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PID Neural Network control of SUT building energy management system
, Article Proceedings of the 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2005, Monterey, CA, 24 July 2005 through 28 July 2005 ; Volume 1 , 2005 , Pages 682-686 ; Ghafari, A. S ; Hannani, S. K ; Sharif University of Technology
2005
Abstract
PID Neural Network controller design for Sharif University of Technology (SUT) Building Energy Management System (BEMS) is addressed in this paper. The most important characteristics of process systems are time delay with model uncertainties. Artificial neural networks can perform adaptive controller properties through learning processes. FID neural network has the advantages of both conventional PID controllers and the neural structure. Simulation results using Modified Hooke-Jeeves Optimization Method show that this controller has short convergence time and quick learning speed and the performance of the closed loop system is very good. © 2005 IEEE
Energy management of smart home considering residences' satisfaction and PHEV
, Article 2018 International Conference on Smart Energy Systems and Technologies, SEST 2018, 10 September 2018 through 12 September 2018 ; 2018 ; 9781538653265 (ISBN) ; Shokri Gazafroudi, A ; Corchado, J. M ; Ebrahimi, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2018
Abstract
Regarding the increasing number of electrical devices in the smart homes that leads to increase in total electricity consumption and cost, it is essential to use energy management methods to reduce the electricity cost. However, this can cause resident's dissatisfaction. Hence, it is important to define a method in which cost and dissatisfaction be optimized simultaneously. Among different services, an electric vehicle is the one that can be used as an energy storage system, so it can reduce the daily cost despite of increasing the total energy consumption. In this paper, we study the effect of the EV on the cost and dissatisfaction in our proposed method. © 2018 IEEE
Energy Management of a Residential Prosumer Employing Machine Learning Techniques
, M.Sc. Thesis Sharif University of Technology ; Moeini Eghtaei, Moein (Supervisor)
Abstract
This thesis proposes an energy management model for a residential prosumer building which is a multi-carrier energy hub in a grid-connected mode. Power may be bought and sold between the building energy system and the power grid. Solar panels and solar water heaters are integrated into the building's energy system to create electricity and heat, which may be used in a variety of ways: used immediately to meet the home's demands, stored in batteries and heat banks for later use, or sold back to the power grid to earn income. The energy dispatch is managed such that the overall energy consumption cost is minimized, considering the variation in electricity price (grid tariff), renewable energy...
Model reference adaptive control of SUT building energy management system
, Article 2005 ASME International Mechanical Engineering Congress and Exposition, IMECE 2005, Orlando, FL, 5 November 2005 through 11 November 2005 ; Volume 10 , 2006 , Pages 25-28 ; 0791842274 (ISBN) ; Selk Ghafari, A ; Hannani, S. K ; Sharif University of Technology
2006
Abstract
Model Reference Adaptive Controller (MRAC) design, for Sharif University of Technology (SUT) Building Energy Management System (BEMS) is addressed in this paper. A reference model with fuzzy adaptive control rules was employed to design the controller for a system with time delay and model parameter uncertainties. Simulation study shows good performance of the closed loop system with optimum energy consumption for this system under external load disturbance. Copyright © 2005 by ASME
Enhancement the economical and environmental aspects of plus-zero energy buildings integrated with INVELOX turbines
, Article Renewable Energy ; Volume 153 , 2020 , Pages 1355-1367 ; Jirdehi, M. A ; Amiri, N ; Omidi, S ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
A multi-objective energy management strategy for a plus-zero energy building during a year, incorporating renewable resources, air to water heat pump, micro-CHP, ventilation, energy storage systems and thermal-cooling-electrical loads have been proposed in this paper. In this strategy, a novel technology of wind turbine that has been known as INVELOX has been investigated and collaborated in ZEB planning to reach efficient plus-ZEB at lower cost and pollution. As well the building can sell and buy power to/from the upstream network. The total cost and pollution of the building have been considered as objective functions. Also, the effect of objective function priority on the planning of the...
Adaptive model predictive climate control of multi-unit buildings using weather forecast data
, Article Journal of Building Engineering ; Volume 32 , May , 2020 , Pages: 5-6 ; Rezaeizadeh, A ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
Energy use in buildings contributes a large part in global energy demand. To reduce energy use in this group of consumers, specially in cold seasons, an automatic control technique is proposed. In this paper, a model predictive controller (MPC) is employed to minimize the boiler activation time. The method uses the building model and incorporates the weather forecast data to act on the actuator in an optimal fashion while treating the user comfort constraints. This technique, as a part, can be embedded into the building energy management system. The building model parameters are obtained via an online identification process using unscented kalman filter (UKF). This identification is...
Transactive energy management of V2G-capable electric vehicles in residential buildings: an milp approach
, Article IEEE Transactions on Sustainable Energy ; Volume 13, Issue 3 , 2022 , Pages 1734-1743 ; 19493029 (ISSN) ; Ranjbar, H ; Fattaheian-Dehkordi, S ; Moeini Aghtaie, M ; Ehsan, M ; Shahidehpour, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2022
Abstract
This paper proposes a new energy management model for residential buildings to handle the uncertainties of demand and on-site PV generation. For this purpose, the building energy management system (BEMS) organizes a transactive energy (TE) market among plug-in electric vehicles (PEVs) to determine their charge/discharge scheduling. According to the proposed TE framework, the PEV owners get reimbursed by the BEMS for the flexibility they offer. In this regard, the PEV owners submit their response curves for reimbursement upon arrival. Then, the BEMS solves an optimization problem to maximize its own profit and determine the real-time TE market-clearing price. Afterward, based on the clearing...