Integrated Intelligent Energy

A three-point probabilistic load flow estimation algorithm for the power system considering photovoltaic uncertainties

GAO Ming, CHEN Jiahao, WANG Lixiao, TANG Wuchen, WANG Zhidong, ZHANG Zifan, MA Haixia, FENG Ruijue, ZHOU Changpeng

2022, 44(9): 1-10. doi:10.3969/j.issn.2097-0706.2022.09.001

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As the access proportions of renewable energy and adjustable load rise,the traditional power system faces increasingly complex uncertainties. In order to effectively describe the influence of uncertain factors on system operation,a probabilistic load flow calculation method based on three-point estimation method（3PEM）is proposed. Firstly,3PEM takes 2m+1 sampling strategy to reduce the sampling time. Combining cumulant method and Cornish-Fisher series,the probabilistic load flow of the power system taking adjustable load and PV uncertainty into considerations is described quantitatively. The method is verified by an IEEE 33 node system. Taking the results obtained from Monte Carlo method as the reference,the proposed method is proved to be accurate and fast. Further study is made on comparing the effects of PV power grid-connection on the probability load flow,and the results show that the closer the PV power connection point is to the power system,the more significant impact is on the power system.

Research on the optimal configuration of integrated energy systems for parks with hydrogen storage devices

ZHONG Pengyuan, YANG Xiaohong, KOU Jianyu

2022, 44(9): 11-19. doi:10.3969/j.issn.2097-0706.2022.09.002

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Since hydrogen energy is of high energy density and good energy storage capacity,its application to an integrated energy system for an industrial park can effectively improve the economy of the system.A study on the optimal configuration of integrated energy systems for parks with hydrogen storage devices is made.Firstly,electricity storage devices for the system are replaces by hydrogen storage devices.Then,the system takes the uniform annual value of its whole-life-cycle cost as the objective function of the capacity configuration layer,and its annual operating cost as the objective function of the optimal operating layer.Under the constraints on energy balance and equipment outputs,the corresponding model of the optimal configuration is established.The bi-level optimization algorithm that integrates particle swarm algorithm and CPLEX solver is used to solve the model.Finally,the equipment capacities,operation mode,system performance and economy of the power system for an industrial park are analyzed.The analysis results shows that the scheme of integrated energy systems for parks with hydrogen storage systems can meet users' real-time energy demand reliably.Comparing the power system with hydrogen storage devices and the one with electricity storage devices,their performances are roughly the same,but the former one is obviously more economic,which proves the practicability of the suggested method.

Researches on hydrogen storage peak-shaving technology for new power systems to achieve carbon neutrality

HAN Shiwang, ZHAO Ying, ZHANG Xingyu, XUAN Chengbo, ZHAO Tiantian, HOU Xukai, LIU Qianqian

2022, 44(9): 20-26. doi:10.3969/j.issn.2097-0706.2022.09.003

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Economic development varies significantly in different regions of China.The resources reserves in western China superior to that in eastern China,but the economic situation is just the opposite.Renewable energy in the west cannot be totally consumed locally,and has to be transmitted to the east.Power generation is a common application way of renewable energy,but the operation is greatly affected by seasons and weather.Therefore,it is difficult to accurately predict the amount of electricity generated by renewable energy.The power grid system needs corresponding energy storage technologies and facilities to realize peak regulation,so as to reduce the waste of renewable energy and perform peak regulation.The mutual conversion between electricity and chemical energy of hydrogen and ammonia can achieve the purpose of energy storage and peak regulation.When the electricity is sufficient,the surplus electricity is stored by hydrogen production from water electrolysis and ammonia synthesis technology.On the contrary,the stored energy will be transmitted to the power grid from fuel cells and hydrogen power station when the power supply is insufficient.To achieve the "dual carbon" target,the ammonia synthesis and hydrogen storage technologies applied in the new power system are expounded,and the advantages of fuel cells and principles of ammonia transportation and combustion are discussed.Hydrogen and ammonia are proven to be practical,efficient,economic and environmental for the peak regulation of the new power system.

Carbon emission reduction analysis for gas-based distributed integrated energy systems

JIANG Ting, ZHAO Yajiao

2022, 44(9): 27-32. doi:10.3969/j.issn.2097-0706.2022.09.004

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Integrated energy system is regard as an excellent power suppler at current stage for its capabilities of horizontally adjusting electric power,heat,cold energy,gas and hot water,and vertically coordinating source,network,load,storage and consumption links.CCER methodology and Guidelines On Enterprises Greenhouse Gas Emissions Accounting and Reporting—Power Generation Facilities provide a calculation method for the carbon emission reduction of gas-based distributed integrated energy systems and the reference system.A carbon emission reduction analysis was made on a gas-based distributed integrated energy system in Beijing.The system worked well in energy saving and emission reduction in current power system for realizing 3 000 tCO₂ emission reduction from 2016 to 2020 annually.With the large-scale grid-connection of renewable energy generators,the greenhouse gas emission factor for grid will drop to 0.34 tCO₂/（MW·h） or below.At that time,the existing system can no longer save energy or reduce carbon emissions,unless the proportion of power supply made by renewable energy can be increased.The study lays a sound theoretical foundation for the development of gas-based distributed integrated energy systems and the realization of "dual carbon" target.

Prediction method for adjustable load based on EEMD-BiLSTM

LI Bin, HU Chunjin, WANG Jing

2022, 44(9): 33-39. doi:10.3969/j.issn.2097-0706.2022.09.005

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To achieve the goals of carbon peaking and carbon neutrality,adjustable load has become emerging regulation resources of the power grid. In order to solve the mode aliasing phenomenon in EMD and obtain good time perception of load series,an adjustable load prediction method that combines EEMD with BiLSTM is proposed. The working principles of EEMD and BiLSTM were expounded. The preprocessed adjustable load series was decomposed by EEMD algorithm, and then the decomposed component data and original data were used for load prediction modeling and reconstruction, respectively. Experimental results show that EEMD-BiLSTM can effectively express the relation between time sequence and adjustable load with a high accuracy.

Comprehensive evaluation for energy saving and emission reduction performance of turbulent drag reducing agent in heating systems

WANG Kaiting, LI Xiaobin, ZHANG Hongna, LIU Shen, QU Kaiyang, LI Fengchen

2022, 44(9): 40-50. doi:10.3969/j.issn.2097-0706.2022.09.006

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The development and technologies of cogeneration heating,solar heating,wind power heating and other heating systems are reviewed. According to the estimation on the energy-saving and emission-reduction effect of turbulent drag reducing agent added in centralized heating systems,the heating systems that are suitable for dosing turbulent drag reducing agent are screened. The results show that adding turbulent drag reducing agent can save about 294 000 yuan, cut 587.2 t standard coal and reduce 1 409.8 t CO₂ emission for a heating system heating with a 1 million m² area in a 150 d heating season. If drag reducing agent can be applied to heating systems national-widely,5.7 million tons of standard coal, 2.88 billion yuan and 14 Mt CO₂ emission can be reduced in a single heating season. The data have proved the significant energy saving and emission reduction effect, as well as the economy of dosing drag reducing agent in centralized heating systems.

Study on difference analysis and sampling inference methods of room temperature spatial characteristics

ZHANG Xu, ZHANG Haohao, GU Jihao

2022, 44(9): 51-58. doi:10.3969/j.issn.2097-0706.2022.09.007

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To pursue the "dual carbon" target, technical transformations in heating industry is overwhelming. In recent years, networked room temperature acquisition devices have been widely used in this industry. Since the collected data of thermal energy users are affected by equipment installation ratio, installation location, systematic error, random error, etc., the room temperature data needs to be analysed and processed before being used to evaluate the heating quality. Based on data cleaning and sampling statistics, difference analysis and sampling inference methods for classical room temperature spatial characteristics are proposed, which provides theoretical guidance for the application of room temperature data from massive heat users in heating quality assessment and heat supply optimization control.

Comprehensive cascade application of "geothermal energy +" in engineering practice

JIANG Shu, LIU Fangfang, LIU Yuanyuan, CHEN Qizhao, LIAN Li, REN Mengnan

2022, 44(9): 59-64. doi:10.3969/j.issn.2097-0706.2022.09.008

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To achieve the goals of carbon peaking and carbon neutrality in China, and to realize energy conservation, emission reduction and clean energy utilization rate improvement, geothermal resource application methods are summarized based on the storage of geothermal energy in China. The geothermal energy application mode has developed from the single and extensive one, such as power generation or heating only,to a cascade and integrated one. According to the conditions of geothermal and solar energy of a scenic spot, a new comprehensive cascade utilization scheme for geothermal energy is designed, in which geothermal water is successively used for power generation, cooling, drying and bathing. Since the temperature of geothermal water is only 80-90 ℃ after heat dissipation in pipes, it cannot be applied for power generation by domestic generator sets. The temperature of geothermal water heated to 93 ℃ by solar energy can be used to generate electricity.Then the temperature of geothermal water drops from 75 ℃ to 65 ℃ after cooling, and reduces from 65 ℃ to 50 ℃ after drying. Finally, it reaches at 50 ℃ and is used for bathing. The "geothermal energy +" comprehensive cascade utilization scheme realizes the “near-zero carbon” power supply of heat pump units, water pumps and other equipment, improves energy utilization rate, reduces operating costs and achieves the sustainable development of energy.

Study on the status quo and development trend of grid-forming converter technology

YU Guo, WU Jun, XIA Re, CHEN Yihui, GUO Zihui, HUANG Wenxin

2022, 44(9): 65-70. doi:10.3969/j.issn.2097-0706.2022.09.009

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Due to the numerous electric and electrical devices and high-penetration new energy in a power system,the system's inertia tends to decrease and its strength and stability are hampered. In order to improve the stability of the system,a grid-forming converter technology which gives play to the flexibility and controllability of converters,compensates for the missing inherent inertia damping and provides reliable voltage and frequency support for the system is proposed.Based on the comparison between grid-forming control and gird-following control technologies,different network construction control strategies are analyzed. Then, the grid-forming high-pressure energy storage technology is introduced.The bottlenecks,challenges and feasible solutions of the technology are pointed out.The research results show that since the grid construction control technology can effectively improve the inertia damping,and provide the voltage and frequency support for the power system,it is promising in new power systems with high proportion of new energy and a large quantity of electronic equipment.

Mechanism design and operation practice of Zhejiang frequency regulation ancillary service market

TANG Qiwen, SHEN Qi, ZHU Jun, SU Yijing

2022, 44(9): 71-77. doi:10.3969/j.issn.2097-0706.2022.09.010

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Grid-connection of large-scale and high-proportion new energy makes higher requirement on the regulation capacity of power systems. To improve the regulation performance of generators,high-quality frequency regulation resources are introduced into the establishment of Zhejiang frequency regulation ancillary service market. On the premise of satisfying the regulation requirements of the power system,the market mechanism comprehensively considers the electric power market and regulation service cost,aiming to minimize the total regulation cost included the opportunity cost. The clearing mode of the electricity-regulation joint optimization market takes regulation bidding price,opportunity cost and regulation performance index as the determining factors and makes the payment according to the actual regulation contribution and regulation effect. The operation results of Zhejiang frequency regulation market show that the market clearing mechanism plays a positive role in selecting high-quality resources,reducing regulation cost,improving regulation performance and increasing revenue sources. Based on the summary on experience, suggestions on developing and improving the ancillary service market are put forward.

Research on fault diagnosis method of power transformers based on multi-scale extreme fusion network

LONG Sicheng, HUANG Zhihong

2022, 44(9): 78-83. doi:10.3969/j.issn.2097-0706.2022.09.011

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To cope with the low accuracy of the power transformer fault diagnosis taking a classification method with fixed-parameter algorithm,a new diagnosis method based on multi-scale extreme fusion network（MEFN）is proposed.There are two main steps in this method.Firstly,the initial diagnosis results are generated by extreme learning machine （ELM） models with different parameter scales.Models are made to analyze the same set of data about dissolved gas,and reflect different statistical characteristics,providing complementary statistical information to power transformer fault diagnosis.Then,the diagnostic results are fused by the decision-level information fusion algorithm,which can improve the accuracy of the power transformer fault diagnosis.Modeling training and test for the proposed method are made based on 487 sets of experimental data.The test results show that,MEFN can detect six types of common transformer faults with a high recognition accuracy of 94%.The recognition accuracy of MEFN is higher than that of support vector machine （SVM） and back-propagation （BP） neural network by 8% and 13%,respectively.The proposed method can meet the requirements on transformer fault diagnosis made by power companies.

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