Main motivation to achieve a system able to reduce consumption of energy and natural resources, in terms of maintaining the comfort level of buildings with various purposes rises from both economic and social situation existing at national and international previously said.
In many buildings which have been implemented with projects to reduce energy consumption was found that the difference between measured consumption and the one projected to be achieved is disappointingly high, in some cases probably due to the use in the forecasting and planning of the systems, only of factors which did not take into account issues concerning the destination of these spaces, their mode of use and maintenance process of facilities. [1]
In some projects to rehabilitate buildings in terms of energy efficiency were considered only the passive elements to conserve heat, namely were performed insulation work, including facilities changing by replacing old heating and individual air conditioning systems with general air-conditioning systems. In these cases, were found decreases in operating costs and thus consumption by up to 20%.
For both new buildings and rehabilitation projects of old buildings, have began to be used more solutions to conserve or reduce energy use in air conditioning [2] or in the process of water heating [3] or by using of solutions that transform the solar energy into electricity or heat or solutions that use wind power to provide natural ventilation in buildings [4] or to be converted into electricity. Also it is noted that the interest of housing developers is granted for the use of an increasing percentage of resources which are referred above.
Although at first glance the measures referred above are leading to additional costs in completion of new buildings or implementation of energy rehabilitation projects of buildings, they have the capacity to absorb the cost differences between operating price of a rehabilitated building and operating price of a new building constructed using the above referred methods or the costs of a energy refurbished building. [5]
In the rows above there is a implementation strategy of the projects for energetic rehabilitation of the existing buildings or for design of the new buildings that has the main part only the advantage offered by the materials properties and the efficiency of the technical solutions used, without taking into account the interaction between these methods and the techniques with the destination space building, with the habits of the users or with calendar moment of an activity.
Still, there is a series of software instruments and also social instruments. These are in the form of behavioural studies for some categories of users (generally for the buildings with offices spaces). The main goal of these instruments is the achievement of some models and the development of solutions for improvement of the level of saving of the energetic and natural resources of the buildings by the interconnection of one or more actions and/or by assertion of an “eco-friendly” behaviour for the users of the respective spaces. [6],[7].
In this moment of the description of the current stage should be taken into account the conventional control systems located in buildings.
The main goal from the moment of control classic systems development for the things that are related with the comfort was the minimize of the energy consumption. One of the most used element of temperature control was the thermostat [8]. For avoiding the attrition created by the frequently change of the two states of the thermostat it were introduced and used on a larger scale the thermostats with the buffer zone. Although, by the implementation of this method could not achieve the limitation of the input/output cycles in time in the control process of temperature. This thing caused the increase of the energy consumption.
To solve this problem, the designers has elected the optimal solution offered by the advanced PID-controllers (Proportional-Integrate-Derivative) [8, 9]. Even with this improvement of the control systems, because of the imprecise establishment of the input data for PID-controllers, the control system is very unstable. As a solution, the designers have choose some type of controllers, that use new predictive or adaptive optimal control techniques.
The predictive or adaptive optimal control
Between 1980-1990 it was realized a series of important investigations for the optimal and predictive control strategies. Although the results of these investigations were not transposed later in the industry because the implementation problems. To be used the optimal controllers [10-19] or adaptive controllers [20] it is necessary the use of a mathematical model of the building. The predictive control [17, 21-24] gain greater importance because use the mathematical models for possible perturbations (heating due to sunstroke, the human presence, etc.). This model improves the comfort by reducing the overheating [25-27] mainly through the use of natural cooling from the night. Although, the mathematical model of the building that is made from the nonlinear models varies from a building to another.
The adaptive control systems have the capacity of self-adjustment at climate conditions for various buildings. Especially, the adaptive control systems developed through fuzzy technique are viewed as being the most efficient adaptive control systems for the buildings [11, 25, 20]. Another way to solve the buildings particularities problems, problems that must be taken into account in the adjustment of a controller has been solved by using the parameters estimation method [28]. But, have been identified also at these adaptive control systems a series of limitations determined by the actuators nonlinearity. In the literature there is a few number of authors that used directly the adaptive techniques that learn the buildings characteristics who are able to adapt to environmental particularities in which are located the buildings.
The computational intelligence in buildings
Applications of the intelligent methods in the buildings control systems appeared in a larger scale in the second half of the 90’s. The artificial intelligence techniques are used both in conventional buildings control systems and also in bioclimatic buildings. For the subsystems control in intelligent buildings [29] has been developed optimized intelligent control systems by including a series of evolutional algorithms.
The synergy between neural networks techniques, fuzzy logic and evolutional algorithms underlying Computational Intelligence is more used in the buildings control systems.
To solve the problem caused by non-linear characteristics of thermal comfort and physiological indices, of the times of delay and uncertainty of system algorithms include some adaptive fuzzy control techniques [30, 31] for optimal comfort control [13] and of economic comfort [32 ]. For water heating systems have been developed and successfully implemented a series of controller which use Neural algorithm -Back Propagation [8]. Neural networks have been widely used in applications for energy saving in buildings in condition of maintaining or increasing comfort in Japan [33] where they were embedded in commercial products such as air conditioning, heating plants, washing machines, etc..
To receive benefit of the advantages offered by the control systems mentioned above in a way related to the level of a building is necessary to use a distributed monitoring and control system, able to take data and execute commands in some components of control energy systems building.
One of the issues outstanding in this area is represented by the fact that there are currently few solutions available on the market able to do one internal environmental control parameters taking into account all the above elements [34]. More specifically, most of the existing controllers are focused either on the analysis of the particularities of the building, either on the primary analysis of human behavior but only in terms of a single controlled element: either heating appliances or air conditioning or lighting installation without link these controllers so as to obtain an increased effect of global energy saving, referring to all parts of the building systems.
To have such an approach we need an information network capable to take data and send commands linked to the entire arsenal of consuming energy systems or natural resources in the building. A solution that I will use to solve this problem is offered by wireless sensory networks [35].
Development of microelectronics and miniaturization of mechanical structures led to the development of autonomous sensory nodes in terms of power, size increasingly smaller as the full registration process and communication functions [40, 41] these sensor nodes can form ad hoc network which in turn form the distributed sensor systems that are able to acquire data and process information from different situations. Such wireless sensor network has a tolerance to failure and a higher measurement accuracy than conventional monitoring systems, and normally these types of networks are less expensive both in the acquisition and implementation and in operation compared with alternatives solutions available that use only a few isolated sensors coupled to data transmission systems. An advantage of using these distributed networks of wireless sensors is that it can be located in difficult areas to continuously monitor the parameters of that area, and to process and transmit the data acquired a wide variety of applications.
Wireless sensory networks being ableto monitor the environment where they are located, to process information and make decisions based on previous comments have pointed out especially the last time, being a viable alternative for the developed applications in various fields based on classical networks [37-44]. As applications where are used wireless sensory networks we can mention military applications and civil applications such as environmental monitoring, monitoring of areas with high potential for environmental disaster, monitoring inventory or monitoring industrial processes in an enterprise to enhance operability and implementation of specific elements quality management.
Recent discoveries in the field of miniaturization, design techniques, and transposition of the projects in hardware systems, and development techniques and information mainly due to developments in programming has led to cheaper sensors and electronic modules and components which in turn generated an increase of developing sensory wireless networks [36-38,40,44].
As can be found the project have a highly inter and multidisciplinary character. The project is at the crossroads of four priority areas: Information Society Technologies, Energy, Environment and not at least with innovative character of the system who will be developed, the project can be classified and in Materials domain, processes and innovative products.
In conclusion, in light of the current state of knowledge in related areas in terms of the proposed project and by objectives that will must be performed and expected results, I will highlight a number of elements and challenges that will have to find a solution and an answer on the postdoctoral traineeship period. To identify the elements and challenges of the project I will enumerate them separately on each component module of the system in part.
The main challenges in implementing module of data acquisition, are that will be studied and performed communication protocols, between network nodes sensory of the building, who allowing data communication between network nodes, so that in case if a nod failure, it can be reported and nodes use like a routing point aren’t scrapped, but can continue the bidirectional transfer of dates from other adjacent nodes. Another element to be considered is the transmit power and data transfer protocol that, depending on the type of building, construction materials and the distance between nodes, to ensure the transfer of data between network nodes with high confidence and also to increase life of a node.
For component storage, processing and presentation of information, the main elements to be studied and solved are related on implementation of database, the configuration it, the query mode and not at least by securing and controlling access to these data. We have studied the structure of databases in terms of number, type, conditions and resources monitored so that data supplied to logic controllers lead to their behavior as appropriate to the intended purpose: energy efficiency, increased comfort.
The questions that I have to respond in achieving a more effective implementation of intelligent module for command and control are related to parameters monitored, the conditions that can be transmitted in order to reduce consumption system, which are normal values, which are the limits the system should be within, what represent the optimal thermal comfort and visual limits. Eventually, by implementing an intelligent system that uses as data drive, data storage component, the system can identify the user’s preferences, based on history and using these constraints to be able to redefine for user, the comfort parameters and the solution for minimum consumption of resources.
