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Table of Content

    25 November 2022, Volume 44 Issue 11
    Coordinated Economic Dispatch
    Electric vehicle priority dispatch policy based on comprehensive dispatchable potential assessment model
    LI Hao, JI Zhenya, LIU Xiaofeng, ZHANG Shiwei, BAO Yuqing, WANG Wei
    2022, 44(11):  1-11.  doi:10.3969/j.issn.2097-0706.2022.11.001
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    The number of electric vehicles is mounting in the process of achieving "dual carbon" target. And their charging and discharging behaviours significantly impact the operation of power grid. In response to the numerous control instructions given to schedule every single electric vehicle(EV), considering from EV side and distribution network side, a dispatchable capacity assessment index and a benefit assessment index are proposed. And a comprehensive dispatchable potential assessment model for EVs is established. Then, EVs can be divided into different groups and those in dispatch priority zones will be given schedule instructions preferentially. To alleviate the difficulty brought by EV mobility between regions to the model solving, an EV grouping method based on W-GAN and k-means clustering algorithm is used. Based on three peak load regulation cases, the dispatchable potential and dispatch performance of four EV groups are analysed. The simulation results show that the dispatchable capacity assessment index and the dispatching benefit assessment index of the proposed method are reasonable. Giving scheduling priority to the divided EV dispatch priority zones selected by the integrated dispatchable potential assessment model can accomplish peak load regulation with less dispatching times.

    Strategy for large-scale electric vehicles cluster scheduling considering peak-shaving cost
    WANG Kangping, HUANG Qucan, ZHANG Xingke, WAN Fangru, WEI Chaoyang, LIU Caihua, TIAN Hao, WEI Cong, ZHOU Xia
    2022, 44(11):  12-19.  doi:10.3969/j.issn.2097-0706.2022.11.002
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    Large-scale grid-connection of new energy and electric vehicles(EVs)leads to volatile power fluctuation and excessive peak-shaving cost. In order to alleviate the pressure of peak shaving and realize the safe and economic operation of the power grid,an EV cluster scheduling strategy considering peak-shaving cost is proposed. Based on the interaction mode between EVs and the power grid and their charging and discharging characteristics,EV load models can be classified into three groups,uni-directional,bi-directional and battery swapping models. Then,an EV peak-shaving pricing model considering the impact of EV participation on peak-shaving cost is constructed. Aiming at the minimal load fluctuation, the pricing strategy for cluster scheduling of EVs in a regional power grid is proposed, and the dynamic electricity price considering EV participation in peak shaving is formulated according to the results obtained from the peak-shaving pricing strategy. EV loads are scheduled with the smallest sum of the expected values of various operating costs as the objective. The effectiveness of the peak load regulation strategy and the economy of the pricing strategy are verified by the simulation result of an improved regional power grid system

    Overall day-ahead scheduling optimization for pumped-storage power stations considering the uncertainty of wind and photovoltaic power prediction
    OUYANG Ting, CAI Ye, WANG Weiyu, TANG Xiafei, TAN Yudong
    2022, 44(11):  20-27.  doi:10.3969/j.issn.2097-0706.2022.11.003
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    In order to reduce the impact of uncertain forecasting on renewable energy outputs on the economy of day-ahead optimization scheduling, an overall day-ahead scheduling optimization model for pumped storage power stations considering the uncertainty of wind and photovoltaic power prediction is proposed. Firstly, the wind speed and solar irradiance are predicted based on Weibull distribution and Beta distribution,respectively. The predicted outputs of wind and photovoltaic power are obtained. The multi-scenario stochastic programming is adopted to solve the uncertainty of day-ahead wind and photovoltaic output predictions. Secondly, based on the scenario set of the predicted day-ahead wind and photovoltaic outputs and the load prediction curve, the overall day-ahead dispatching optimization model for the pumped storage power station considering wind, PV and thermal power is established. Taking steady net load and the minimum total peak-shaving cost as objectives, the water pumping and power generation outputs of the storage power station and the output of the thermal power units are obtained. Verified by the data from a province in China,the model can fully smooth the fluctuation of new energy outputs, reduce the peak load regulation pressure of thermal power units, and improve the economy of the system.

    Load Scheduling and Market Mechanism
    Development of the simulation system for microgrids based on programmable logic software
    CHEN Yufeng, WANG Jiahua, XU Jian, JI Xiaopeng
    2022, 44(11):  28-35.  doi:10.3969/j.issn.2097-0706.2022.11.004
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    Since a microgrid contains many distributed generators with different characteristics and follows complex operation and control strategies, its control system needs to be verified by various experimental approaches. Dynamic simulation experimental platform(DSEP) and hardware-in-the-loop simulation (HILS) are rarely used in engineering scenarios due to their large sizes and high costs. A simulation system based on programmable logic software for the microgrid including distributed generators, loads and controllers is established. In the simulation test on an isolated microgrid,the distributed generator modelling,system control strategy design,software debugging and simulation of the microgrid are carried out, and the control theory and control logic are tested and verified. The control logic after the simulation and verification can realize the dynamical loading and operation in the controller directly.

    Day-ahead electricity price prediction model based on GRU optimized by crossover optimization algorithm
    ZHAI Guangsong, WANG Peng, LIANG Pengxun, XIE Zhifeng, YIN Hao
    2022, 44(11):  36-42.  doi:10.3969/j.issn.2097-0706.2022.11.005
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    The penetration rate of renewable energy is rising with the development of new energy system.In view of the mounting number of features and fluctuation of electricity price, a combined prediction model based on gated recurrent unit (GRU) optimized by crossover optimization algorithm(CSO)is proposed,to improve the prediction accuracy of day-ahead electricity price. Firstly, the correlation between electricity price and features is analysed by mutual information (MI) method and those features with high correlation are extracted. The electricity price sequence is decomposed into several components by variational modal decomposition (VMD). Features extracted from the superimposed components are sent to GRU prediction model for prediction. CSO algorithm can optimize some parameters of the model and avoid the model from falling into local optimum. The final predicted electricity price is obtained by superimposing the prediction results of different components. Verified by the experimental data of Nordpool, a power market leader in the Nordic region, the proposed prediction method is more accurate than others.

    Optimization strategy of microgrid responding users' bounded rational demand
    XU Zhirong, ZHANG Gaorui
    2022, 44(11):  43-49.  doi:10.3969/j.issn.2097-0706.2022.11.006
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    Microgrid aggregates power sources,energy storage equipment and terminals and coordinated schedules their operation, in order to achieve resources optimization. Since the decision-making of electricity users is not completely rational in general,a bounded rationality optimization model for decision-making on electricity consumption is established based on the transferable electricity usage and the span of transfer. The half-Γ-shaped membership degree function is used to address the fuzzy relationship and varied dimensions between microgrid operation cost function and bounded rationality optimization function.Finally,a GOJaya(Global Optimization Jaya)algorithm with global optimization capability is proposed,which improve the search speed in the early stage and search inaccuracy in the later stage of the conventional algorithms.The results show that the proposed optimization strategy has good applicability in microgrid optimized operation,and the GOJaya algorithm is superior to Jaya algorithm and GA algorithm in solving speed and accuracy.

    Classification and characteristic analysis of adjustable resources on the user side
    ZHENG Qingrong, LU Yingjie, XIANG Jiani, CHEN Yuyang, GONG Feixiang, YUAN Jindou, WU Yingjun
    2022, 44(11):  50-55.  doi:10.3969/j.issn.2097-0706.2022.11.007
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    Since the rapid growth of load has posed a huge challenge to the stability of the power system, supply-side regulation and control capabilities of traditional methods have gradually been weakened. Therefore, demand response, as an important means to alleviate the imbalance between supply and demand during power peak periods, has received increasing attention. Demand response can improve the stability of the grid by scheduling the adjustable loads on demand sides and reducing partial load capacity in peak load periods. Therefore, it is of great significance to study adjustable resources on load sides. Based on the existing researches on user-side load classification, a classification method for user-side resources according to their energy supply and consumption attributes is proposed. By analyzing the typical loads of different energy supply and consumption attributes and their characteristics, a resource library of loads with different attributes has been established, which lays a foundation for in-depth research on demand response.

    Carbon emission characteristics model of thermal power units for environmental economic dispatch
    WU Junda, ZHAO Yi, SUN Wenyao
    2022, 44(11):  56-62.  doi:10.3969/j.issn.2097-0706.2022.11.008
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    In the backdrop against carbon emission reduction campaign,constructing a CO2 emission reduction characteristics model of thermal power units for power system environmental economic dispatch is crucial for achieving the goals of carbon peaking and carbon neutrality. According to the investigated data on the proportion of thermal power units in China, relationships between the units' capacity, load rate and CO2 emission intensity are studied and the CO2 emission intensities of the units of different capacities and under different load rates are compared. Based on least square method, a model for CO2 emission reduction and load characteristics of thermal power units is made, and its satisfaction index is determined by bi-objective optimization algorithm. The mode can be solved by transforming the bi-objective problem to single objective problems. Based on the data of nine power units running for 24 h,a CO2 emission reduction and load characteristics model is made for the units. Being able to reconcile the contradiction between coal consumption and CO2 emission, the model is proven to be pragmatic and reliable for power system economic emission dispatch.

    Optimized Operation and Control of Integrating Energy Systems
    Study on dynamic optimal energy flow of a source-network-load-storage integrated energy system considering its economic benefit
    YANG Mei, ZHOU Xichao, WEI Qiang, LIANG Dawei, WU Maoqian
    2022, 44(11):  63-69.  doi:10.3969/j.issn.2097-0706.2022.11.009
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    With the large-scale access of new energy,the power system shows the characteristics of "two-side randomness","two peaks" and "two high proportions". In order to ensure the safe,stable and efficient operation of the power system,it is necessary to accelerate the integration of source,network,load and storage and the complementary development of multiple energy. A large amount of new energy can be consumed by Integrated Energy Systems(IESs). Energy interactions between energy subsystems can be more frequent in an integrated energy system. In order to obtain the data such as interaction characteristics,response time scale and regulation rate of in source,network,load and storage links, the dynamic optimal energy flow analysis of the integrated energy system is made with the goals of economic benefit and high efficiency. Firstly,the mathematical models of the power grid,natural gas network and thermal system in the IES are established,respectively. Then, the overall dynamic analysis model of the multi-energy flow system considering the energy interaction between source, network, load and storage links is constructed, aiming at the lowest economic cost and the highest efficiency of these links. Finally,based on the case study of an integrated energy system including a 6-node power system and a 6-node heating system,its dynamic response and regulation characteristics of the multi-energy flow system are analyzed,which verifies the correctness and effectiveness of the proposed model.

    A scheduling method for suppressing wind power fluctuation of data centers considering wind power uncertainty
    ZHAO Jianli, XIANG Jiani, WANG Weidong, CHEN Ke, CHEN Jinjuzheng, WU Yingjun
    2022, 44(11):  70-78.  doi:10.3969/j.issn.2097-0706.2022.11.010
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    The security and stability of a power system can be compromised by the output fluctuation brought by wind power grid-connection. Thus, considering the uncertainty of wind power prediction,a wind power output fluctuation suppression model is proposed based on a data center's delay calculation. The model is divided into two stages. In the first stage,based on the predicted wind power output,the data center load curve need to be smoothed in the premise of fluctuation suppression.In the second stage,the scheduling scheme is adjusted to meet the wind power output suppression requirements under the worst scenario. The simulation results on the practical case show that the proposed model can suppress the wind power output under the worst scenario. The suppression method that takes wind power uncertainty into consideration is more reliable than that does not.

    Research on economic operation method of multi energy complementary systems
    ZHANG Huifu
    2022, 44(11):  79-86.  doi:10.3969/j.issn.2097-0706.2022.11.011
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    To achieve the "dual carbon" target,we coordinately utilize multiple energies to improve the comprehensive energy efficiency. Demand sides of different energy systems are usually designed and operated separately. A multi-energy complementary system integrating a water-cooled air conditioning system, an air source heat pump hot water system, a PV system,a wind power system and an energy(cold,heat and electricity)storage system is constructed,which couples different subsystems at user ends. Making simulation calculation on the complementary system and apply it to the optimal design and scheduling of actual projects. In the actual project, taking the lowest comprehensive economic index as the only objective, the calculation results show that the comprehensive cost of the complementary system can be reduced by 18% under the typical working condition by increasing the capacity of electric energy storage system, reducing the capacities of the water-cooled air conditioning system, air source heat pump hot water system, chilled water storage system and heat storage tank and removing the photovoltaic system and wind power system. The simulation on the multi-energy complementary system can provide guidance for the design and operation of related projects.