Abstract
Advanced sensor and communication technologies can make natural gas supply systems smarter than ever before, in both system management and operation. This paper presents the development of a novel data-driven Demand Side Management, whose framework includes demand forecasting, customer response analysis, prediction of dynamic condition of the gas network, quick supply reliability evaluation, multi-objective optimization and decision-making. The aims of this DSM method are to smooth load profiles, improve company profit and enhance system reliability, by means of a dynamic pricing strategy. To verify the effectiveness of the developed framework, a case study is considered, concerning the management of a relatively complex gas supply system, wherein four different pricing periods are introduced for comprehensively testing. The results in the case study show that the DSM framework is able to effectively achieve the targets of peak shaving and valley filling. Besides, it can significantly and stably improve the system efficiency and reliability, for different pricing periods. Finally, pricing period determination is discussed in relation to the features of performance.
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.
