Abstract
Orderly power utilization (OPU) is an important measure to alleviate contradiction between supply and demand in a power system peak load period. As a load management system becomes smarter, it is necessary to fully explore the interactive ability among users and make schemes for OPU more applicable. Therefore, an intelligent multi-agent apanage management system that includes a mutual aid mechanism (MAM) is proposed. In the decision-making scheme, users’ participation patterns and the potential of peak shifting and willingness are considered, as well as the interests of both power consumers and power grid are comprehensively considered. For residential users, the charging time for their electric vehicles (EVs) is managed to consume the locally distributed power generation. To fully exploit user response potential, the algorithm for improved clustering by fast search and find of density peaks (I-CFSFDP), i.e., clusters the power load curve, is proposed. To conduct electrical mutual aid among users and adjust the schemes reasonably, a multi-objective optimization model (M2OM) is established based on the cluster load curves. The objectives include the OPU control cost, the user’s electricity cost, and the consumption of distributed photovoltaic (PV). Our results of a case study show that the above method is effective and economical for improving interactive ability among users. Agents can coordinate their apanage power resources optimally. Experiments and examples verify the practicability and effectiveness of the improved algorithm proposed in this study.
Highlights
The smart grid plays an important role in improving the efficiency and quality of power supply.The peak clipping mode is widely used by power companies [1], but there are problems, such as severe peak power consumption and power shortage [2]
To improve the accuracy and practicability of load curve clustering, we propose the improved clustering by fast search and find of density peaks (I-CFSFDP) algorithm
The normalized dataset is dimensionally reduced by principal component analysis (PCA) to X∗ ; The k-nearest neighbors (KNN) matrix of X∗ is established by the k-d tree algorithm
Summary
The smart grid plays an important role in improving the efficiency and quality of power supply. To improve the accuracy of schemes, the participation patterns, willingness of users, as well as the interests of both the power grid and users should be fully considered. On the basis of the the load characteristic curve obtained by the I-CFSFDP, a multi-objective model is established It considers the participation patterns, willingness of users, as well as the interests of both the power grid and users. IMAS’s OPU scheme canfully reduce peakthe power consumption, improve execution efficiency, and fully above issues, we proposes an IMAS with a MAM for OPU in a multilayer power exploitConsidering the potentialthe of user interaction. The negotiation agent quickly adjusts the OPU plan according to the user’s aid willingness table. Table according to the aid situation to ensure the fairness of electricity consumption
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
