• Ultra-short-term Photovoltaic Power Forecasting Based on Multi-level Sky Image Features and Broad Learning

  CHEN Dianhao, ZANG Haixiang, JIANG Yunan, LIU Jingxuan, SUN Guoqiang, WEI Zhinong

  Available online:September 30, 2024  DOI: 10.7500/AEPS20240416009

  Abstract(18) HTML(14) PDF(1.94 M)( 147)

  Abstract:Aiming at the problems of insufficient use of sky image information and large errors in ramp power forecasting, which lead to the limited predictive performance improvement, an ultra-short-term photovoltaic power forecasting method based on multi-level sky image features and broad learning is proposed. Firstly, the multi-level features of the ground-based sky image are extracted as the image features of the power forecasting model. At the same time, the cloud coverage and cloud change rate are introduced as image features of the ramp recognition model. Secondly, combined with the historical power data, the photovoltaic power forecasting model and the ramp recognition model based on the broad learning are developed. Finally, if the ramp recognition result is a non-ramp event, the forecasting results are obtained according to the power forecasting model, but if the ramp recognition result is a ramp event, the power forecasting model is incrementally updated using the historical data related to the ramp event, and the forecasting results are obtained based on the updated power forecasting model. The experimental results show that the proposed method can effectively improve the forecasting accuracy of ultra-short-term photovoltaic power.

• Voltage Control Strategy for Active Distribution Network Based on Data-enabled Predictive Control

  ZHU Yongqi, LIU Youbo, TANG Zhiyuan, XU Zirong, GAO Hongjun, LIU Junyong

  Available online:September 30, 2024  DOI: 10.7500/AEPS20240409006

  Abstract(11) HTML(10) PDF(2.76 M)( 161)

  Abstract:The integration of a high proportion of distributed photovoltaic into distribution networks exacerbates the system's uncertainty. Moreover, it is challenging to accurately acquire data such as the network topology and line parameters of distribution networks, rendering traditional control methods for distribution networks based on precise physical modeling ineffective. With the widespread application of measurement devices in distribution networks, it becomes increasingly easier to obtain operation data of distribution networks. In this paper, a model-free voltage control method for active distribution networks based on measurement data of distribution networks is proposed. Firstly, a Hankel matrix is constructed based on the historical data of the distribution network to establish the relationship between the node voltages of the network and the output power of energy storage. Secondly, using local measurement data and considering uncertain disturbance factors and the attenuation model of the energy storage lifespan, an optimization framework for distribution network voltage under data-enabled predictive control is constructed to achieve the rolling optimization of distribution network voltage within the control cycle. Finally, the effectiveness and superiority of the proposed method are verified through simulations using the IEEE 34-bus standard example and the modified IEEE 123-bus example.

• Collaborative Robust Planning of Electric and Thermal Flexibility Resources Considering Reserve Optimization

  GAO Xueqian, LIU Chang, LIU Wenxia

  Available online:September 30, 2024  DOI: 10.7500/AEPS20240120002

  Abstract(8) HTML(8) PDF(3.64 M)( 161)

  Abstract:In the “Three North” regions of China, wind resources are abundant but system flexibility resources are scarce. During the heating period, the proportion of electric output of thermoelectric unit is high, occupying the space for wind power integration and posing severe challenges to the safe and economic operation of the system. To improve the economy of wind power accommodation, a collaborative robust planning method for electric and thermal flexibility resources considering reserve optimization is proposed. First, the peak shaving operation mechanism of promoting thermoelectric decoupling and its collaborative planning mechanism through various resources has been studied. On this basis, a min-max-min three-layer two-stage light robust planning model is established. The main problem aims to minimize the sum of the planned annual incremental investment cost, operation cost, and risk cost of insufficient reserve, optimizes all kinds of resource investment schemes and day-ahead deterministic optimal scheduling. Taking into account the uncertainty of wind power based on day-ahead scheduling results,the sub-problem minimizes the risk of insufficient reserve in the worst scenario, reschedule the equipment within days, searches for the worst scenario, and assesses the risk of insufficient reserve. The main problem and sub-problems are solved iteratively based on the column-and-constraint generation algorithm and the strong duality theory. Finally, the validity of the model is verified by a numerical example, and the robustness and risk of the model are analyzed.

• Review on Deployment Planning Techniques and Operational Methods for Port Shore Power System

  DAI Lei, WANG Yubing, GUO Siqing, HU Hao, FANG Sidun

  Available online:September 30, 2024  DOI: 10.7500/AEPS20231225005

  Abstract(8) HTML(12) PDF(1.65 M)( 134)

  Abstract:Shore power system reduces the emission of port area by shutting down the power generation equipment of docked ships, and is the central equipment of port energy-transportation integration. Its operation and planning play an important role in realizing the goal of "carbon neutrality" in the future port integrated energy system. In order to clarify the current research status and point out the bottleneck problems restricting the development of shore power system, the port shore power system is reviewed from three aspects: environmental benefit assessment, technical standards and deployment scheme of shore power system, policy planning and operation strategy of shore power system. The current situation analysis shows that the shore power system plays a key role in port green development, but it is also pointed out that the installation rate and utilization rate of shore power system present a great contradiction. In view of the future development of shore power system, the following suggestions are put forward. The whole life cycle benefit assessment of shore power system is the premise and foundation of economic planning, and the low level of energy-transportation integration is an important reason for the low utilization rate of shore power system. Also, the multi-agent operation management collaboration is the key way to improve the operation efficiency of shore power system.

• Optimal Setting of Power and Frequency Parameters for Voltage-type Distributed Photovoltaics-Virtual Synchronous Generator Based on Transient Search Optimization

  ZHAO Bo, TANG Yajie, XU Hao, LIU Nian, GONG Diyang

  Available online:September 30, 2024  DOI: 10.7500/AEPS20240227009

  Abstract(7) HTML(14) PDF(6.09 M)( 166)

  Abstract:With the increasing penetration of distributed photovoltaics (DPV), the proportion of traditional energy units continues to decline, resulting in a reduction of inertia and primary frequency regulation capabilities in power systems. Therefore, it is crucial to explore the frequency support capabilities of DPV in low-inertia systems. On this basis, firstly, this paper proposes an improved frequency active support method for voltage-type DPV-virtual synchronous generator (DPV-VSG) with variable reserve rate to enhance the system inertia, reduce the response delay, and improve the ability of DPV for active participation in system frequency support. Then, an optimal selection model for setting the power and frequency parameters based on the transient search optimization (TSO) algorithm is proposed to solve the optimal initial reserve power and best frequency regulation parameters of DPV, which improves the limitation of fixed photovoltaic initial reserve power. Finally, the proposed model is applied a single-generator model and an actual distribution station area model with high penetration of DPV to verify its effectiveness.

• Day-ahead Interactive Operation Method for Distribution Network and 5G Base Stations Based on Inter-station Migration of Communication Load

  LIU Hong, WANG Zhijie, XU Zhengyang, YANG Baijie, LI Junkai, ZHANG Shida

  Available online:September 30, 2024  DOI: 10.7500/AEPS20240202004

  Abstract(7) HTML(16) PDF(2.63 M)( 145)

  Abstract:Current research on 5G base stations as flexible resources to participate in power grid interaction mostly focuses on the utilization of energy storage resources of 5G base station, ignoring the regulatory potential of 5G base station communication load. Therefore, a day-ahead interactive operation method for distribution network operator (DNO) and mobile network operator (MNO) based on interstation migration of communication load is proposed. Firstly, a DNO-MNO dual-layer interactive operation optimization model is constructed. In this model, DNO is an incentive strategy that comprehensively considers the system network loss cost and the incentive cost of the 5G base station, and takes the system N-1 safe operation criterion as a constraint and aims at the the lowest total system operating cost. MNO comprehensively considers the power consumption cost of the 5G base station and the grid demand response benefits, and develops the 5G base station power operation plan with the goal of the lowest net operating cost of the 5G base station. Secondly, to solve the problem that the lower MNO 5G base station scheduling model has non-convex and nonlinear constraints which are difficult to solve analytically, an algorithm based on feasible domain iteration is proposed to solve the model accurately. Thirdly, the algorithm of DNO embedded MNO dual-layer interactive model based on elite genetic algorithm is proposed. Finally, a numerical example is given to verify the effectiveness and practicability of the proposed method.This work is supportedFoundation by the State Key Laboratory of Power System Operation and Control (No. SKLD23KM15) and Basic and Applied Basic Research Foundation of Guangdong Province (No. 2022A1515110896).

• Review on Grid-following/Grid-forming Hybrid Mode Control for Grid-connected Converter in High-penetration Renewable Energy Generation

  ZHANG Xing, ZHAN Xiangdui, WU Mengze, HAN Feng, FU Xinxin, LI Ming

  Available online:September 30, 2024  DOI: 10.7500/AEPS20240114003

  Abstract(14) HTML(22) PDF(2.40 M)( 174)

  Abstract:With the increasing penetration rate of renewable energy generation, the stable operation of grid-connected converters with grid-following control as the mainstream has been severely challenged. Therefore, the control technologies of grid-forming converters with active support capability for the power grid and strong stability in the weak power grid has received much attention. However, under the conditions of high-penetration renewable energy generation, especially in the terminal weak grid, it is difficult for the grid-connected converters to balance stability, economy, and power grid support performance by using a single grid-following or grid-forming mode control. Based on the complementary characteristics of the two modes, scholars at home and abroad have proposed and studied the grid-following/grid-forming hybrid mode control strategy, to make the grid-connected converters operate stably in the weak power grid, maximize the use of renewable energy, and achieve superior power grid support performance. Starting from the basic control structures of grid-following and grid-forming converters, this paper analyzes the complementary characteristics of the control performance of grid-following and grid-forming converters. On this basis, the hybrid mode control schemes of several different technical routes are sorted out, involving a variety of single-machine hybrid control strategies and multi-machine station-level hybrid control strategies. The technical research idea, principle, advantages, and disadvantages of each scheme are elaborated in detail. Finally, the development of grid-following/grid-forming hybrid mode control technologies is prospected.

• Short-term Active Power Impact Assessment for Low Voltage Ride-through of System Large-scale Renewable Energy Caused by Voltage Drop

  ZHU Ling, JIANG Tao, XUE Feng, LIU Fusuo, HUANG Xifang, LI Wei

  Available online:September 30, 2024  DOI: 10.7500/AEPS20240312004

  Abstract(11) HTML(16) PDF(3.40 M)( 132)

  Abstract:As the proportion of renewable energy replacing synchronous generators continues to rise, the system voltage support capacity decreases, and the voltage drop at the fault point can trigger large-scale renewable energy to enter low voltage ride-through (LVRT). In order to describe the stable operation risk after the power system fault disturbance and guide the selection of stability control measures, it is particularly important to quickly and accurately evaluate the LVRT risk of renewable energy caused by disturbances and the short-term active power impact of the system. Therefore, from the perspective of mechanism analysis, the transient support of the generators during faults and the reactive power support of renewable energy entering LVRT are firstly considered. The traditional voltage interaction factor method is improved, and an assessment method for the bus voltage drop of renewable energy during fault disturbances suitable for large-scale power grids is proposed. Furthermore, based on the transient power response characteristics of renewable energy at the electromechanical scale, a rapid evaluation method for the short-term active power impact of LVRT of system large-scale renewable energy is proposed. Finally, taking the New England 39-bus system with renewable energy as an example, the effectiveness of the proposed assessment method for the short-term active power impact is verified through simulation.

More+

Volume 48,2024 Issue 18

>专辑：规模化灵活资源虚拟电厂（二）

• Optimal Operation Method for Virtual Power Plant Based on Joint Sharing of Energy and Reserve of Prosumers

  SONG Meng, JING Xinyi, CAI Yunfeng, GAO Ciwei, YAN Xingyu, REN Shuangxue

  2024,48(18):3-13, DOI: 10.7500/AEPS20231226005

  Abstract(23) HTML(68) PDF(2.63 M)( 283)

  Abstract:To promote the coordination and optimization of multi-market entities and the entities of power and responsibility in a multi-level market environment, this paper combines local peer-to-peer (P2P) transactions with wholesale markets through the virtual power plant (VPP). An optimal operation method for VPP based on the joint sharing of energy and reserve of prosumers is proposed. Firstly, the reserve requirement is extended to the distribution network market and the local energy-reserve market is distributedly cleared by the adaptive alternating direction method of multipliers (ADMM). Secondly, a bi-level trading model of VPP-prosumer is established. The upper-level VPP collects the transaction demands of prosumers and optimizes the purchase and sale prices. The lower-level prosumers quantify reserve demands, decision energy and reserve capacity by using the general Gaussian distribution and opportunity constraint theory. Finally, the model is solved by dichotomy. The results show that the proposed mechanism increases the market income of VPP and realizes the traceability and allocation of reserve cost to prosumers. The local market enlarges the bargaining space of VPP and prosumers.

• Bidding Mechanism Design for Building Virtual Power Plant to Participate in Demand Response Markets

  QI Taoyi, HUI Hongxun, YE Chengjin, DING Yi, ZHAO Yuming, SONG Yonghua

  2024,48(18):14-24, DOI: 10.7500/AEPS20240313002

  Abstract(29) HTML(65) PDF(2.19 M)( 254)

  Abstract:The receiving-end urban power grids with high load density are facing an increasingly serious shortage of regulation resource. Urban buildings have many promising and flexible resources such as central air conditioners and electric vehicles, and can participate in the supply-demand interaction by constructing the virtual power plant (VPP) through aggregation. With the rapid development of the demand response (DR) markets, the market-oriented pricing and trading of flexible resources have become a trend. Therefore, considering the benefit demand of buildings and VPPs, the bidding mechanism for the building VPP participating in the DR market trading is designed. First, according to the characteristics of flexible loads of buildings, they are divided into lossless transferable loads, lossy transferable loads, as well as lossy reducible loads, and the corresponding formulation methods of capacity-cost are proposed, respectively. Then, an allocation method is proposed to guarantee the reliable revenues of both the buildings and the VPP, so as to continuously motivate them to participate in the DR markets. On this basis, the bidding optimization model is developed for the VPP to participate in the DR markets to realize the maximization of the revenues of VPPs in different scenarios. Finally, the effectiveness of the proposed mechanism in market trading and revenues allocation is proved by case simulations.

• Electricity-Carbon Double-layer Collaborative Decision-making Mechanism for Building Virtual Power Plant Based on Mutual Recognition of Green Electricity Emission Reduction

  XIE Min, HUANG Ying, LU Yanxuan, LI Yisheng, LIU Mingbo, WANG Tao

  2024,48(18):25-37, DOI: 10.7500/AEPS20231126001

  Abstract(11) HTML(50) PDF(3.69 M)( 254)

  Abstract:In the background of “carbon emission peak and carbon neutrality”, the coexistence of multiple electricity-carbon policies and markets has brought about the problem of repeated rewards and punishments for the environmental rights and interests of electric power. To solve this problem, this paper proposes a green electricity-Chinese certified emission reduction (CCER) mutual recognition method based on emission reduction equivalence, uniformly assigns the environmental rights and interests of green electricity to the user side, and the building entity is taken as the research object to verify the mutual recognition method. Firstly, according to the difference of emission reduction characteristics, the buildings are divided into mandatory buildings, emission-reducing buildings and zero-carbon buildings, and the building virtual power plant (BVPP) is used as the agent of CCER mutual recognition. Secondly, aiming at the internal CCER distribution problem of BVPP, a distribution method based on Shapley value method is proposed to ensure the fairness and rationality of the distribution. Then, an electricity-carbon double-layer collaborative trading mechanism based on the principle of energy sharing is proposed for the electricity-carbon collaborative decision-making problem faced by the building entity, and a double-layer decision-making model is constructed based on Stackelberg game theory. The model is convex by combining the concept of supply-demand ratio. Finally, the feasibility of the mutual recognition method and the effectiveness of the electricity-carbon double-layer collaborative decision-making mechanism are verified by the case simulation.

• Two-stage Robust Trading Strategy for Virtual Power Plant in Multi-level Electricity-Carbon Coupling Market

  ZHOU Yizhou, WU Junzhao, SUN Guoqiang, HAN Haiteng, ZANG Haixiang, WEI Zhinong

  2024,48(18):38-46, DOI: 10.7500/AEPS20231204002

  Abstract(18) HTML(47) PDF(1.84 M)( 226)

  Abstract:With the continuous development of the electricity market and carbon market in China, virtual power plant (VPP) has become an important market participating entity. This paper proposes a two-stage robust trading strategy for a VPP in a multi-level electricity-carbon coupling market. First, the coupling characteristics of the electricity market and carbon market in China are analyzed, and the trading processes of the multi-level electricity-carbon market are proposed including the medium- and long-term electricity market, primary carbon market, electricity spot market, and secondary carbon market. Then, a two-stage trading model is established for VPP participating in the multi-level electricity-carbon coupling market. In the first stage, the trading strategy of the VPP in the medium- and long-term electricity market and the primary carbon market is optimized. In the second stage, the trading strategy of the VPP in the day-ahead electricity spot market and the secondary carbon market is optimized. Finally, a two-stage adaptive robust optimization model is established for the VPP to mitigate the impact of renewable energy output uncertainty of VPP on trading results, and a column-and-constraint generation algorithm is employed to solve the model. The results of the simulation cases demonstrate the feasibility and effectiveness of the proposed model and method.

• Dynamic Construction and Response Demonstration of Virtual Power Plant with Aggregated Large-scale 5G Base Stations

  GAO Hongchao, LI Chuyi, WANG Guanxiong, JIN Tai, HU Jiye, ZHU Jingkai, CHEN Qixin, KANG Chongqing

  2024,48(18):47-55, DOI: 10.7500/AEPS20231003001

  Abstract(18) HTML(41) PDF(2.35 M)( 302)

  Abstract:Due to the increasing penetration of renewable energy sources, the power system is facing a lack of flexibility as a result of the increasing pressure on its regulation. With the participation of virtual power plants and other emerging entities in the interaction, a wide range of distributed resources can be aggregated and become regulating resources that cannot be ignored in the power system. This virtual power plants with 5G base stations are taken as the research objects. Firstly, the coordination mechanism of response potential of submodules in 5G base stations is discussed, and energy utilization models for different resource objects are developed. Secondly, the problem of characterizing the feasible region of the aggregated response of large-scale 5G base stations is analyzed, and the differential effect on 5G base station response characteristics between independent charaterization and classified charaterization is analyzed. The feasible region deviation of different aggregation methods in approximate solution based on Minkowski sum is elaborated in detail. Then, the advantages and principles of classifying characterization of feasible region for large-scale 5G base stations are analyzed, and the effectiveness is verified through multiple cases. Finally, based on actual response data, the response empirical effect of virtual power plant with large-scale 5G base stations is demonstrated.

• Low-carbon Economic Dispatch for Multiple Data Center Virtual Power Plant Based on Spatio-Temporal Collaboration

  WEN Xiyu, ZHU Jizhong, LI Shenglin, DONG Hanjiang

  2024,48(18):56-65, DOI: 10.7500/AEPS20240424007

  Abstract(28) HTML(39) PDF(1.86 M)( 250)

  Abstract:The data center, due to its adjustable load at both spatial and temporal scales, can be regarded as a huge and highly potential new demand response resource, and is an industrial case of virtual power plants. However, in existing studies of data center economic dispatch, environmental benefits and computing experience for renters have not been fully considered, and the evaluation of execution effectiveness after demand response has been mostly neglected. Thus, a low-carbon economic dispatch scheme for multiple data centers based on spatio-temporal collaboration is proposed. Firstly, the spatio-temporal adjustable characteristics of data center workloads are modeled to clarify the specific realization path of demand response and renewable energy accommodation. Secondly, the renter satisfaction for demand response is quantified to ensure the user-side service experience. The carbon trading cost is introduced into the objective function to guide the source side in reducing carbon emissions. Finally, the case study is conducted using typical data of data center in the day-ahead invitation demand response mode in Guangdong electricity market, China. Simulation results show that the proposed scheme can effectively stimulate the spatio-temporal regulation potential for flexible resources of data centers and achieve overall economic improvement while considering environmental benefits and renter satisfaction.

• Solution Method of Regulation Boundary for Industrial Park Virtual Power Plant Considering Power Network Constraints

  LIAO Siyang, HE Cong, LI Lingfang, XU Jian, SUN Yuanzhang, KE Deping

  2024,48(18):66-75, DOI: 10.7500/AEPS20231206002

  Abstract(12) HTML(47) PDF(1.74 M)( 270)

  Abstract:To construct a new power system with renewable energy as its primary component, it is urgent to explore the flexible regulation resources on the load side to participate in grid control and regulation. Industrial parks that contain high energy-consuming loads, such as aluminium electrolyzers and mineral heat furnaces, have good potential for control and regulation. However, due to the constraints of the internal power networks of the parks, accurately solving the regulation boundary is faced with the difficulties of high dimensionality of the variables and non-linearity of the constraints, and the existing methods don’t take into account the computational efficiency and accuracy very well. Hence, the above problem is abstracted as the projection of high-dimensional nonlinear state space in the P-Q coupling plane: the projection solution models of the regulation boundary considering the linearized and nonlinear constraints on the safe operation of the industrial park are established, respectively, and a novel high-dimensional state space projection algorithm is adopted to obtain the accurate projection of the regulation boundary of the industrial park virtual power plant through the two-step solution process of vertex “searching-mapping”. The results demonstrate that the regulation boundary solved by the proposed method can be fully characterised by a linear inequality set, which is fully compatible with the existing scheduling system. Combined with the comparison with the superimposed flexible resource regulation capability and the traditional sampling method, the feasibility, and high accuracy and solution efficiency of the method are verified.

• Multi-timescale Frequency Regulation Control of Flexible Resources in Virtual Power Plant

  MO Lili, LAN Junkun, ZHOU Liang, YE Meng, MA Li, CHEN Haoyong

  2024,48(18):76-86, DOI: 10.7500/AEPS20230912004

  Abstract(23) HTML(35) PDF(1.69 M)( 301)

  Abstract:With the promotion of the transition of energy structure, the utilization of renewable energy is gradually increasing, and it is difficult to meet the demand by relying on traditional units to regulate frequency deviation. Therefore, in order to solve this problem, the use of distributed resources (DRs) to participate in frequency regulation auxiliary services is considered. The DRs are mainly considered as air conditioners, electric vehicle charging piles and energy storage. First, the characteristics and satisfaction evaluation methods of DRs are considered. Then, DRs are controlled coordinately based on the state-potential game theory and centralized to externally present as a whole to participate in the frequency regulation auxiliary services. Finally, the feasibility and effectiveness of aggregation and coordinated control of DRs to participate in frequency regulation auxiliary services under the proposed control strategy are demonstrated through simulation cases, and the participation of energy storage, charging piles, and controllable loads in the fast frequency regulation under multiple time scales is verified.

• Review on Aggregation Characteristics and Trading Mechanisms of Virtual Power Plant for Enhancing System Response Capability

  WANG Fei, WANG Ge, XU Fei

  2024,48(18):87-103, DOI: 10.7500/AEPS20240424005

  Abstract(22) HTML(37) PDF(1.91 M)( 287)

  Abstract:In the context of the issues of degraded frequency dynamic performance and prominent frequency stability in the new power system, this paper summarizes aggregation response characteristics and market trading mechanisms of virtual power plants (VPPs) for system frequency response capability enhancement, and provides market-based solutions for the current application difficulties in the distributed resource frequency support technology due to the lack of market mechanism. Firstly, the fundamental principles of frequency dynamic responses of distributed resources and the key supporting technologies required by VPPs are summarized, and the problems existing in providing system frequency support for VPPs are analyzed. Secondly, the frequency aggregation response characteristics of VPPs are refined from the three dimensions of time, space and cost, and the market trading mechanism of VPPs to enhance the system frequency response capability is summarized, including product design, clearing pricing, contribution quantification and settlement assessment. Then, the interaction between the aggregation response characteristics of VPPs and the market trading mechanism is discussed. Finally, the future research focuses of VPPs to enhance the system frequency response capability are prospected.

• Risk Scheduling and Power Sharing Mechanism for Sharing-based Virtual Power Plant

  MA Yutong, ZHANG Chunyan, DOU Zhenlan, WANG Lingling, JIANG Chuanwen, WANG Su

  2024,48(18):104-114, DOI: 10.7500/AEPS20240229003

  Abstract(19) HTML(31) PDF(2.09 M)( 289)

  Abstract:As the development of demand-side resources continues to increase and the electricity market mechanism is being improved, the decentralized flexibility resources on the demand side will play a more important role in the power dispatch and trading. The construction of virtual power plants provides a new idea for the demand-side resource management and utilization, while the power sharing has attracted much attention for its ability to promote regional power balance and enhance power system flexibility. To this end, the power sharing trading mechanism based on virtual power plant is studied. Firstly, the concept of sharing-based virtual power plant is proposed and the framework of power sharing with renewable energy stations is established. Secondly, the risk scheduling model of sharing alliance based on the minimum-maximum regret method considering the uncertainty of the renewable energy output is established. Then, the price mechanism of shared power based on the consistency theory is derived. Finally, case analysis is conducted based on the modified IEEE 33-bus system. Results demonstrate that the proposed scheduling method and trading mechanism can improve the utilization efficiency of user-side resources, promote the renewable energy accommodation and balance the regional supply and demand of the power grid.

• Planning Method for Resource Aggregation of Virtual Power Plant Based on Dynamic Reconstruction

  SUN Lingling, LI Haibin, JIA Qingquan, FU Lida, ZHANG Gong

  2024,48(18):115-128, DOI: 10.7500/AEPS20240314004

  Abstract(16) HTML(40) PDF(2.01 M)( 239)

  Abstract:With the development of Energy Internet technology, virtual power plant has become an effective way to aggregate and control large-scale distributed resources. How to aggregate virtual power plants to release the adjustable potential of distributed resources is a key technical problem. This paper focuses on the optimization of the resource aggregation for virtual power plants, and proposes a planning method for the resource aggregation of virtual power plant based on dynamic reconstruction. Firstly, a virtual power plant joining incentive mechanism is built to encourage high-quality resources to participate in aggregation. Secondly, according to the multiple and different characteristics of massive distributed resources, a method for resource feature extraction and classification is proposed to provide data basis for the resource aggregation of virtual power plant. Then, the decision model of resource joining intention is established and its joining capacity is evaluated. On the basis of the above, according to the dynamic change laws of distributed resources and electricity markets, the dynamic reconstruction optimization strategy of virtual power plant is proposed, and the phased dynamic aggregation planning of virtual power plant is carried out, and the two-layer optimization model of virtual power plant aggregation and operation is established to solve it. Finally, the case analysis proves the feasibility and superiority of the proposed method in solving the problem of virtual power plant aggregation planning.

• Construction Method for Probability-based Feasible Region of Virtual Power Plant Considering Uncertainty of Distributed Renewable Energy Output

  JIAO Zhijie, WANG Xiaojun, LIU Zhao, HE Jinghan, SI Fangyuan, GUAN Jinyu

  2024,48(18):129-138, DOI: 10.7500/AEPS20240407002

  Abstract(18) HTML(54) PDF(3.73 M)( 275)

  Abstract:The uncertainty of distributed renewable energy output significantly affects the accurate characterization of the feasible region for virtual power plant aggregation. It is necessary to accurately calculate the adjustable capacity of virtual power plants to enhance the balancing capability of the power system. This paper proposes a probability model for the uncertainty of distributed renewable energy output in virtual power plants and a construction method of the credible probability-based feasible region based on multiple probability variables. Firstly, based on the ensemble learning and conformal quantile regression methods, an uncertainty probability model is proposed to describe the heteroscedastic time series of renewable energy output. Secondly, the characteristics of Minkowski sum and optimization methods for solving feasible region are studied, and the influences of renewable energy output constraints and network constraints on the feasible region of the virtual power plant are analyzed. Then, this paper proposes a construction method for the probability-based feasible region of the virtual power plant based on output probability intervals of distributed renewable energy. Finally, considering the coupling characteristics of wind and photovoltaic power, the construction method for the probability-based feasible region of the virtual power plant is optimized. By coordinating the confidence coefficients of the output probability intervals of each distributed renewable energy, an overall confidence level of the probability-based feasible region of the virtual power plant is obtained. The case verification results show that the proposed method can accurately characterize the adjustable capacity of virtual power plants.

• Zonotope-based Wide-area Aggregation and Regulation Method for Distributed Resources in Virtual Power Plant

  XU Tianyun, CHEN Tao, ZHANG Xin, YUAN Hao, YAN Chunhua, ZHANG Hao

  2024,48(18):139-148, DOI: 10.7500/AEPS20240513002

  Abstract(20) HTML(55) PDF(2.26 M)( 275)

  Abstract:Due to the widespread adoption of distributed resources at the distribution network side, the exploration of their significant flexibility potential has become increasingly crucial. First, the air conditioning load, energy storage device and diesel generator are selected as representative resources to establish dynamic electrical models for these specific resources and delineate their feasible regions. Then, leveraging the foundation of Zonotope, an efficient aggregation method tailored for wide-area distributed resources is proposed. On this basis, aiming at the unique mathematical form of Zonotope, a precise mathematical transformation method between Zonotope and polytope in half-space form is proposed. And the aggregation clusters of specific distributed resources are applied to the optimized regulation in the virtual power plant scenario through this method. The effectiveness of this aggregation method is validated through numerical analysis, and its advantages in accuracy are compared with other aggregation methods. Finally, the effectiveness of the regulation method after resource cluster aggregation in terms of economy and computational efficiency is analyzed by combining the results of the case study.

• Privacy Preservation Trading Strategy for Power Peak-shaving Market with Participation of Virtual Power Plant

  ZUO Juan, AI Qian, WANG Di, WANG Wenbo, XU Chongxin

  2024,48(18):149-157, DOI: 10.7500/AEPS20240209001

  Abstract(16) HTML(41) PDF(1.77 M)( 248)

  Abstract:To solve the problems of malicious bidding and market disorder caused by key transaction information and sensitive data leakage in the centralized power peak-shaving auxiliary service market with the participation of virtual power plants, this paper designs a privacy preservation trading strategy for the centralized market based on “service provider-blockchain-power dispatch control center”. The strategy achieves trusted trading in the power peak-shaving market under the dual constraints of privacy preservation and network security. Firstly, a bidding information privacy preservation scheme based on the price confusion random oracle and the improved Shamir secret sharing network is designed to strictly preserve the quantity and price information submitted to the blockchain. Secondly, based on homomorphic encryption technology, a blockchain smart contract is designed according to the priority order principle of price, credit value, and time, achieving privacy sorting and trusted automatic clearing of bidding quantity. Thirdly, for the practical value, by deploying security verification contracts on the blockchain, the network security constraint verification of transaction results is achieved, and the operation security of the distribution network and the settlement security of service providers are ensured. Finally, through case analysis and evaluation, the effectiveness and superiority of this privacy preservation trading strategy are verified, indicating that this strategy can improve the flexibility and reliability of the power system while preserving the privacy of participants.

• Optimization of Internal Transaction Decisions in Virtual Power Plant Considering Privacy Preservation

  LUAN Wenpeng, LI Peilin, ZHAO Bochao, XU Biao

  2024,48(18):158-166, DOI: 10.7500/AEPS20240509004

  Abstract(18) HTML(22) PDF(2.42 M)( 230)

  Abstract:The virtual power plant serves as an effective means of participating in electricity market transactions, providing ancillary services, and enabling peer-to-peer transactions through the aggregation and management of various demand-side resources. Addressing the issues such as information manipulation and privacy leakage during the transaction decision optimization process in the traditional virtual power plant, a distributed transaction decision optimization method based on the main-side blockchain structure is proposed. To incentivize the participation of aggregators in the peer-to-peer trading market, a peer-to-peer trading mechanism for virtual power plant aggregators with an adaptive pricing mechanism is designed. To resist dishonest aggregators from manipulating interaction information during the optimization process, an improved practical Byzantine fault tolerance consensus algorithm based on the main-side blockchain is proposed. Additionally, to further prevent privacy leakage resulting from information interaction, a message encryption and decryption algorithm based on Shamir’s secret sharing scheme is proposed. Finally, the superiority of the proposed method in terms of transaction decision optimization, manipulating resistance, and privacy preservation is verified through numerical analysis.

>Basic Research

• Probabilistic Power Flow Method Based on Arbitrary Probability Distribution Modeling and Improved Polynomial Chaos Expansion

  LI Kemeng, WANG Yi, SHAN Xin, LU Juanjuan

  2024,48(18):167-176, DOI: 10.7500/AEPS20231220001

  Abstract(16) HTML(143) PDF(1.36 M)( 220)

  Abstract:In response to the current difficulty in balancing accuracy and speed in probabilistic power flow, as well as the lack of effective means to handle source and load data with arbitrary probability distributions, a probabilistic power flow method based on the arbitrary probability distribution modelling strategy and improved polynomial chaos expansion is proposed. Firstly, the system inputs are fitted to the probability distribution in the parameterized probability distribution type library. The optimal distribution is selected based on the Akaike information criterion, and the likelihood estimates of the optimal distribution and non-parametric kernel density estimation are compared to determine the final probability distribution. Secondly, to improve the accuracy of the generalized polynomial chaos expansions based on least angular regression, the pseudo spectral method and moment matching method are used to obtain a set of candidate points, and the combination probability window is used to filter them and obtain the optimal candidate points. Then, Latin hypercube sampling is performed on the original probability space to obtain supplementary configuration points, which are combined with the optimal candidate points to obtain the final configuration points. The proposed method has been validated in IEEE 30-bus and IEEE 118-bus cases, and its accuracy is significantly improved compared with the uncertainty quantification computing framework UQLab recommendation algorithm under similar time consumption.

• Holomorphic Embedding Probabilistic Power Flow Calculation Method for AC/DC System Based on Polynomial Chaos Expansion

  LI Xue, FU Yunyue, JIANG Tao, LI Guoqing

  2024,48(18):177-188, DOI: 10.7500/AEPS20240129007

  Abstract(17) HTML(30) PDF(4.48 M)( 215)

  Abstract:In order to quickly and accurately quantify the influence of uncertainty of wind power output on power flow distribution of AC/DC power system, a holomorphic embedding probabilistic power flow calculation method of AC/DC power system based on polynomial chaos expansion (PCE) is proposed. Firstly, the optimal orthogonal basis function is selected according to the probability distribution characteristics of wind power output, and the PCE expression approximating the probability distribution characteristics of wind power output is constructed. Secondly, the PCE expression is introduced into the holomorphic embedding power flow equation of AC/DC power system, and the holomorphic embedding probabilistic power flow calculation model of AC/DC power system based on PCE is constructed. Thirdly, the holomorphic embedding probabilistic power flow model is transformed into a high-dimensional deterministic holomorphic embedding power flow model by Galerkin projection. Then, with the deterministic holomorphic embedding power flow model solving method, the transformed high-dimensional deterministic holomorphic embedding power flow model is solved, and the probability distribution characteristics of power flow in AC/DC power system are calculated according to the obtained PCE approximation coefficient. Finally, the accuracy and effectiveness of the proposed method are verified by the modified PJM 5-bus, IEEE 30-bus and IEEE 118-bus AC/DC test systems.

• Reduced-order Modeling and Stability Domain Analysis of Multi-terminal AC/DC Distribution System

  JIANG Songhan, PENG Ke, ZHAO Xueshen, CHEN Jiajia, JIANG Yan, LIU Yuxin

  2024,48(18):189-198, DOI: 10.7500/AEPS20231120002

  Abstract(18) HTML(48) PDF(2.92 M)( 236)

  Abstract:With the widespread access of different power electronic equipment, the stability analysis of AC/DC distribution systems has become more complex, leading to low-frequency oscillation accidents which seriously endangered the safe and stable operation of the systems. How to simplify the complex AC/DC distribution system model and analyze the dynamic characteristics of DC voltage under different parameters is the key to improving system stability and avoiding system oscillation instability. This paper takes the three-terminal AC/DC distribution system as the research object. First, the equivalent single-machine model is established to achieve the equivalent order reduction of the multi-terminal AC/DC distribution system. Then, based on the equivalent single-machine model, a low-frequency analysis model of DC voltage is derived, which reduces the order of the low-frequency model and obtains an analytical expression of the dynamic performance of DC voltage. Thirdly, based on the transfer function and analytical expression of the equivalent single-machine model, a stability domain analysis method is proposed to study the influence of system parameter changes on the stability domain and system dynamic performance. Finally, based on the software simulation and hardware-in-the-loop experiments, the effectiveness of the proposed method is verified.

• Incremental Cost Based Hierarchical Distributed Control Strategy for AC/DC Hybrid Microgrid

  YANG Fan, CAO Jiuzhou, YE Lingyue, LI Dongdong, LIN Shunfu, ZHAO Yao, SHEN Yunwei

  2024,48(18):199-207, DOI: 10.7500/AEPS20231220005

  Abstract(15) HTML(42) PDF(1.40 M)( 235)

  Abstract:Due to the varying costs of distributed generators in the AC/DC hybrid microgrids, it tends to cause higher system costs with the droop control that distributes power according to the capacity ratio. A droop control based on incremental costs is proposed to address this issue. To further eliminate the impact of mismatched line impedances on the power distribution accuracy and fully consider the economic operation of the microgrid, this paper proposes a hierarchical distributed control strategy based on the consensus algorithm. This control strategy is divided into the subnetwork-level control and system-level economic control. The subnetwork-level control introduces the frequency/voltage secondary control term and cost secondary control term in the incremental cost based droop control to restore the AC frequency and DC voltage, and realizes the economic power distribution of distributed generators among the subnetworks at the same time. In the system-level economic control, the “relative frequency index” and “relative voltage index” are introduced to construct the local control strategy of the bi-directional interconnected converter. The power secondary control term based on the consensus algorithm is further introduced to realize the consistent incremental cost across distributed generators, so as to achieve the globally optimal economic operation of the system. Finally, the simulation of the AC/DC hybrid microgrid model is carried out to verify the effectiveness of the proposed control strategy.