The energy performance in buildings is influenced by many factors, such as ambient weather conditions, building structure and characteristics, the operation of sub-level components like lighting and HVAC systems, occupancy and their behavior. This complex situation makes it very difficult to accurately implement the prediction of building energy consumption. This paper reviews recently developed models for solving this problem, which include elaborate and simplified engineering methods, statistical methods and artificial intelligence methods. Previous research work concerning these models and relevant applications are introduced. Based on the analysis of previous work, further prospects are proposed for additional research reference.

A review on the prediction of building energy consumption

How to effectively utilize low and medium temperature energy is one of the solutions to alleviate the energy shortage and environmental pollution problems. In the past twenty years, because of its feasibility and reliability, organic Rankine cycle has received widespread attentions and researches. In this paper, it reviews the selections of working fluids and expanders for organic Rankine cycle, including an analysis of the influence of working fluids' category and their thermodynamic and physical properties on the organic Rankine cycle's performance, a summary of pure and mixed working fluids' screening researches for organic Rankine cycle, a comparison of pure and mixture working fluids' applications and a discussion of all types of expansion machines' operating characteristics, which would be beneficial to select the optimal working fluid and suitable expansion machine for an effective organic Rankine cycle system.

A review of working fluid and expander selections for organic Rankine cycle

An organic Rankine cycle (ORC) machine is similar to a conventional steam cycle energy conversion system, but uses an organic fluid such as refrigerants and hydrocarbons instead of water. In recent years, research was intensified on this device as it is being progressively adopted as premier technology to convert low-temperature heat resources into power. Available heat resources are: solar energy, geothermal energy, biomass products, surface seawater, and waste heat from various thermal processes. This paper presents existing applications and analyzes their maturity. Binary geothermal and binary biomass CHP are already mature. Provided the interest to recover waste heat rejected by thermal devices and industrial processes continue to grow, and favorable legislative conditions are adopted, waste heat recovery organic Rankine cycle systems in the near future will experience a rapid growth. Solar modular power plants are being intensely investigated at smaller scale for cogeneration applications in buildings but larger plants are also expected in tropical or Sahel regions with constant and low solar radiation intensity. OTEC power plants operating mainly on offshore installations at very low temperature have been advertised as total resource systems and interest on this technology is growing in large isolated islands.

Low­grade heat conversion into power using organic Rankine cycles - A review of various applications

Theory and applications of HVAC control systems – A review of model predictive control (MPC)

Given restrictions that comfort conditions in the interior of a building are satisfied, it becomes obvious that the problem of energy conservation is a multidimensional one. Scientists from a variety of fields have been working on this problem for a few decades now; however, essentially it remains an open issue. In the beginning of this article, we define the whole problem in which the topics are: energy, comfort and control. Next, we briefly present the conventional control systems in buildings and their advantages and disadvantage. We will also see how the development of intelligent control systems has improved the efficiency of control systems for the management of indoor environment including user preferences. This paper presents a survey exploring state of the art control systems in buildings. Attention will be focused on the design of agent-based intelligent control systems in building environments. In particular, this paper presents a multi-agent control system (MACS). This advanced control system is simulated using TRNSYS/MATLAB. The simulation results show that the MACS successfully manage the user’s preferences for thermal and illuminance comfort, indoor air quality and energy conservation.

Advanced control systems engineering for energy and comfort management in a building environment—A review

A thermal model for photovoltaic systems

Building thermal model reduction using nonlinear constrained optimization

Climate change mitigation and sustainable practices are now at the top of political and technical agendas. Environmental system modelling provides a way of appraising options and this book will make a significant contribution to the uptake of such systems. It provides knowledge of the principles involved in modelling systems, builds confidence amongst designers and offers a broad perspective of the potential of these new technologies. The aim of the book is to provide an understanding of the concepts and principles behind predictive modelling methods; review progress in the development of the modelling software available; and explore modelling in building design through international case studies based on real design problems.

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Modelling Methods for Energy in Buildings

Performance analysis of the Chena binary geothermal power plant

Most heating, ventilation and air conditioning (HVAC) control systems are considered as temperature control problems. In this work, the predicted mean vote (PMV) is used to control the indoor temperature of a space by setting it at a point where the PMV index becomes zero and the predicted percentage of persons dissatisfied (PPD) achieves a maximum threshold of 5%. This is achieved through the use of a fuzzy logic controller that takes into account a range of human comfort criteria in the formulation of the control action that should be applied to the heating system to bring the space to comfort conditions. The resulting controller is free of the set up and tuning problems that hinder conventional HVAC controllers. Simulation results show that the proposed control strategy makes it possible to maximize the indoor thermal comfort and, correspondingly, a reduction in energy use of 20% was obtained for a typical 7-day winter period when compared with conventional control.

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Chris Underwood

Papers

A thermal model for photovoltaic systems

Building thermal model reduction using nonlinear constrained optimization

Modelling Methods for Energy in Buildings

Performance analysis of the Chena binary geothermal power plant

Thermal comfort based fuzzy logic controller