulation of the thickness ratio, defect density of MoS₂, WS₂/CZTSSe, and CZTSSe/MoS₂ interface defect density. The optimal thicknesses of the CZTSSe and MoS₂ are determined to be 400 and 1600 nm. It is found that the interface defects of the buffer layer and the absorption layer have a significant impact on the performance of the battery, and the expected reasons are given. Finally, the optimized PCE can reach 22.31%. This work may be helpful for the application of MoS₂ in CZTSSe solar thin-film cells, and make a little contribution to the continuous development of CZTSSe solar cell research.

   9. The Solar Cell Performance Parameters of CuI as a Hole Transport Layer Were Analyzed by SCAPS-1D

      Jiawei Shen, Yuming Xue, Luoxin Wang, Tianen Li, Hongli Dai

      Abstract

      Kesterite materials such as CZTS are widely found in nature and have the advantages of nontoxicity, high absorption coefficient, direct bandgap, etc. These characteristics are conducive to the production of solar cells. Solar technology has seen some success in recent years, but there is still a big gap between the actual conversion efficiency and the ideal conversion efficiency, and the main problem lies in the defects of the CZTS layer and CdS/CZTS interface layer. Copper iodide (CuI) has better photovoltaic characteristics, which can be used as a potential solution to this problem. Therefore, different from traditional solar cells, a CuI layer is added as a hole transport layer (HTL), and the SCAPS-1D program is used for simulation. Adjust the thickness of the CZTS layer and CuI layer, defect density of the CZTS layer and defect density of the CdS/CZTS interface layer, and other different variables to optimize the Cu/AZO/i-ZnO/CdS/CZTS/CuI/Au structure. The battery structure was optimized through power conversion efficiency (PCE), short-circuit current (J_SC), open-circuit voltage (V_OC), and filling factor (FF), and the efficiency was finally increased to 21.26%.

   10. The Influence of Two Flow Control Methods on the Anti-Wind Sand Erosion Wear of Airfoils

       Yuantian Xue, Yongxiang Li, Hongtian Zhang

       Abstract

       In the twenty-first century, with the efforts of scholars at home and abroad, the related technologies of wind power generation are being improved. In this chapter, combining the flow control method of wind turbines and the resistance to wind and sand erosion and wear, this chapter investigates the effects of two flow control methods, namely, the leading-edge small wing and the leading-edge cylinder, on the aerodynamic performance and resistance to wind and sand erosion and wear of wind turbine wing profiles. Research has shown that both flow control methods can enhance the aerodynamic performance of airfoils while enhancing their resistance to wind and sand erosion and wear. Compared to the leading-edge small wing control airfoil, the leading-edge cylindrical control airfoil has a better anti-erosion and wear effect, but the improvement in the effect of aerodynamic performance is opposite.

   11. Tannic Acid/Polyurethane-Laminated Coatings for the Stability of Metal Anodes in Aqueous Zinc-Ion Batteries

       Liteng Qiao, Jie Liu

       Abstract

       Although Zn metal offers low cost, high safety, a high theoretical specific capacity of 820 mAh g⁻¹, and a smaller redox potential (−0.76 V versus SHE), it encounters issues like dendrite rampant generation, corrosion, and passivation reaction when utilized in the anode of aqueous Zn-ion batteries. Together, these issues reduce the cycle life of the battery and the coulombic efficiency. In this chapter, a bifunctional coating is constructed on the surface of the Zn anode by repeated spin-coating twice. The coating is composed of two layers, one layer on the surface of the Zn electrode is a tannic acid (TA) coating, which uses the chelation effect of TA and zinc metal to anchor Zn²⁺ on the cross-linking network of TA molecules, which limits the two-dimensional deposition of Zn²⁺, thereby producing a uniform nucleation site, avoiding the “tip effect”. The polyurethane (PU) coating that touches the electrolyte layer acts as a solid barrier to keep water molecules from reaching the surface of the Zn electrode because of its strong water-repelling properties, preventing both the hydrogen evolution reaction (HER) and severe corrosion reaction from happening. The Zn@PT//Zn@PT symmetrical battery exhibits exceptional cycling stability, enduring over 1200 h at 1 and 0.5 mAh cm⁻², with minimal overpotential. Despite the rise in a current density to 5 mA cm⁻², the cycling performance of the full cell remains stable for over 500 h, surpassing that of Zn//Zn symmetrical cells. The Zn@PT//MnO₂ cells possess a high specific capacity of 271.6 mAh g⁻¹ at a current density of 0.2 A g⁻¹.

   12. Cost–Benefit Optimization Analysis of Proper Utilization Rate of Provincial Renewable Energy

       Jing Wan, Fen Cao, Anyuan Yang, Jinrui Tang, Shuang Xu, Rui Chen

       Abstract

       A novel method is proposed to analyze the reasonable utilization rate of renewable energy considering the cost of adjustable resources in provincial area. The formula for calculating the utilization rate of renewable energy in provincial region is quantitatively given by combining the power supply load of the power system in the target region and the operating constraints of non-hydro conventional units. And then the analytical expression for the utilization rate of renewable energy based on the cost of consumption is proposed by combining with the provincial power supply–demand balance model that takes into account the output of renewable energy. The results of one case study show that the renewable energy utilization rate gradually increases with the growth of flexibility resources, but the effect of renewable energy consumption per unit of new flexibility resources gradually decreases, and the reasonable renewable energy utilization rate in the analyzed area in some year is 0.9886.

   13. Water Partial Discharge Detection via Interferometry

       Junjie Chen, Wenjing Wang

       Abstract

       Partial discharge (PD) detection plays a pivotal role in ensuring the integrity and reliability of electrical power systems. PD events serve as precursors to insulation breakdown, posing significant threats to equipment safety and operational continuity. Traditional PD detection methods have exhibited limitations, particularly in liquid insulation environments. This chapter presents an interferometric method for detecting PD in liquids. Employing a setup based on interferometry, PD in the liquid sample is induced by the voltage from a lightning surge generator, and the resulting distorted interference patterns are captured using a CCD camera. The experimental results show that the peak value of the phase after PD is larger than that before PD, and the peak value of the phase distribution increases accordingly with the increase of the voltage. This study highlights the direct relationship between the applied voltage and the phase distribution generated within the interferogram, which provides a new idea for condition monitoring and fault diagnosis of liquid insulation systems.

   14. Interactive Management Strategy of Virtual Power Plants Based on Carbon Demand Response

       Jiapei Liu, Wenwen Qin, Chao Yue

       Abstract

       Household energy consumption continues to rise as the living standards of residents improve, making household carbon emissions a major contributor to global carbon emissions. Aiming at a low-carbon management strategy for the virtual power plants (VPPs), this paper estimates household carbon emissions based on dynamic carbon emission factors that can accurately reflect differences in carbon emissions generated by electricity, which can accurately reflect the difference of carbon emissions generated by electricity and heat consumption in each period. On this basis, a carbon demand response mechanism was established to guide users to adjust their energy consumption plans according to the carbon emission intensity of energy consumption in different periods. The coordinated load plan influences the VPP scheduling plan and achieves the interaction between supply and demand. According to the simulation results, compared with the traditional integrated demand response (IDR) mechanism, the carbon emissions of this method are reduced by 9.3%, and the energy supply cost is reduced by 18.9%, which shows that the CDR mechanism proposed in this paper can effectively reduce the carbon emissions and energy supply cost of the system.

   15. A Multi-objective Optimal Scheduling Method for the Gas–Steam–Power System Takes into Account the Exergy Efficiency of Iron and Steel Enterprises

       Lei Zhang, Peihong Yang, Lan Kang, Hui Cao

       Abstract

       To achieve the economic, low-carbon, and high-efficiency cooperative operation of gas–steam–power system (GSPS) in iron and steel enterprises, this chapter proposes a multi-objective optimal scheduling method that takes into account the exergy efficiency of GSPS. First, the analysis approach of electricity equivalent is used to simplify the calculation of the exergy efficiency, and a low carbon emission reduction method based on exergy efficiency is proposed for the GSPS, which can achieve the dual goals of reducing system carbon emissions and reducing energy consumption. Then a multi-objective scheduling model is constructed to maximize the exergy efficiency of the system and minimize the operating cost. Finally, the Pareto frontier solution is obtained by using the traversal weight method of solving, and the optimal decision solution is determined by combining with the TOPSIS method. The effectiveness of the proposed method is verified by simulation examples, which can provide a guiding program for the sustainable development of iron and steel enterprises.

   16. Load Forecasting Based on SABO-PSO-ELM Hybrid Algorithm

       Erhao Shang

       Abstract

       The short-term forecast of power load is of great significance to the planning and development of the power industry. In this chapter, we propose a new method to enhance the performance of predictive models by combining subtraction mean optimization (SABO), particle swarm optimization algorithm (PSO), and extreme learning machine (ELM). Through careful parameter adjustment and optimization process, this study successfully demonstrated the effectiveness of SABO and PSO algorithms in optimizing ELM parameters, which greatly improved the application performance of the model in practical prediction tasks. In addition, the method in this study provides a feasible solution for processing complex data sets, enhancing the adaptability and stability of the model in the face of data changes. Future work will explore the potential of this approach for other types of machine learning tasks and on larger data sets. The proposed method was evaluated using the 2021 load data of the PJM public dataset and the 2022 full-year data of an industrial park in Liaoning province. The SABO-PSO-ELM method is compared with other mainstream methods (BWO-ELM). The statistical analysis shows that the proposed method has better prediction accuracy on the four standard scales of MSE, MAPE, MAD, and NRMSE, which reflects the advanced nature of the method.

   17. Optimal Configuration Method of Power-Energy Hybrid Storage Systems for Renewable Power Plants

       Yanda Huo, Jiahui Qu, Yang Wang, Hua Jiang

       Abstract

       Compared with traditional single storage technologies, a hybrid energy storage system (HESS) combines various storage methods, utilizing the advantages of multiple techniques and compensating for the shortcomings of a single storage technology. It is one of the effective ways to address the intermittency issues of renewable power output. Addressing issues of rapid fluctuation and randomness of renewable power, this paper proposes an optimization configuration method of a power-energy hybrid storage system (PEHSS) for renewable power plants (RPP). The proposed method decomposes and reconstructs the original output data of RPP, obtaining the high-frequency fluctuation information and low-frequency steady-state information. Subsequently, the high-power energy storage system (HPESS), such as flywheels and super capacitors (SC), can be configured with the high-frequency fluctuation information, which contributes to the suppression of power fluctuations for RPPs. Then the capacity of the energy storage system (ESS) can be calculated with the low-frequency steady-state information to achieve within-day peak shaving for RPPs. This research overcomes the shortcomings of traditional planning methods in multi-time scale configuration for HESS. The case studies verify the effectiveness of the proposed method.

   18. Integrated Optimal Operation of Rural Microgrid Production Management Considering Photovoltaic Outputs

       Dayong Liu, Dapeng Jia, Keyin Jia, Hongbo Wen, Shiyang Zheng

       Abstract

       Rural microgrids are characterized by a close connection between industrial production and energy demand, which can play an important role in optimizing the flexible scheduling of the distribution market. This chapter proposes an integrated optimization model and method for production management of rural microgrids, considering photovoltaic output, in which ground source heat pumps are introduced to provide hot and cold energy for rural microgrids to optimize the energy strategy of rural microgrids; finally, the feasibility and effectiveness of the method are verified through an example analysis.