SONG Meng , JING Xinyi , CAI Yunfeng , GAO Ciwei , YAN Xingyu , REN Shuangxue
2024, 48(18):3-13. DOI: 10.7500/AEPS20231226005
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.
QI Taoyi , HUI Hongxun , YE Chengjin , DING Yi , ZHAO Yuming , SONG Yonghua
2024, 48(18):14-24. DOI: 10.7500/AEPS20240313002
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.
XIE Min , HUANG Ying , LU Yanxuan , LI Yisheng , LIU Mingbo , WANG Tao
2024, 48(18):25-37. DOI: 10.7500/AEPS20231126001
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.
ZHOU Yizhou , WU Junzhao , SUN Guoqiang , HAN Haiteng , ZANG Haixiang , WEI Zhinong
2024, 48(18):38-46. DOI: 10.7500/AEPS20231204002
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.
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: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.
WEN Xiyu , ZHU Jizhong , LI Shenglin , DONG Hanjiang
2024, 48(18):56-65. DOI: 10.7500/AEPS20240424007
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.
LIAO Siyang , HE Cong , LI Lingfang , XU Jian , SUN Yuanzhang , KE Deping
2024, 48(18):66-75. DOI: 10.7500/AEPS20231206002
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.
MO Lili , LAN Junkun , ZHOU Liang , YE Meng , MA Li , CHEN Haoyong
2024, 48(18):76-86. DOI: 10.7500/AEPS20230912004
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.
2024, 48(18):87-103. DOI: 10.7500/AEPS20240424005
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.
MA Yutong , ZHANG Chunyan , DOU Zhenlan , WANG Lingling , JIANG Chuanwen , WANG Su
2024, 48(18):104-114. DOI: 10.7500/AEPS20240229003
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.
SUN Lingling , LI Haibin , JIA Qingquan , FU Lida , ZHANG Gong
2024, 48(18):115-128. DOI: 10.7500/AEPS20240314004
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.
JIAO Zhijie , WANG Xiaojun , LIU Zhao , HE Jinghan , SI Fangyuan , GUAN Jinyu
2024, 48(18):129-138. DOI: 10.7500/AEPS20240407002
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.
XU Tianyun , CHEN Tao , ZHANG Xin , YUAN Hao , YAN Chunhua , ZHANG Hao
2024, 48(18):139-148. DOI: 10.7500/AEPS20240513002
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.
ZUO Juan , AI Qian , WANG Di , WANG Wenbo , XU Chongxin
2024, 48(18):149-157. DOI: 10.7500/AEPS20240209001
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.
LUAN Wenpeng , LI Peilin , ZHAO Bochao , XU Biao
2024, 48(18):158-166. DOI: 10.7500/AEPS20240509004
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.
LI Kemeng , WANG Yi , SHAN Xin , LU Juanjuan
2024, 48(18):167-176. DOI: 10.7500/AEPS20231220001
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.
LI Xue , FU Yunyue , JIANG Tao , LI Guoqing
2024, 48(18):177-188. DOI: 10.7500/AEPS20240129007
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.
JIANG Songhan , PENG Ke , ZHAO Xueshen , CHEN Jiajia , JIANG Yan , LIU Yuxin
2024, 48(18):189-198. DOI: 10.7500/AEPS20231120002
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.
YANG Fan , CAO Jiuzhou , YE Lingyue , LI Dongdong , LIN Shunfu , ZHAO Yao , SHEN Yunwei
2024, 48(18):199-207. DOI: 10.7500/AEPS20231220005
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.
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