International Journal of Computer and Applications

Buildings all around the world consume a significant amount of energy, which is more or less one-third of the total primary energy resources. This has raised concerns over energy supplies, rapid energy resource depletion, rising building service demands, improved comfort life styles along with the increased time spent in buildings; consequently, this has shown a rising energy demand in the near future. However, contemporary buildings’ energy efficiency has been fast tracked solution to cope/limit the rising energy demand of this sector. Building energy efficiency has turned out to be a multi-faceted problem, when provided with the limitation for the satisfaction of the indoor comfort index. However, the comfort level for occupants and their behavior have a significant effect on the energy consumption pattern. It is generally perceived that energy unaware activities can also add one-third to the building’s energy performance. Researchers and investigators have been working with this issue for over a decade; yet it remains a challenge. This review paper presents a comprehensive and significant research conducted on state-of-the-art intelligent control systems for energy and comfort management in smart energy buildings (SEB’s). It also aims at providing a building research community for better understanding and up-to-date knowledge for energy and comfort related trends and future directions. The main table summarizes 121 works closely related to the mentioned issue. Key areas focused on include comfort parameters, control systems, intelligent computational methods, simulation tools, occupants’ behavior and preferences, building types, supply source considerations and countries research interest in this sector. Trends for future developments and existing research in this area have been broadly studied and depicted in a graphical layout. In addition, prospective future advancements and gaps have also been discussed comprehensively.

A review on optimized control systems for building energy and comfort management of smart sustainable buildings

In the last few years, the application of Model Predictive Control (MPC) for energy management in buildings has received significant attention from the research community. MPC is becoming more and more viable because of the increase in computational power of building automation systems and the availability of a significant amount of monitored building data. MPC has found successful implementation in building thermal regulation, fully exploiting the potential of building thermal mass. Moreover, MPC has been positively applied to active energy storage systems, as well as to the optimal management of on-site renewable energy sources. MPC also opens up several opportunities for enhancing energy efficiency in the operation of Heating Ventilation and Air Conditioning (HVAC) systems because of its ability to consider constraints, prediction of disturbances and multiple conflicting objectives, such as indoor thermal comfort and building energy demand. Despite the application of MPC algorithms in building control has been thoroughly investigated in various works, a unified framework that fully describes and formulates the implementation is still lacking. Firstly, this work introduces a common dictionary and taxonomy that gives a common ground to all the engineering disciplines involved in building design and control. Secondly the main scope of this paper is to define the MPC formulation framework and critically discuss the outcomes of different existing MPC algorithms for building and HVAC system management. The potential benefits of the application of MPC in improving energy efficiency in buildings were highlighted.

/pdf/model-predictive-control-mpc-for-enhancing-building-and-hvac-3bxzsgstnj.pdf

Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities

This paper investigates heat pump systems in smart grids, focussing on fields of application and control approaches that have emerged in academic literature. Based on a review of published literatu ...

https://zenodo.org/record/895978/files/article.pdf

On heat pumps in smart grids: A review

All you need to know about model predictive control for buildings

Intelligent Optimized Control System for Energy and Comfort Management in Efficient and Sustainable Buildings

The primary energy supply of Pakistan in the financial year 2009–10 was 63.088 million tonnes of oil equivalent (MTOE). Globally, renewable energies generation is around (19%) [1]. Pakistan has a yearly average solar energy shining potential of about 19 Mega Joules per square meter, with 7.6 hours per day with an average solar radiation of 5–7 kW h/(m2 day). An alarming stage for the government to take serious steps to tackle energy demand, in vision to inclining oil markets, depletion of gas reserves, huge electricity demand and supply gap, lessening offorest reserves, calamity (floods, heavy rainfalls, earth quakes, melting of glaciers etc.), Kyoto bindings etc. All these factors are indicating for the transition towards renewable energy technologies.

Solar energy: Topographical asset for Pakistan

The world's population, approximately 90% spend most of their time inside the buildings, which results in 40 - 45% of the total energy consumption. The annual demand of building energy is increasing in the range of 1.5 - 1.9% due to growing world's population. To reduce energy consumption and wastage, effective energy management within the buildings is very essential. Therefore, the concept of smart and energy efficient buildings has become a future trend. It becomes challenging to design and develop the control system for such buildings that require energy efficiency with optimum comfort level for dwellers. In this connection, various studies have been conducted to meet the challenges in this area. However, very limited studies are reported in the literature, especially on the relationship model between energy consumption and comfort parameters within the building. Therefore, in this work, a robust stochastic control model (RSCM) has been developed between the relationship of energy consumption and comfort parameters. The developed model will be helpful for the further minimization of building energy consumption with maximum comfort level in designing building control system.

Robust Stochastic Control Model for Energy and Comfort Management of Buildings

Stochastic optimized intelligent controller for smart energy efficient buildings

The building sector consumes approximately one-third of global primary energy. The energy and environmental performance of buildings for all their energy uses have to be revisited. Building energy retrofitting provides substantial opportunities to reduce the level of building energy consumption, saves cost, improves comfort level, and mitigates greenhouse gas emissions. Building retrofitting is a form of technical intrusion in the energy system of a building to effectively utilize its energy. The aim of the chapter is to identify the optimal cost-effective energy-retrofitting strategy. A holistic retrofitting scenario has been considered that includes reduced energy consumption, cost savings, capital investments, emissions, technology behavioral change, and comfort indexing, along with sustainability concerns involving geometry and envelope construction. However, this study primarily focused on energy systems within the building envelope. In addition, various uncertainty parameters and risk factors have been considered. Multifaceted optimal retrofitting strategies based on the optimized decisions are prioritized to address these challenges. Additionally, some challenges for simulation toolkits have been discussed for the success of the building energy retrofit project. This work helps building practitioners and researchers with in-depth understanding challenges for cost-effective optimal retrofitting within buildings to attain energy conservation and sustainability.

Pervez Hameed Shaikh

Papers

Intelligent Optimized Control System for Energy and Comfort Management in Efficient and Sustainable Buildings

Solar energy: Topographical asset for Pakistan

Robust Stochastic Control Model for Energy and Comfort Management of Buildings

Stochastic optimized intelligent controller for smart energy efficient buildings

An Overview of the Challenges for Cost-Effective and Energy-Efficient Retrofits of the Existing Building Stock