scholarly journals Energy Management-Based Predictive Controller for a Smart Building Powered by Renewable Energy

2020 ◽  
Vol 12 (10) ◽  
pp. 4264 ◽  
Author(s):  
Younès Dagdougui ◽  
Ahmed Ouammi ◽  
Rachid Benchrifa
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Residential Building ◽  
Centralized Control ◽  
Control Approach ◽  
Electrical Grid ◽  
Smart Building ◽  
Building Energy Management ◽  
High Level ◽  
Horizon Planning

This paper presents a smart building energy management system (BEMS), which is in charge of optimally controlling the sustainable operation of a building-integrated-microgrid (BIM). The main objective is to develop an advanced high-level centralized control approach-based model predictive control (MPC) considering variations of renewable sources and loads. A finite-horizon planning optimization problem is developed to control the operation of the BIM. The model can be implemented as a BEMS for the BIM to manipulate the indoor temperature and optimize the operation of the system’s units. A centralized MPC-based algorithm is implemented for the power management scheduling of all sub-systems as well as power exchanges with the electrical grid. The MPC algorithm is verified over case studies applied to two floors residential building considering the climate condition of a typical day of March, where the effects of both loads and thermal resistance of building shell on the operation of the BIM are analyzed via numerical simulations. The analysis shows that 96% of the total electrical load has been fulfilled by the local production where 23% represents the total electric output of the micro-CHP and 73% is the renewable energy production. The deficit, which represents only 4%, is purchased from the electrical distribution network (EDN).

scholarly journals Conception and Validation of Smart Building Energy Management System BEMS Using the Discrete Event System Specification DEVS

2014 ◽  
Vol 10 (2) ◽  
pp. 107 ◽  
Author(s):  
Abdelfettah Maatoug ◽  
Ghalem Belalem
Keyword(s):  
Energy Management ◽  
Management System ◽  
Discrete Event ◽  
Building Energy ◽  
Energy Management System ◽  
System Specification ◽  
Reactive Control ◽  
Smart Building ◽  
Building Energy Management ◽  
High Level

The improvement of the energetic behavior of buildings has turned into a major issue due to the high level of energy consumption. In this context, the building is represented as a dynamical system and a system of data acquisition is developed, which allows the measurement of environmental and energetic parameters, so as to describe the behavior of the building interacting with its direct environment. Research related to energy management can be divided into two categories: predictive control (anticipative) and adaptive control (reactive). A new building energy management system (BEMS) which is the chosen system to validate, treats a long-term anticipative control and introduces a reactive control that adds another level of intelligence to the BEMS.The main goal of this paper is to propose a model using the formalism DEVS to describe and simulate the BEMS. Our motivation is explained by the fact that DEVS is a tool for modeling of discrete event systems and it divides the overall system into subsystems in order to facilitate the achievement which is consistent with the characteristics of multilayer architecture of the chosen system.

scholarly journals Application of Model Transformation for Optimized Building Energy Management

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Energy Management ◽  
Building Energy ◽  
Mixed Integer ◽  
Smart Building ◽  
Integer Linear Programming Problem ◽  
Building Energy Management ◽  
Management Application ◽  
Hinge Model ◽  
High Level ◽  
Transformation Processes

This paper describes an approach aiming to automatically transform a model describing a high level physical behavior model into two different optimized building energy management application models. The first step consists in building a hinge model composed of element models. Then based on MDE approach, this model is projected, according to transformation processes, to application models. This paper presents core specifications of manipulation and transformation of hinge model. To illustrate this approach, an example of transformation into both an acausal anticipative model based on mixed integer linear programming problem and a non-linear causal model for fast simulated annealing optimization are shown. These models are used for energy management of a smart building platform named PREDIS/MHI.

scholarly journals Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2338
Author(s):  
Sofia Agostinelli ◽  
Fabrizio Cumo ◽  
Giambattista Guidi ◽  
Claudio Tomazzoli
Keyword(s):  
Artificial Intelligence ◽  
Renewable Energy ◽  
Energy Management ◽  
Three Dimensional ◽  
Cost Effective ◽  
Automation System ◽  
Climate Conditions ◽  
Digital Twin ◽  
Building Energy Management ◽  
Computing Paradigm

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements.

scholarly journals Modeling and Optimization of Smart Building Energy Management System Considering Both Electrical and Thermal Load

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 574
Author(s):  
Muhammad Hilal Khan ◽  
Azzam Ul Asar ◽  
Nasim Ullah ◽  
Fahad R. Albogamy ◽  
Muhammad Kashif Rafique
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Demand ◽  
Storage System ◽  
Building Energy ◽  
Energy Management System ◽  
Smart Building ◽  
Building Energy Management ◽  
Real Coded Genetic Algorithm ◽  
The Impact

Energy consumption in buildings is expected to increase by 40% over the next 20 years. Electricity remains the largest source of energy used by buildings, and the demand for it is growing. Building energy improvement strategies is needed to mitigate the impact of growing energy demand. Introducing a smart energy management system in buildings is an ambitious yet increasingly achievable goal that is gaining momentum across geographic regions and corporate markets in the world due to its potential in saving energy costs consumed by the buildings. This paper presents a Smart Building Energy Management system (SBEMS), which is connected to a bidirectional power network. The smart building has both thermal and electrical power loops. Renewable energy from wind and photo-voltaic, battery storage system, auxiliary boiler, a fuel cell-based combined heat and power system, heat sharing from neighboring buildings, and heat storage tank are among the main components of the smart building. A constraint optimization model has been developed for the proposed SBEMS and the state-of-the-art real coded genetic algorithm is used to solve the optimization problem. The main characteristics of the proposed SBEMS are emphasized through eight simulation cases, taking into account the various configurations of the smart building components. In addition, EV charging is also scheduled and the outcomes are compared to the unscheduled mode of charging which shows that scheduling of Electric Vehicle charging further enhances the cost-effectiveness of smart building operation.

Smart Building Energy Management: Load Profile Prediction using Machine Learning

2021 ◽  
Author(s):  
G. Revati ◽  
J. Hozefa ◽  
S. Shadab ◽  
A. Sheikh ◽  
S. R. Wagh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Management ◽  
Building Energy ◽  
Load Profile ◽  
Smart Building ◽  
Building Energy Management

Decision support methodologies and day-ahead optimization for smart building energy management in a dynamic pricing scenario

2020 ◽  
Vol 216 ◽  
pp. 109963 ◽  
Author(s):  
A. Pallante ◽  
L. Adacher ◽  
M. Botticelli ◽  
S. Pizzuti ◽  
G. Comodi ◽  
...  
Keyword(s):  
Decision Support ◽  
Energy Management ◽  
Dynamic Pricing ◽  
Building Energy ◽  
Smart Building ◽  
Building Energy Management

Parallel building: a complex system approach for smart building energy management

2019 ◽  
Vol 6 (6) ◽  
pp. 1452-1461
Author(s):  
Abdulaziz Almalaq ◽  
Jun Hao ◽  
Jun Jason Zhang ◽  
Fei-Yue Wang
Keyword(s):  
Complex System ◽  
Energy Management ◽  
System Approach ◽  
Building Energy ◽  
Smart Building ◽  
Building Energy Management

MPC-Based Appliance Scheduling for Residential Building Energy Management Controller

2013 ◽  
Vol 4 (3) ◽  
pp. 1401-1410 ◽  
Author(s):  
Chen Chen ◽  
Jianhui Wang ◽  
Yeonsook Heo ◽  
Shalinee Kishore
Keyword(s):  
Energy Management ◽  
Residential Building ◽  
Building Energy ◽  
Building Energy Management
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