Modeling and application of marketing and distribution data based on graph computing

Integrating marketing and distribution businesses is crucial for improving the coordination of equipment and the efficient management of multi-energy systems.New energy sources are continuously being connected to distribution grids;this,however,increases the complexity of the information structure of marketing and distribution businesses.The existing unified data model and the coordinated application of marketing and distribution suffer from various drawbacks.As a solution,this paper presents a data model of"one graph of marketing and distribution"and a framework for graph computing,by analyzing the current trends of business and data in the marketing and distribution fields and using graph data theory.Specifically,this work aims to determine the correlation between distribution transformers and marketing users,which is crucial for elucidating the connection between marketing and distribution.In this manner,a novel identification algorithm is proposed based on the collected data for marketing and distribution.Lastly,a forecasting application is developed based on the proposed algorithm to realize the coordinated prediction and consumption of distributed photovoltaic power generation and distribution loads.Furthermore,an operation and maintenance(O&M)knowledge graph reasoning application is developed to improve the intelligent O&M ability of marketing and distribution equipment.

Strategic Bidding in Distribution Network Electricity Market Focusing on Competition Modeling and Uncertainties

Developing the electricity market at the distribution level can facilitate the energy transactions in distribution networks with a high penetration level of distributed energy resources(DERs)and microgrids(MGs).However,the lack of comprehensive information about the marginal production cost of competitors leads to uncertainties in the optimal bidding strategy of participants.The electricity demand within the network and the price in the wholesale electricity market are two other sources of the uncertainties.In this paper,a day-ahead-market-based framework for managing the energy transactions among MGs and other participants in distribution networks is introduced.A game-theory-based method is presented to model the competition and determine the optimal bidding strategy of participants in the market.Robust optimization technique is employed to capture the uncertainties in the marginal cost of competitors.Additionally,the uncertainties in demand are modeled using a scenario-based stochastic approach.The results ob-tained from case studies reveal the merit of considering competition modeling and uncertainties.

Geographical Distribution Of Chinese Car Market

Ⅰ. Brief Account of Geographical Divi-sion The formation and development of the do-mestic car market are heavily influenced by the development of geographic economic momen-tum. On the basis of the general economic

Local Energy and Planned Ramping Product Joint Market Based on a Distributed Optimization Method

High penetration of renewable energy generation(REG)in the distribution system increases both the power uncertainty at a given interval and the power variation between two intervals.Reserve markets addressing power uncertainty have been widely investigated.However,there is a lack of market mechanisms regarding the power variation of the load and REGs.This paper thus defines a planned ramping(PR)product to follow the net load variation and extends the local energy market to include the trading of PR products.Players are economically compensated for their PR products.Bidding models of dispatchable generators and flexible load aggregators in the joint market are investigated.To solve the market problem in polynomial time,a distributed market clearing method is developed based on the ADMM algorithm.The joint market is tested on a modified IEEE 33-bus system.It verifies that introducing the PR market can encourage flexible loads to provide more PR service to accommodate the net load variation.As such,the ramping cost of dispatchable generators is reduced by 29.09%in the test case.The planned energy curtailment from REG is also reduced.The computational efficiency of the proposed distributed clearing method is validated by comparing it with a centralized method.