This paper presents a novel modified inter- active honey bee mating optimization （IHBMO） base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources （DERs）. T...This paper presents a novel modified inter- active honey bee mating optimization （IHBMO） base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources （DERs）. The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting, A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduc- tion in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power orDERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.展开更多
With large-scale development of distributed generation(DG) and its potential role in microgrids, the microgrid cluster(MGC) becomes a useful control model to assist the integration of DG. Considering that microgrids i...With large-scale development of distributed generation(DG) and its potential role in microgrids, the microgrid cluster(MGC) becomes a useful control model to assist the integration of DG. Considering that microgrids in a MGC, power dispatch optimization in a MGC is dif-ficult to achieve. In this paper, a hybrid interactive communication optimization solution(HICOS) is suggested based on flexible communication, which could be used to solve plug-in or plug-out operation states of microgrids in MGC power dispatch optimization. HICOS consists of a hierarchical architecture: the upper layer uses distributed control among multiple microgrids, with no central controller for the MGC, and the lower layer uses a central controller for each microgrid. Based on flexible communication links among microgrids, the optimal iterative information are exchanged among microgrids, thus HICOS would gradually converge to the global optimal solution.While some microgrids plug-in or plug-out, communication links will be changed, so as to unsuccessfully reach optimal solution. Differing from changeless communication links in traditional communication networks, HICOS redefines the topology of flexible communication links to meet the requirement to reach the global optimal solutions.Simulation studies show that HICOS could effectively reach the global optimal dispatch solution with non-MGC center. Especially, facing to microgrids plug-in or plug-out states, HICOS would also reach the global optimal solution based on refined communication link topology.展开更多
The problem of Point-Of-Interest(POI)recommendation,based on the user’s historical checkin records,determines whether a user checks in at specific POI.However,the user-POI data have a longtail distribution phenomenon...The problem of Point-Of-Interest(POI)recommendation,based on the user’s historical checkin records,determines whether a user checks in at specific POI.However,the user-POI data have a longtail distribution phenomenon.To mitigate the sparsity of check-in data,it is a good idea to exploit the sufficient attributes of POI and recommend POIs in both geography wise and category wise.Generally,this problem can be treated as two specific tasks with feature combination,ignoring cross-task dependencies and feature disentanglement.To address the aforementioned problems,this paper proposes a novel joint framework named InteractPOI,enabling two-stage interaction bewteen geographywise and category-wise POI recommendations.Specifically,this paper comprehensively considers the sequence effect and the neighbor effect both from geography wise and category wise.For the firststage interaction,we design a disentangled graph embedding model to distinguish different influencing factors from geography wise and category wise.For the second-stage interaction,we integrate a gating mechanism for feature fusion with a complementary algorithm for interactive optimization.Extensive experiments on two datasets demonstrate the superiority of the proposed model.展开更多
文摘This paper presents a novel modified inter- active honey bee mating optimization （IHBMO） base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources （DERs）. The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting, A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduc- tion in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power orDERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.
基金funded by the State Grid Corporation of China project:Cooperative Simulation of Power Grid and Communication Gridthe National Natural Science Funds 51407030China Postdoctoral Science Foundation 121809
文摘With large-scale development of distributed generation(DG) and its potential role in microgrids, the microgrid cluster(MGC) becomes a useful control model to assist the integration of DG. Considering that microgrids in a MGC, power dispatch optimization in a MGC is dif-ficult to achieve. In this paper, a hybrid interactive communication optimization solution(HICOS) is suggested based on flexible communication, which could be used to solve plug-in or plug-out operation states of microgrids in MGC power dispatch optimization. HICOS consists of a hierarchical architecture: the upper layer uses distributed control among multiple microgrids, with no central controller for the MGC, and the lower layer uses a central controller for each microgrid. Based on flexible communication links among microgrids, the optimal iterative information are exchanged among microgrids, thus HICOS would gradually converge to the global optimal solution.While some microgrids plug-in or plug-out, communication links will be changed, so as to unsuccessfully reach optimal solution. Differing from changeless communication links in traditional communication networks, HICOS redefines the topology of flexible communication links to meet the requirement to reach the global optimal solutions.Simulation studies show that HICOS could effectively reach the global optimal dispatch solution with non-MGC center. Especially, facing to microgrids plug-in or plug-out states, HICOS would also reach the global optimal solution based on refined communication link topology.
基金funded by the National Natural Science Foundation of China(Nos.62172090 and 62202209)the Key Laboratory of Computer Network and Information Integration of Ministry of Education of China(No.93K-9-2024-04)the Jiangsu Province Higher Education Basic Science(Natural Science)Foundation(No.24KJB520014).
文摘The problem of Point-Of-Interest(POI)recommendation,based on the user’s historical checkin records,determines whether a user checks in at specific POI.However,the user-POI data have a longtail distribution phenomenon.To mitigate the sparsity of check-in data,it is a good idea to exploit the sufficient attributes of POI and recommend POIs in both geography wise and category wise.Generally,this problem can be treated as two specific tasks with feature combination,ignoring cross-task dependencies and feature disentanglement.To address the aforementioned problems,this paper proposes a novel joint framework named InteractPOI,enabling two-stage interaction bewteen geographywise and category-wise POI recommendations.Specifically,this paper comprehensively considers the sequence effect and the neighbor effect both from geography wise and category wise.For the firststage interaction,we design a disentangled graph embedding model to distinguish different influencing factors from geography wise and category wise.For the second-stage interaction,we integrate a gating mechanism for feature fusion with a complementary algorithm for interactive optimization.Extensive experiments on two datasets demonstrate the superiority of the proposed model.
