Fulin Wang

Building Energy Management: Integrated Control of Active and Passive Heating, Cooling, Lighting, Shading, and Ventilation Systems

Buildings account for nearly 40% of global energy consumption. About 40% and 15% of that are consumed, respectively, by HVAC and lighting. These energy uses can be reduced by integrated control of active and passive sources of heating, cooling, lighting, shading and ventilation. However, rigorous studies of such control strategies are lacking since computationally tractable models are not available. In this paper, a novel formulation capturing key interactions of the above building functions is established to minimize the total daily energy cost. To obtain effective integrated strategies in a timely manner, a methodology that combines stochastic dynamic programming (DP) and the rollout technique is developed within the price-based coordination framework. For easy implementation, DP-derived heuristic rules are developed to coordinate shading blinds and natural ventilation, with simplified optimization strategies for HVAC and lighting systems. Numerical simulation results show that these strategies are scalable, and can effectively reduce energy costs and improve human comfort.

An integrated control of shading blinds, natural ventilation, and HVAC systems for energy saving and human comfort

Improving the control of shading blinds, lights, natural ventilation, and HVAC systems while satisfying human comfort requirements can result in significant energy cost savings with time-of-day electricity pricing. Traditionally, the above-mentioned devices are controlled separately. In this paper, a novel formulation for the integrated control and the corresponding solution methodology are presented. The problem is to minimize daily energy costs of lights and HVAC systems while satisfying equipment capacities, system dynamics, and human comfort. The problem is complicated since 1) individual rooms are coupled as they compete for the HVAC with limited capacity and nonlinear characteristics, and 2) the problem is believed to be NP-hard in view that decision variables are all discrete. A solution methodology that combines Lagrangian relaxation and stochastic dynamic programming is developed within the surrogate optimization framework to obtain near-optimal strategies. These strategies are further refined to become novel control rules for easy practical implementation. Numerical simulation results show that both of the above strategies can effectively reduce the total energy cost, and that the integrated control works better than selected traditional control strategies.

Research of the Room Occupant Complaining Behavior Pattern for the Indoor Environmental Control

The present indoor environmental control is implemented according to indoor environmental parameter set points. However room occupants generally lack of the knowledge on comfortable values of indoor environmental parameters. The next generation of indoor environmental control should be based on room occupants’ actual perception instead of set points. This paper describes some fundamental work for developing such a system. Experiments were conducted to collect room occupants’ complaints when they feel dissatisfied to the indoor environment. The collected data were analyzed to find the characteristics complaining behaviors.

A unified control framework of HVAC system for thermal and acoustic comforts in office building

Intelligent building system attracts more and more attention in both academic and industrial communities. Learning human comfort requirements and incorporating it into building control system is one of the important issues. In the traditional HVAC control system, the thermal comfort and the acoustic comfort are often conflicted and we lack of a scheme to trade off them well. In this paper, we propose a unified control framework based on reinforcement learning to balance the multiple dimension comforts, including the thermal and acoustic comforts. We utilize the users complaints in thermal and acoustic sensations as feedback and combine the current environment and devices information to learn the personalized optimal control policy using online Q-learning. The challenge caused by the complaints is coped with an incorporated perception estimation scheme in the Q-learning reward design. Both simulation results and the field experimental results demonstrate the effectiveness of the algorithm, especially in the adaptivity to the individual tradeoff between thermal and acoustic comfort.

Case studies of fault diagnosis and energy saving in buildings using data mining techniques

Building Automation Systems (BASs) have been developed to provide a safe, comfortable, and energy-efficient indoor environment for households. A tremendous volume and enormous variety of building data are collected and stored in BASs. However, these data could not be completely utilized by traditional data analytics due to the huge volume and heterogeneous nature. In this paper, case studies are carried out using data mining techniques to find the potential value and discover the hidden knowledge in building area. We proposed a new fault diagnosis approach for chillers/AHU during operation. A promising guide to knowledge selection and interpretation in associate rule mining is presented to capture more energy saving potential opportunities. We also demonstrate the importance of occupancy information in improving building operation performance. The approaches and findings presented are not only for these cases but also feasible for more applications.

Study on the Optimal Control Strategy for Condensing Side of Chiller Systems

The performance curves of typical chillers available from the present market are investigated. These performance curves are fitted to develop a chiller model, which together with pump and cooling tower models are used to study the optimal control strategy for condensing side of chiller systems. The optimization objective is to minimize the total energy use of chillers, condensing pumps, and cooling tower fans. The optimization problem is solved by traversing all possible combinations of chiller water flow rates, cooling tower air flow rates, and ambient air wet-bulb temperatures. Then the optimal solutions are analyzed to find out applicable rule-based control strategies that are not far from optimal solutions and reliable as well. The rule-based control strategy is to keep one or two constant cooling water flow rates during whole operational season according to the number of running chillers and to keep cooling tower air flow rate at a constant ratio to cooling water flow rate. Because this rule-based control strategy does not use sensor measured data, such as wet-bulb air temperature, it is free of sensor faults and can be more robust and reliable than the currently used control strategies, most of which use cooling water temperature or ambient air wet-bulb temperature to decide the cooling water flow rate or air flow rate of cooling tower fans.

An Investment-Benefit Assessing Approach for Intelligent Buildings

For the purpose of achieving high performance of intelligent buildings, it needs to pay expanses for maintaining the intelligent systems. So it is in great need to analyze the costs and benefits of building intelligent system to help building owners to make decision on installing intelligent systems or not. This paper proposes an investment-benefit assessing approach for building intelligent systems. Net Present Value (NPV) is used as an index to evaluate the performance of building intelligent system. The NPV is calculated by analyzing the initial capital investment, maintenance costs, and the tangible and intangible benefits in building life cycle. The intangible benefits are quantified using a series of indexes which represent the cash flows brought by the intangible benefits. Different weights of these indexes are used to express the different contributions of these intangible benefits. Analytical Hierarchy Process (AHP) method [ is used to quantify the weights of the indexes.

Showcase for a satisfaction based group comfort control system

In this showcase, a satisfaction based group comfort control system is introduced based on our previous work. The key feature of this system is that the occupant perception of the indoor thermal environment is used as feedback signal to the control system in for a group of occupants in office buildings.

Heating and Cooling Load Characteristics Comparison between Normal Building and Low Energy Consumption Building

In this research, a normal building and low energy consumption building were chosen to compare and analyze heating and cooling load characteristics. Firstly, the abstract of two buildings were carried out. Secondly, methodology of measurement and calculation was researched. At last the heating and cooling load of two buildings was examined using this methodology.

Improving Air-Conditioners’ Energy Efficiency Using Green Roof Plants

Environment and energy issues are considered to be most urgent things nowadays even in future. A lot of researches have been conducted to study how to prevent global warming and reduce energy consumption. In the field of building and urban environment, green roof attracts a lot of researchers’ attention because it is considered to be a good solution for improving urban thermal environment by mitigating heat island and to reduce building cooling energy consumption by reducing cooling load. Alexandria et al. (2008) analyzed how much the urban canyon temperature can be decreased due to green walls and green roofs. Takebayashi et al. (2007) compared the building surface heat transfer of green roofs with common roofs and high reflection roofs. Kumar et al. (2005) developed a mathematical model to evaluate the cooling potential and solar shading effect of green roofs. Wong et al. (2003) analyzed the thermal benefits of green roofs in tropical area. Di et al. (1999) measured an actual green wall to analyze how much cooling effect is achieved. Elena (1998) analyzed the cooling potential of green roofs. Besides studying the green roofs’ benefits of heat island mitigation and thermal isolation, the cost vs. benefit is also analyzed (Clerk et al., 2008) and green roof plants selection is analyzed as well (Spala et al., 2008).