Table of Content

28 January 2024, Volume 57 Issue 1

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Construction and Operation of Virtual Power Plants

Research and Thinking on the Aggregation and Dispatching Control Framework of Virtual Power Plant's Large Scale Flexible Resources

Tianqi SONG, Zhipeng LV, Zhenhao SONG, Yunting MA, Zhihui ZHANG, Shan ZHOU, Hao LI

2024, 57(1):  2-8.  DOI: 10.11930/j.issn.1004-9649.202306121

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In the background of the "cloud-edge collaboration + Internet of Things", in order to provide a comprehensive resource structure basis and a systematic regulation framework for dynamic performance quantitative analysis of virtual power plant (VPP), this paper conducts a comprehensive survey and systematic analysis of the existing and potential VPP's large-scale flexible resources, and makes a study on the grid access system and grid controllability of the resources. On this basis, a comprehensive systematic aggregation and regulation framework of VPP large-scale flexible resources is constructed, which integrates three paths and adapts to multiple scenarios and conditions. Based on the proposed framework, the reference principles are given for the research on the "Cloud-edge collaboration + Internet of Things" architecture of the VPP dynamic performance quantitative analysis and evaluation system, and the research directions of relevant VPP mechanisms are also discussed.

Analysis and Evolution Trend of Temperature-Sensitive Loads for Virtual Power Plant Operation

Ying ZHOU, Xuefeng BAI, Yang WANG, Min QIU, Chong SUN, Yajie WU, Bin LI

2024, 57(1):  9-17.  DOI: 10.11930/j.issn.1004-9649.202307100

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With the frequent occurrence of extreme weather, the electricity consumption of temperature-sensitive loads is increasing year by year. As a high-quality regulation resource of virtual power plant (VPP), temperature-sensitive loads urgently need to be analyzed for the impact of meteorological changes on them. Due to the influence of abnormal weather such as extreme high temperature and large-scale cold waves, temperature-sensitive loads fluctuate violently. Conventional analysis and prediction methods are not adaptable to the extreme meteorological scenarios. Aiming at the problem of insufficient sample data and prediction accuracy of temperature-sensitive loads under cold wave weather, this paper proposes a daily maximum load prediction method for temperature-sensitive loads under the condition of small sample in cold wave weather. In this method, the TimeGAN is used to expand the small sample data during the cold wave period, and then the CNN-LSTM network is used to predict the daily maximum load during the cold wave period. Finally, the model is verified by the load data of a province in China during the winter period in the past two years. The results show that the prediction results of the proposed model are better than those of other models, with the prediction accuracy of the daily maximum load on the verification set being 99.5%.

A Method for Optimal Selection of High-Capacity Industrial Users for Demand Response Based on Load Step Data Processing Mode

Xiangbo SU, Ruike LYU, Hongye GUO, Qixin CHEN

2024, 57(1):  18-29.  DOI: 10.11930/j.issn.1004-9649.202307044

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In the context of future high penetration of new energy, the uncertainty of supply-demand balance gradually increases. Demand response is an important means of ensuring the balance of power and electricity in the system by tapping into user-side flexible resources. When power sector works on demand response, historical data is needed for an initial assessment of load response potential, so as to select the users with high potential and initiate mobilization efforts. This article focuses on defining and providing a mathematical expression for load step that represents the energy consumption characteristics of industrial users. And then a user selection method for industrial demand response based on load step is proposed. Firstly, an index system for the potential of industrial users' demand response across multiple time scales based on load step is proposed. And then, a user selection model is established to conduct an initial evaluation of different users' response potential, and the k-means algorithm and the nearest neighbor propagation algorithm are used to divide groups, allowing for user selection across different time scales. Finally, a case study is presented based on actual load data from several industrial users in industries such as cement and paper, illustrating the user selection results for industrial demand response using the proposed method.

Evaluation of Virtual Power Plant Flexibility Resources Based on External Characteristic Equivalence

Rui ZHU, Yiding OU, Xiaotian LI, Xingyu LEI, Yuqing ZHOU, Poyang ZHANG, Rui OU

2024, 57(1):  30-39.  DOI: 10.11930/j.issn.1004-9649.202310002

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In order to fully utilize the clean, flexible and economic characteristics of distributed energy(DE), it is needed to efficiently manage its comprehensive and flexible regulation characteristics. However, directly embedding the virtual power plant(VPP) model into the main grid scheduling is prone to the risk of privacy leakage and great computational burden of different energy entities. Therefore, it is necessary to aggregate the multi-category flexibility resources of VPP to calculate their equivalent external characteristics. To this end, this article proposes a VPP flexibility characterization method based on vertex search, which aggregates various flexibility within the VPP into the output power of the VPP nodes, whose mathematical essence is the projection of a high-dimensional flexibility space to a low-dimensional space. Then, by introducing the extrapolation-based vertex search method, we achieve the approximation of the projection by maximizing the Euclidean distance between hyperplanes. Finally, based on the flexibility equivalence method, we propose an evaluation method for VPP flexibility resources to explain the main grid operation cost and optimal solution changes before and after the VPP access from a geometric perspective. The case study shows that the proposed flexibility aggregation model can effectively reduce the operating cost of the main grids, and the proposed VPP value assessment method based on external characteristic equivalence can effectively evaluate the value generated by various types of flexible equipment under small changes of flexibility ranges.

Virtual Power Plant Quotation Strategy Based on Information Gap Decision Theory

Mengfei XIE, Gaoquan MA, Bin LIU, Zhenning PAN, Yunfeng SHANG

2024, 57(1):  40-50.  DOI: 10.11930/j.issn.1004-9649.202308122

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To further enhance the regulatory potential of distributed energy resource (DER), based on the information gap decision theory (IGDT), the bidding methods for virtual power plants (VPPs) participating in demand response (DR) strategies are divided into three strategy models: balanced, conservative and aggressive, and the robust and opportunity functions are designed for each strategy to optimize different types of decisions. Meanwhile, a ε-constraint model is set with consideration of the trade-off between carbon emissions and profits. The advantages and necessity of the proposed method were verified using an IEEE18 node system as the simulation environment. The simulation results show that the conservative VPP can ensure the minimum critical profit when the future price falls into the maximum robustness range; the progressive VPP can benefit from unexpected price fluctuations and achieve expected profits.

Operation Optimization Method for Virtual Power Plant Participating in Clean Heating Based on Time-of-Use Tariff of Wind Power

Yunchen FENG, Heping JIA, Min YAN, Genzhu LI, Le LIU, Dunnan LIU

2024, 57(1):  51-60.  DOI: 10.11930/j.issn.1004-9649.202306102

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With the proposal of carbon peaking and carbon neutrality targets, the rapid development of wind power is facing the prominent accommodation problem due to wind power’s randomness and volatility. Regenerative electric heating is a primary heating mode adopted in Northern China, and the virtual power plant (VPP) is the primary demand-side resource aggregation technology. The VPP, which aggregates regenerative electric heating, can provide a solution for wind power accommodation and increasing the wind power usage rate. In this regard, this paper proposes a wind power based time-of-use tariff division method to realize the optimal operation of VPP aggregating regenerative electric heating to participate in time-of-use tariff-based clean heating trading. Firstly, the transaction mode of VPP aggregating regenerative electric heating users to participate in wind power heating is described. Secondly, with consideration of the thermal inertia, the regenerative electric heating and buildings are modeled in detail, and a time-of-use tariff method based on hierarchical agglomerative clustering algorithm is proposed. A load fuzzy response model is established based on Weber-Fechner law, and a VPP operation optimization model is constructed with multi-objective of maximum comprehensive benefits of multiple entities, minimum wind curtailment and smallest load volatility. The wind power accommodation effects and VPP benefits are analyzed through case study. It is verified that the proposed method can effectively promote the wind power accommodation and raise the enthusiasm of multiple entities.

Collaborative Optimization Strategy for Virtual Power Plant Participating in Energy and Ancillary Service Market

Ting ZHOU, Yudong TAN, Jin SUN, Ming WEN, Jing LIAO, Yang LI, Gong LIU, Dunnan LIU

2024, 57(1):  61-70.  DOI: 10.11930/j.issn.1004-9649.202307050

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As a flexible resource with energy storage characteristics, virtual power plant (VPP) is becoming more and more important in cooperating with the grid for peak load shaving and new energy accommodation. However, its poor economy and efficiency in market operation directly leads to its lack of enthusiasm in participation in the market. In view of this, this paper proposes a collaborative work strategy for VPP participating in electricity energy market and auxiliary services market. Firstly, based on the spot market electricity price and the aggregation of VPP, the strategy for the VPP participating in the market in each time period is determined. Secondly, taking the maximum revenue of VPP as the goal, the dynamic programming method is used to establish a collaborative optimization model of VPP participating in the spot electricity energy - FM market under multi-time scale. Finally, through simulation, we analyzed and compared the revenue and utilization rate of the VPP participating in the separate market and the joint optimization. The shapely value method is used to analyze the revenue sharing of various resources participating in the aggregation of the VPP, so as to validate the feasibility and validity of the scheme proposed in this paper.

Improved PBFT Consensus Mechanism for Multi-virtual Power Plant Transactions

Shuhan ZHANG, Qian AI, Xiaolu LI, Di WANG

2024, 57(1):  71-81, 157.  DOI: 10.11930/j.issn.1004-9649.202304046

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The diversity of distributed energy investment entities makes it more difficult to build trust in the process of interaction between resources, so it is necessary to explore the interaction mode of multi-virtual power plants and build a corresponding trust system. Based on the main and side blockchain technology, this paper constructs an overall architecture for the multi-virtual power plant transaction model and clarifies the transaction process of multi-virtual power plant. A cross-chain channel is constructed through the main side anchoring technology to realize the on-chain collaborative operation mode of multi-virtual power plants. To solve the problems of the lack of trust environment and the decline of blockchain performance caused by the low enthusiasm of nodes to maintain the blockchain network environment, a differentiated credit evaluation index is proposed to standardize node behavior based on different node functions, and the practical byzantine fault tolerance (PBFT) algorithm is improved using this index. Experimental results show that the consensus algorithm improved by the differentiated credit evaluation indicators can build a trust environment and improve the consensus efficiency under the proposed multi-virtual power plant architecture.

Calculation of Day-Ahead Frequency Regulation Capacity for Virtual Power Plants Based on Analytical Target Cascading Method

Ying ZHANG, Yan WEN, Yu JI, Juan ZUO, Wenbo WANG

2024, 57(1):  82-90.  DOI: 10.11930/j.issn.1004-9649.202303003

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In recent years, with the large-scale integration of clean energy such as photovoltaic and wind power, the power grid is under growing stress from the demand of the system's frequency regulation. Meanwhile, the access of distributed resources such as micro gas turbines and energy storage with stable frequency regulation performance has provided new ideas to improve the system's frequency regulation capability. Therefore, an optimized scheduling model based on target cascade analysis is proposed in this paper, which aims to aggregate distributed resources through virtual power plants to participate in the frequency regulation ancillary service market. Specifically, a bi-level optimization scheduling model is established for both the distribution network layer and the virtual power plant layer. The distribution network coordinates the complementary resources of the virtual power plant to improve resource utilization efficiency. Then, the virtual power plant conducts optimization scheduling among internal participants, and the chance-constrained programming is applied to constrain the uncertainty of the frequency regulation signal. Finally, the target cascade analysis method is used to solve the established model, and the effectiveness and feasibility of the optimization scheduling model are verified through simulation examples. The results has demonstrated the effectiveness of the proposed day-ahead dispatching model. Moreover, the virtual power plant can effectively reduce its operating cost by participating in the regulation auxiliary service.

Real Time Optimal Dispatch of Virtual Power Plant Based on Improved Deep Q Network

Chao ZHANG, Dongmei ZHAO, Yu JI, Ying ZHANG

2024, 57(1):  91-100.  DOI: 10.11930/j.issn.1004-9649.202307006

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The deep reinforcement learning algorithm is data-driven and does not rely on specific models, which can effectively address the complexity issues in virtual power plant (VPP) operation. However, existing algorithms are difficult to strictly enforce operational constraints, which limits their application in practical systems. To overcome this problem, an improved deep Q-network (MDQN) algorithm based on deep reinforcement learning is proposed. This algorithm expresses deep neural networks as mixed integer programming formulas to ensure strict execution of all operational constraints within the action space, thus ensuring the feasibility of the formulated scheduling in actual operation. In addition, sensitivity analysis is conducted to flexibly adjust hyperparameters, providing greater flexibility for algorithm optimization. Finally, the superior performance of the MDQN algorithm is verified through comparative experiments. An effective solution is provided to address the complexity issues in the operation of VPP.

Optimal Scheduling Strategy for Virtual Power Plant Considering Electricity-Gas-Heat Coupling and Demand Response

Shijie WANG, Tianbo FENG, Ning SUN, Ke HE, Jiawen LI, Cheng YANG, Haoyang CUI

2024, 57(1):  101-114.  DOI: 10.11930/j.issn.1004-9649.202309050

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The combined heat and power (CHP) units can not meet the maximum heating efficiency and power peak shaving demand in winter at the same time, and there exit problems of insufficient power generation output regulation ability. In view of the above problems, an optimal scheduling strategy for virtual power plant (VPP) is proposed considering electricity-gas-thermal energy coupling and demand response. Firstly, in order to improve the downward peak shaving capacity of CHP units, the P2G equipment and carbon capture technology are introduced to construct a new CHP coupling model. Secondly, in order to improve the operation flexibility of the system, considering the peak-valley time-of-use electricity price and heat price, a comprehensive demand response mechanism is established. And then, in order to reduce the generation cost of the system, the electric and thermal energy storage devices are introduced, and a VPP bi-level optimization model is established with the goal of minimizing the total cost of the system and the operation cost of the electric and thermal energy storage devices. According to the Karush-Kuhn-Tucher ( KKT ) condition of the lower-level optimization model, the bi-level model is transformed into a single level and linearized for solution. The results show that the carbon emissions, operation cost and new energy consumption rate of the proposed method are optimal, which improves the downward peak shaving capacity of the CHP units and meets the low-carbon and economic requirements of the system.

Low-Carbon Planning and Operation for New-Type Power Systems

Optimal Dispatch Strategy of Power and Electricity Balance Based on Multi-Energy Complementation

Zhiyuan SUN, Boya PENG, Yan SUN

2024, 57(1):  115-122.  DOI: 10.11930/j.issn.1004-9649.202304064

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In the modern power system with high penetration of renewable power generation, giving full play to the potential of coordinative and complementary operations between different power generation sources and different energy storage equipments, can alleviate the huge stress on the system's power and electricity balance caused by the volatility of new energy output. This paper proposes an optimal scheduling strategy for power and electricity balance considering multi-energy complementation, such that multi-energy dispatch is coordinated under different time scales and hence the overall operating performance of the system can be improved. First, according to the seasonal and short-term fluctuation characteristics of new energy output, by taking into account the medium and long-term electricity balance as well as short-term power balance, the multi-time scale double-layer optimal scheduling system model is established. Then, through the optimization of the charging and discharging strategy of the hybrid energy storage system, the operation of multiple energy storages is coordinated efficiently and the economic benefit of system operation can be boosted. Finally, case studies are performed to verify the effectiveness of the proposed method on the modified IEEE-RTS 1979 system model. The results indicate that the energy complementation of different time scales and the coordination of different energy storage equipment can be applied to improve the economic benefits of the system while maintaining system power balance.

Reactive Power Optimization for Loss Reduction of Distribution Network Considering Interactions of High Penetration Level of Multiple Regulating Energy Resources

Xiping MA, Yaxin LI, Chen LIANG, Xiaoyang DONG, Rui XU

2024, 57(1):  123-132.  DOI: 10.11930/j.issn.1004-9649.202308071

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Under the background of high proportion distributed resource access, in order to fully explore the loss reduction potential of reactive power regulation of the distribution network and reach the target of loss reduction through reactive power optimization technology more comprehensively and precisely, this paper proposes a multi-objective reactive power optimization and loss reduction method considering the coordination and interaction of multiple regulating resources in the distribution power grid. Firstly, regarding the impact of harmonics on line loss in the context of high proportion of distributed resource access, a distribution network line loss calculation model considering harmonic loss is put forward. On this basis, the reactive power regulation capability of multiple regulating resources is analyzed, and a distribution network reactive power optimization scheduling model is established with the objective set as the minimization of line loss and the maximization of static voltage stability. By developing the reactive power optimization strategy of multiple distributed resources such as multiple adjustable load, distributed power supply, energy storage and reactive power compensation equipment, the goal of minimizing the system line loss under the comprehensive consideration of the static voltage stability requirements of the distribution network is achieved. Finally, through the simulation analysis of the improved IEEE 33-bus system, the results show that the full interaction of multiple regulating resources can effectively improve the system voltage stability, reduce the system loss, and ensure the secure and economic operation of the distribution network.

Whole Process Carbon Footprint Traceability of Dalian City Based on STIRPAT Model

Na ZHANG, Lin ZHAO, Wenying SHANG, Xing JI, Jia LI, Yuhui HUANG

2024, 57(1):  133-139.  DOI: 10.11930/j.issn.1004-9649.202310008

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Taking Dalian city as the research object, this paper measures the carbon footprint of energy consumption in Dalian city from 2010 to 2020, calculates the value of carbon footprint and carbon footprint intensity as well as the ecological pressure intensity, and analyzes the carbon emissions of the key industries with the data of Dalian city in 2019. The research results show that: (1) Based on energy types, petroleum is the largest, coal is the second and natural gas is the smallest in produced carbon footprint from 2010-2020; based on key industries, the power industry is the largest and the petrochemical industry is the second in produced carbon footprint in 2019; the energy utilization efficiency of Dalian city was improving from 2010-2014, and the output value of unit land area increased quickly with the economic value created by carbon footprint surpassing the growth rate of GDP, indicating that economic growth at this stage is independent of fossil energy. (2) The carbon footprint produced by various energy consumption and its percentage in 1995-2006 period decreases from coal to oil to natural gas, and the carbon footprint percentage produced by coal consumption decreases year by year while the oil and natural gas show the opposite.

Hierarchical Cluster Control Method for Flexible Load in Distribution Network Based on Improved Alternating Direction Multiplier Method

Juncheng ZHANG, Min LI, Zhiwen LIU, Jing TAN, Yigang TAO, Tianlu LUO

2024, 57(1):  140-147.  DOI: 10.11930/j.issn.1004-9649.202309093

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With the rapid development of various load side resources such as adjustable loads and electric vehicles, how to accurately regulate them has become an important research point. In order to give full play to the regulation ability of flexible loads in distribution networks, a hierarchical cluster regulation method for flexible loads in distribution networks based on improved alternating direction multiplier method is proposed. Firstly, the flexible loads are clustered hierarchically using the BIRCH clustering algorithm. Secondly, based on Nash negotiation theory, the original problem is decomposed into two sub problems: cost minimization and revenue allocation, and a flexible load cluster regulation model for distribution networks is established. Then, an improved alternating direction multiplier method is proposed by introducing an adaptive variable parameter acceleration factor. Finally, a simulation example is used to verify the effectiveness of the proposed method. The results show that the proposed method can effectively achieve cluster regulation under access of large-scale flexible loads, and its convergence performance is better than the conventional methods.

Robust Simplified Modeling of Microgrid in the Context of Constructing New Power Systems

Daxing WANG, Yan Ning, Jingpei WANG, Yang XU, Jun BI, Mingbiao ZHOU, Peng WANG

2024, 57(1):  148-157.  DOI: 10.11930/j.issn.1004-9649.202307072

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The development of microgrid with high proportion of renewable energy is one of the important means to construct new modern power systems so as to achieve energy security and low carbon emissions. However, amid the analysis of the dynamic characteristics of microgrid-integrated power system, the current equivalent models appear to be not robust enough. Specifically, these models can well reproduce the behaviors of actual system under the faults in training set, they may not be able to reflect actual system responses under other unknown faults (non-training faults). In regard to this, k-means++ is introduced first to effectively distinguish the typical operation condition of microgrid such that the randomness and time-varying characteristics of the system can be represented. Next, key parameter selection-based parameter identification method is applied to avoid the issue of multiple solutions in parameter identification process. Then, the convolutional neural network is used to generalize the model parameters with respect to different typical system operation conditions. Additionally, online matching of equivalent model parameters is achieved by virtue of Fisher discriminant analysis. Finally, the effectiveness of the proposed method has been verified in a real microgrid system in China.

Multi-stage Fault Recovery Strategy for Active Distribution Networks Based on Dynamic Islanding

Xundong GONG, Weijia GUO, Chen YANG, Li ZHOU, Xiaofeng DONG, Junpeng ZHU

2024, 57(1):  158-166.  DOI: 10.11930/j.issn.1004-9649.202311012

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Frequent occurrences of extreme weather impose higher demands on the resilience of distribution networks, and traditional fault recovery strategies are inadequate to fully unleash the potential of active distribution networks. Therefore, a multi-stage fault recovery strategy for active distribution networks based on dynamic islanding is proposed. Firstly, an analysis is made on the feasibility region of distribution network reconstruction based on dynamic islanding, and with consideration of the temporal characteristics of distributed generations such as non-black start units (NBSU), an upper-level load restoration model is established to determine the multi-stage network topology plan. Subsequently, the lower-level model is established to provide the generation plans, which is used to examine the feasibility of the multi-stage network topology plan at the islanded flow level. And then, the established models are solved using the improved discrete particle swarm combined algorithm with the CPLEX solver. Finally, a 43-node urban distribution network is used for simulation to verify the effectiveness and superiority of the proposed method in improving resilience.

Topology Identification Method for Active Distribution Network Based on Weighted Minimum Absolute Value State Estimation

Guang MA, Wen ZHU, Huijie GU, Huashi ZHAO, Xiqi HE, Shijie CHEN

2024, 57(1):  167-174.  DOI: 10.11930/j.issn.1004-9649.202307049

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In the state estimation of distribution systems, it is difficult to fully monitor numerous network devices, resulting in insufficient measurement data. Besides, frequent topology switching urgently requires efficient algorithms. Therefore, this paper proposed an effective weighted minimum absolute value state estimation method for distribution network topology identification. Firstly, the traditional weighted minimum absolute value state estimation method based on linear programming was improved to improve the calculation efficiency. Secondly, a weighted minimum absolute value state estimation method based on mixed integer linear programming was formed by adding supplementary variables and constraints to the reformulated weighted minimum absolute value state estimation method to adapt to the topology identification problem. The simulation results on four example systems validate the excellent performance of the proposed topology identification method in different amounts of real-time measurements, high pseudo measurement errors, measurements corrupted by bad data, and unknown branch state scenarios.

Clean and Efficient Power Generation Technology for Carbon Peak and Carbon Neutrality

Carbon Emission Reduction Calculation Method for Pumped Storage Based on CCER Rules

Sanmin XU, Gong ZHANG, Fang WANG, Lei PU

2024, 57(1):  175-182.  DOI: 10.11930/j.issn.1004-9649.202310032

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Pumped storage plays a significant role in emission reduction for accomodating new energy and achieving clean replacement of peak shaving power sources. This paper describes the current situation of pumped storage participating in carbon quota trading market and voluntary emission reduction trading market, and analyzes the emission reduction mechanism of pumped storage in the process of reducing wind and photovoltaic curtailment and realizing clean replacement of peak-shaving power sources. Based on the Chinese certified emission reduction (CCER) methodology system, a pumped storage carbon emission reduction project scenario and calculation model is established, and the actual carbon emission reduction by typical pumped storage stations in 4 regions of China is calculated. The results show that the annual emission reduction by the pumped storage stations in East China, Central China and Northeast China is about 100,000 to 300,000 tons. Finally, the key factors affecting the carbon reduction effect of pumped storage are summarized as the proportion of thermal power in the region and the comprehensive efficiency of the pumped storage stations. This research can provide a reference for the development of CCER methodology for pumped storage and carbon emission reduction calculation.

Optimal Dispatch of Power System with P2G-Wind-Thermal-Nuclear-Carbon Capture Units

Wenhao CHAO, Zhi YUAN, Ji LI

2024, 57(1):  183-194.  DOI: 10.11930/j.issn.1004-9649.202306048

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In power systems consisted of wind power generation (WPG), thermal, nuclear, carbon capture units, the peak shaving depth could be inaccurately selected when nuclear power units participate in peak regulation. In addition, the excessive wind power curtailment could also be an issue. In this paper, a linearized peaking depth model for nuclear units is proposed considering their co-operation with power-to-gas (P2G), WPG, thermal, and carbon capture units. First, based on the load tracking mode of nuclear power units, the accuracy of peak shaving depth selection could be improved by adding continuous variables. Secondly, the joint operation mode of the carbon capture power plant-P2G and demand response resources could facilitate the accommodation of WPG. Finally, the minimization of system comprehensive operation costs is selected as the overall objective function. At the same time, the carbon trading mechanism is considered to build the simulation model on the Matlab platform to verify the effectiveness of the proposed model. The results show that compared with the multi -source combination system of fixed peak-module gears, the proposed multi-source combined system operation mode can ensure the safe and stable operation of the nuclear power unit while achieving WPG utilization. The carbon emissions and comprehensive operating costs have decreased by 13.74% and 6.27%, respectively, which improves the low-carbon and economics of system operation.

Study on the Thermo-economic Performance of a Integrated Energy System Based on Hydrogen-fueled Gas Turbine

Chengshuai HUANG, Jian LIANG, Bo LI, Yaxin YANG, Yang HU, Erren YAO

2024, 57(1):  195-208.  DOI: 10.11930/j.issn.1004-9649.202310023

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In order to achieve low-carbon and high-efficiency operation of natural gas stations driven by hydrogen, a novel integrated energy system is proposed in this paper. The steam cycle is used to recover the waste heat generated by gas turbines. The electrical energy is used to drive the solid oxide electrolysis hydrogen production system to produce hydrogen, and then the mixture of methane and hydrogen is used as the fuel of gas turbine, and the compressed air energy storage technology is used to convert renewable energy into stable electrical energy output. The calculation results indicate that under design conditions, the energy efficiency, exergy efficiency and levelized cost of energy are 85.66%, 41.37% and 294.70 Yuan·(MW·h)^–1, respectively. Parameter sensitivity analysis shows that the operating parameters of gas turbine pressure ratio, gas turbine hydrogen blending ratio, steam cycle low-pressure boiler pressure, steam cycle extraction coefficient, compressed air energy storage technology energy release power have significant impact on system thermodynamic performance, while the operating parameters of gas turbine pressure ratio, gas turbine hydrogen blending ratio, and steam cycle extraction coefficient have significant impact on system economic performance.The multi-objective optimization results indicate that the optimal exergy efficiency and standardized unit energy cost of the system are 42.31% and 284.33 Yuan·(MW·h)^–1, respectively.

Thermodynamic Analysis of CCHP with Compressed Air Energy Storage and Enhanced Geothermal Technology

Jian LIANG, Meng WANG, Yaxin YANG, Yang HU, Erren YAO

2024, 57(1):  209-218.  DOI: 10.11930/j.issn.1004-9649.202306024

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To further improve the efficiency and supply flexibility of compressed air energy storage (CAES), a novel combined cooling-heating-power (CCHP) system integrating CAES and enhanced geothermal system is proposed based on the law of energy cascade utilization. The thermodynamic models of each component within the system are established. The impacts of crucial parameters on the thermodynamic performance of the system are investigated. The multi-objective optimization is carried out to pursue the optimal Pareto fronts of exergy efficiency and total investment cost per total output energy. The results indicate that the expander and heat exchanger are the two key components in the system, and the thermodynamic performance of the above two components could improve the performance of the system significantly. Finally, the optimum exergy efficiency of the system is 55.73%, and the best total investment cost per total output energy is 6378.94 yuan/kW. The optimum values of energy efficiency and energy saving ratio are 6.1% and 10.68%, respectively, which are higher than those of values under design condition.

The Influence of Unevenly Distributed Powder on a 1000 MW Opposed Firing Boiler and the Counter Measures

Ming GE, Zhicheng JIANG, Zhijia LV, Jiayang WANG, Zhaohong QIU, Shouyu ZHANG

2024, 57(1):  219-229.  DOI: 10.11930/j.issn.1004-9649.202304081

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An experimental study was carried out on deviant combustion of a 1000 MW opposed firing boiler. It was found that the powder deviation is the main factor. The distributions of powder amount and pulverized coal fineness demonstrated a typical interval distribution trend as well as a positive correlation. The factors such as uneven distribution of powder amount, deviation of pulverized coal fineness and air distribution characteristics of secondary-air-box led to the deviant combustion in the furnace. In order to alleviate the deviant combustion in the furnace, the fineness of pulverized coal, the air distribution of the burner, the swing angle of the burning wind, and the opening of closing-to-wall air were adjusted. It was found that the adjustment of burning wind opening and swing angle have the most significant influence. The decrease of burning wind opening and the swing angle of burning wind from the middle to both sides were helpful to alleviate the deviant combustion. After adjustment, the deviation of steam temperature at screen superheater outlet was reduced from 40 ℃ to less than 10 ℃. Under the full load condition, the lowest point of oxygen concentration at the outlet of the economizer was increased from less than 1% to more than 2%. The highest point of CO concentration decreased from more than 5000 μL/L to less than 500 μL/L. The deviant combustion was greatly alleviated. The combustion adjustment could provide reference for the same type of units to solve the problem of deviant combustion.

Power System

System, Applications and Challenges of Digital Twin Technology in Energy Internet

Zhao LIU, Qingkai SUN, Zekai XU, Xiaoyu WU, Xiaojun WANG, Jinling LV

2024, 57(1):  230-243.  DOI: 10.11930/j.issn.1004-9649.202303037

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With the gradual upgrading and transformation of traditional energy interconnection system to energy Internet, it is difficult to describe its high dimensionality, nonlinear and multi energy coupling characteristics if only based on the mechanism modeling method. Digital twin technology can accurately map the real system to the virtual space, which is of great significance to the realization of the feature description, operation analysis, monitoring optimization and intelligent decision-making of the energy Internet. Firstly, from the development of digital twin technology, an analysis is made on the digital twin technology system in the energy Internet, and a hierarchical technology system framework is proposed, which covers “multi-source data acquisition-model building-platform support-intelligent interaction” and the application value of digital twin technology in the energy Internet is elaborated. Secondly, the typical applications of the digital twin technology in energy Internet and the current development bottleneck are introduced in detail. Finally, the development route of the digital twin technology in energy internet is summarized and envisaged.

Research and Application of Control Strategy Optimization for Regional Standby Automatic Switching System of Petal-Type Distribution Network

Baocheng FENG, Zhen JIN, Wei HOU, Guangfu XU

2024, 57(1):  244-254.  DOI: 10.11930/j.issn.1004-9649.202303060

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In view of the problem that the regional sandby automatic switching system will not be able to realize the “petal” power supply restoration if the fault cannot be reliably isolated by protection, when fault occurs with the petal-type distribution network, a new control strategy for the regional standby automatic switching system is thereby proposed based on the idea of control strategy equation. The new control strategy actively carries out fault isolation and realizes, through information exchange between adjacent switch rooms, the “petal” function of restoring power supply and the intelligent load switching function in each switch room in case of line overload after power supply restoration. The information exchange also ensures the effectiveness of the load switching function of the safety and stability system. At the same time, this paper proposes a backup protection locked by the main protection, which solves the setting and coordination difficulty of the backup protection and the large workload during the operation of the “petal” inner closed loop. The field application has verified the effectiveness of the proposed new control strategy, which has certain reference significance for the research of the control strategy of the regional standby automatic switching system in other distribution networks.

SCD Two-Layer Vectorization and Change Verification Technology Based on Hash and Edit Distance Algorithm

Yuanbo YE, Jiwen WANG, Wei WANG, Yurong MAO, Zhihua WANG

2024, 57(1):  255-262.  DOI: 10.11930/j.issn.1004-9649.202308062

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In view of the sharp increase in operation and maintenance workloads caused by changes in substation configuration description (SCD) file and unclear configuration of secondary equipment in intelligent substations, a two-layer vectorization and change verification technology based on hash and edit distance algorithm for SCD is proposed. Firstly, considering the initiation and verification of file changes, a two-layer vector model for SCD file parsing is constructed using node elements, verification codes and element attributes. Secondly, the hash algorithm is used to transform the constructed text vector model into a hash string vector model. Then, the edit distance algorithm is introduced to calculate the two-layer vector model similarity between the original file and the changed file. Based on the comparison of the first layer similarities, the second layer verification initiation criterion is formed, and the change verification is achieved based on the second layer similarity in combination with the backtracking path method. Finally, the effectiveness of the proposed algorithm was verified through numerical analysis.