In the year of 1990, the BEMS concept has been developed into an open web-based structure where internet has been utilized widely. Universally adapted communication protocols, such as BACNet and Lonworks have been applied in engineering practices and created huge opportunity for building energy conservation designs. In this research, the development of the BEMS system has been discussed and analyzed in detail including its hardware infrastructure and software requirements, so that the HVAC , lighting and power subsystems can be integrated while remote control can be achieved. The classification of BEMS system, to be adapted in Taiwan, has been proposed and published by the end of year 2006, which enables real-time online building energy auditing with energy conservation potential assessed. Design examples, such as general hospitals, department stores, hotels, have been selected and analyzed to demonstrate the feasibility in adapting BEMS system in Taiwan with successful results.

The demand for energy and cost efficient buildings has made architects and contractors more aware of the resources consumed by the built environment. While the actual economic and environmental costs of future construction can never be completely predicted, energy simulations and cost modeling have become accepted ways to guide the design and construction process by comparing possible outcomes. These tools are now commonplace in the construction industry, and researchers are continuing to develop new and innovative strategies to optimize building design and construction. Previous research has proven that genetic algorithms are effective methods to evaluate and optimize building design in situations that contain a large number of possible solutions. The technique makes a computationally difficult multi-optimization process possible but is still a reactive and time consuming process that focuses on evaluation rather than solution generation. This research presented in this paper builds upon established multi-objective optimization techniques that use an energy simulator to estimate a conceptual building’s energy use as well as construction cost. The study compares simulations of a simplified model of a 3-story inpatient hospital located in Atlanta, Georgia using a defined set of variables. A combined global minimum of annual energy consumption and total construction is sought after using a method that utilizes a genetic algorithm. The second phase of this research uses a modified approach that combines the traditional genetic algorithm with a seeding method that utilizes previous results. A new set of simulations were established that duplicates the initial trials using a slightly modified set of design variables. The simulation was altered, and the phase one trials were utilized as the first generation of simulated solutions. The objective of this thesis is to explore one method of making energy use and cost estimating more accessible to the construction industry by combining simulation optimization and indexing. The results indicate that this study’s proposed augmented approach has potential benefits to building design optimization, although more research is required to validate this hypothesis in its entirety. This study concludes that the proposed approach can potentially reduce the time needed for individual optimization exercises by creating a cumulative, robust catalog of previous computations that will inform and seed future analyses. The research was conducted in five general stages. The first part defines the research problem and scope of research to be conducted. In the second part, the concepts of genetic algorithms and energy simulation are explored in a comprehensive literature review. The remaining parts explain the trial simulations performed in this study. Part three explains the experiment’s methodology, and part four describes the simulation results. The fifth and final part looks at what the possible conclusions that can be made from analyzing the study’s results.

Critical areas in a hospital, such as Intensive Care Units (ICUs) and isolation rooms, are designed to strict health standards. More often than not, these areas operate continuously to maintain designed indoor conditions in order to ensure the safety of patients, making them energy intensive areas. Several attempts have been made to design them to be more energy-efficient. However, cases have emerged in hot and humid countries like Malaysia where combination of poor design, operation and maintenance practices, exacerbated by the humid outdoor conditions especially during night time, have led to occurrences of mould growth in these critical areas. A question arise whether energy efficient design of a critical area can be achieved without incurring a risk of mould growth due to factors like moisture transfer, or continuous part load operation of HVAC systems. The objective of research in this thesis is to investigate the trade-off between optimizing the building and HVAC systems and minimizing the risk of mould growth in hospital buildings located in hot and humid climates. The problem formulation is a single zone isolation room with dimensions based from a real-life isolation room of a district hospital in Malaysia. The design variables, namely HVAC systems and the details of building constructions were selected as input files for energy performance evaluation using EnergyPlus. The output from the simulation will be compared with the selected existing mould growth model during post processing to determine the optimum solution. Simulation and the generation of solutions will be repeated until the most optimum solution is achieved. A binary-encoded Genetic Algorithm (GA) was used as an approach to the minimisation of hospital building energy use. The GA is proven to be effective in performing multi-objective optimisation, since the objective functions for this research are more than one; namely, the minimum annual energy use in the isolation room and the critical indoor surface conditions, such as temperature and relative humidity, below which there would be no mould growth. The research has shown that the normal practice of isolation room design for Malaysian hospitals does not work in minimising energy use and minimising the risk of mould growth and a new design guideline for isolation rooms in Malaysia is recommended. The principal originality of the research will be the application of optimisation methods to investigate the relationship, or trade-off between energy use and the risk of mould growth, particularly for hospital buildings in a hot and humid climate. In this respect, the new knowledge will be on the optimisation procedure and required modelling/analysis components. This combinatorial approach would serve as decision making tool for building and HVAC systems designers in designing more energy-efficient overall environment systems in hospitals, with particular attention to critical areas that are operating continuously.

Buildings have a significant impact on energy usage and the environment. Much of the research in architectural sustainability has centered on economically advanced countries because they consume the most energy and have the most resources. However, sustainable architecture is important in developing countries, where the energy consumption of the building sector is increasing significantly. Currently, developing countries struggle with vaccine storage because vaccines are typically warehoused in old buildings that are poorly designed and wasteful of energy. This thesis created and studied a decision support tool that can be used to aid in the design of economically feasible Net Zero Energy vaccine warehouses for the developing world. The decision support tool used a simulation-optimization approach to combine an optimization technique with two simulation softwares in order to determine the cost-optimal design solution. To test its effectiveness, a new national vaccine storage facility located in Tunis, Tunisia was used. Nine building parameters were investigated to see which have the most significant effect on the annual energy usage and initial construction cost of the building. First, tests were conducted for two construction techniques, five different climates in the developing world, and three photovoltaic system prices to gain insight on the design space of the optimal solution. The results showed the difference between an economically efficient and economically inefficient Net Zero Energy building and the results were used to provide generalized climatic recommendations for all the building parameters studied. The final test showed the benefits of combining two optimization techniques, a design of experiments and a genetic algorithm, to form a two-step process to aid in the building design in the early stages and final stages of the design process. The proposed decision support tool can efficiently and effectively aid in the design of an economically feasible Net Zero Energy vaccine warehouse for the developing world.