Journal ArticleDOI
A System Architecture for Autonomous Demand Side Load Management in Smart Buildings
TLDR
This architecture can encapsulate the system functionality, assure the interoperability between various components, allow the integration of different energy sources, and ease maintenance and upgrading, and allows seamless integration of diverse techniques for online operation control, optimal scheduling, and dynamic pricing.Abstract:
This paper presents a system architecture for load management in smart buildings which enables autonomous demand side load management in the smart grid. Being of a layered structure composed of three main modules for admission control, load balancing, and demand response management, this architecture can encapsulate the system functionality, assure the interoperability between various components, allow the integration of different energy sources, and ease maintenance and upgrading. Hence it is capable of handling autonomous energy consumption management for systems with heterogeneous dynamics in multiple time-scales and allows seamless integration of diverse techniques for online operation control, optimal scheduling, and dynamic pricing. The design of a home energy manager based on this architecture is illustrated and the simulation results with Matlab/Simulink confirm the viability and efficiency of the proposed framework.read more
Citations
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Journal ArticleDOI
A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms
TL;DR: This paper provides a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program, and presents various optimization models for the optimal control of the DR strategies that have been proposed so far.
Journal ArticleDOI
A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings
Luis Hernandez,Carlos Baladrón,Javier M. Aguiar,Belen Carro,Antonio Sánchez-Esguevillas,Jaime Lloret,Joaquim Massana +6 more
TL;DR: This review discusses the most relevant studies on electric demand prediction over the last 40 years, and presents the different models used as well as the future trends, and analyzes the latest studies on demand forecasting in the future environments that emerge from the usage of smart grids.
Book ChapterDOI
Home energy management systems: A review of modelling and complexity
Marc Beaudin,Hamidreza Zareipour +1 more
TL;DR: A set of HEMS challenges such as forecast uncertainty, modelling device heterogeneity, multi-objective scheduling, computational limitations, timing considerations and modelling consumer well-being are discussed.
Journal ArticleDOI
Load forecasting, dynamic pricing and DSM in smart grid: A review
TL;DR: A comprehensive and comparative review of the LF and dynamic pricing schemes in smart grid environment, including Real Time Pricing (RTP), Time of Use (ToU) and Critical Peak Pricing (CPP) are presented.
Journal ArticleDOI
Automated Demand Response From Home Energy Management System Under Dynamic Pricing and Power and Comfort Constraints
TL;DR: In this paper, the authors present a comprehensive and general optimization-based home energy management controller, incorporating several classes of domestic appliances including deferrable, curtailable, thermal, and critical ones, to reduce the consumer's electricity bill whilst minimizing the daily volume of curtailed energy, and therefore considering the user's comfort level.
References
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Grid of the future
Ali Ipakchi,Farrokh Albuyeh +1 more
TL;DR: In this article, the authors argue that the transition to a smart grid has to be evolutionary to keep the lights on; on the other hand, the issues surrounding the smart grid are signifi cant enough to demand major changes in power systems operating philosophy.
Proceedings ArticleDOI
Optimal Real-Time Pricing Algorithm Based on Utility Maximization for Smart Grid
TL;DR: This paper analytically model the subscribers' preferences and their energy consumption patterns in form of carefully selected utility functions based on concepts from microeconomics and proposes a distributed algorithm which automatically manages the interactions among the ECC units at the smart meters and the energy provider.
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Domestic electricity use: A high-resolution energy demand model
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