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Traditional planning models and EMS models were always independently maintained and seldom in synchronism with each other. Using EMS software allows planners and operators to share a common model reducing the mismatch between the two and cutting model maintenance by half. Having a common user interface also allows for easier transition of information from planning to operations. Newer EMS systems based on blade servers occupy a fraction of the space previously required. For instance, a blade rack of 20 servers occupy much the same space as that previously occupied by a single MicroVAX server.

In a slightly different context, EMS can also refer to a system designed to achieve energy efficiency through process optimization by reporting on granular energy use by individual pieces of equipment.

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Newer, cloud-based energy management systems provide the ability to remotely control HVAC and other energy-consuming equipment; gather detailed, real-time data for each piece of equipment; and generate intelligent, specific, real-time guidance on finding and capturing the most compelling savings opportunities. Home energy management HEM enables domestic consumers to take part in demand side activities.

The term Energy Management System can also refer to a computer system which is designed specifically for the automated control and monitoring of those electromechanical facilities in a building which yield significant energy consumption such as heating, ventilation and lighting installations. The scope may span from a single building to a group of buildings such as university campuses, office buildings, retail stores networks or factories.

The linguistic terms associated to these thermal zones of the ground heat exchanger will be used to control the thermal flow of the building. Linguistic terms associated to temperature ranges for the different zones, and pipes characteristics. This effect is shown in the results obtained in the experiments in the nZEB prototype.

Nevertheless, the soil is used as a storage tank and do not consider this factor for multi-year operations. The building envelope acts as a passive thermal barrier. This can be a key element in order to maintain a desired temperature in a building, particularly in cold climates, where the isolation layers of the walls can reduce the heating requirements.

Besides, the right selection of the building envelope composition not only produces a better insulation but can also smooth the temperature peaks during the day-night cycle. In this work a dynamic thermal barrier with high thermal inertia is proposed. By using a controlled fluid flow in the inner zone of the exterior walls, the influence of the daily and seasonal outdoor temperature variations on the inner temperature of the building is reduced.

The wall is composed of three layers: two polystyrene insulation layers and, in the middle, a concrete layer. The parameters of the walls of the real nZEB building are listed in Table 2. The wall presents a notorious thickness, low thermal conductivity, and high density and specific heat. The combination of these properties provides an extremely high thermal inertia to the walls. PP tubes are embedded in the concrete layer, as shown in Figure 5 a.

Thus, a fluid can flow through them to increase the thermal capacity of the concrete layer, and therefore the insulation, by controlling its temperature. The thermal performance of the dynamic thermal barrier has been modelled and simulated with COMSOL Multiphysics, Figure 5 b, taking into account the energy transfer by conduction through the envelope.

That is why the concrete wall is virtually isothermal at the indoor and outdoor average temperature. The pipes act as a temperature shield between the two insulation layers. The temperature plateau of the dynamic thermal barrier for both warm and cold thermal energy flows represents the boundary condition.

Intelligent Building Energy Management System using National Instruments LabVIEW and tools Demo

However, the temperature variation along the dynamic thermal barrier is low compared with the variation experienced along the two external layers. Therefore the thermal barrier reduces the thermal gradient and smooths the temperature variations. Thus, less thermal energy is required to reach an indoor comfort temperature. The model represents the heat balance between building and environment through the envelope, including heat convection in both the inner and outer surfaces, and heat conduction through the envelope layers.

These processes can be also represented by an equivalent circuit, Figure 6 b.

High Priority Research Themes

In current case the fluids are the inner and external air:. The energy transfer through the envelope is calculated with the heat transfer law Equation 9 , and represents the energy variation through the thickness of the wall combining thermal resistance and thermal capacity:. As the envelope layers are connected in series, the equivalent resistance is obtained by adding up the individual resistance of each layer, and the opposite with the inverse equivalent capacity.

The simulation results show the influence of the external conditions on the indoor temperature of the building. In Figure 7 , the indoor and wall temperatures obtained by the model are represented and compared with the measured external temperature, showing the influence of seasonal and daily weather variations, using the values displayed in Table 2.

Energy management software for new buildings

The indoor temperature is clearly affected by external weather conditions, presenting the same behaviour than the outdoor temperature, except for the delay and cushioning effect produced by the thermal inertia of the envelope heat capacity. The temperature measured by the sensor located within the wall follows the same pattern but, in this case, it seems to be more independent of the day-night weather variations.

It is clearly shown that in the first five months of the year an extra thermal energy heating is needed to reach the comfort temperature red band. On the contrary, in the summer an extra thermal energy cooling is required for the building to keep the desired temperature blue band. Thermal inertia, seasonal and daily temperatures. Outdoor measured temperature, and both indoor and wall simulated temperatures.

Besides, a sensitivity analysis was carried out, varying some of the wall parameters Figure 8. The thermal mass is defined by three characteristics: specific heat, density, and thermal conductivity. The values of the indoor temperature while changing these parameters are shown in Figure 7.

In all these cases the model response is as expected. The thickness of the polystyrene layer does not strongly influence the indoor temperature, opposite to the polystyrene thermal mass behaviour.

Related REEEP Case Studies

In addition, it is easy to infer that if the thickness of both the concrete wall and the polystyrene increase, the temperature variations will be reduced, although a much better insulated building also increases the risk of overheating [ 31 ]. To summarize, once the hydraulic circuit Section 2. Finally, a hydraulic circuit is implemented in the nZEB building to connect all the thermal subsystems previously described. The water-glycol fluid transport circuit is formed by the PP pipes connected to the roof solar collector, to the underground heat exchanger, and the ones of the dynamic thermal walls.

Hot, warm, cool, or cold fluids flow through the PP tubes connecting the three different subsystems that act as sinks or sources of thermal energy, according to the demand and the availability. The scheme of the whole circuit is displayed in Figure 9. The fluid recirculation is controlled by an input-output electro-valve, according to the fluid temperature and the thermal energy demand.

When the thermal energy captured is demanded by the user, it is directly sent to the dynamic thermal barrier to change the indoor temperature. Otherwise, the fluid is transferred to the ground heat exchanger for storage and later use. A three level perception and decision-making architecture is designed for monitoring and controlling the thermal energy flow between the three thermal subsystems described in the previous section, according to the user comfort demand. The perception-control loops rely on the data acquired by the Internet of Things IoT nodes.

In the nZEB prototype, the IoT perceptual nodes are presence, temperature, and flow sensors, and the IoT action nodes are linked to electro valves and pumps. Different interfaces are used for the visualization, information transfer to data bases, and updating of the shared memory. The three level perception and decision-making architecture is depicted in Figure Three level perception and decision making architecture for thermal energy flow management.

The bottom level, level 1, corresponds to the physical sensor network that offers different communication channels, and is in charge of the raw data acquisition. In the level 2, a fuzzy rule based controller has been designed to manage the ground heat exchanger. Context information and virtual sensors are also integrated at this level.

At the top level, level 3, the decision making system based on perceptions manages the thermal energy flows between the three subsystems, especially focused on the thermal barrier. The description of each of the three levels is presented in the following subsections. At this level, a network of physical sensors has been developed and implemented for signal acquisition, to monitor the thermal energy flow in the near Zero Energy Building.

Three different IoT nodes are used, all of them with CAN-bus networking protocol communications: M1 gateway modules , M2 temperature sensors , and M3 actuator nodes. They are responsible of data measurement and collection [ 32 ]. Besides, level 1 includes a real time controller of the energy capture at the solar collector, the thermal heat storage in the underground system, and the dynamic thermal barrier control. The communications channels via Ethernet port connect user and data visualization nodes mobile interface.

A gateway CAN-bus port connects the perceptual and action nodes. Information transferring to databases, and shared memory update are also built-in functionalities at this low-level controller. Figure 11 shows the main elements of this bottom level. M2: IoT nodes dedicated to monitoring temperatures at different locations: indoor temperature Ti , subsurface probes Ts , walls TW , and windows Tw. M3: IoT actuator nodes, acting on the valves and monitoring the volumetric flow rate. The embedded web pages are stored in low resolution, to support commands and exchange information with end users.

A DB is used to store data for further processing. The distribution of the IoT nodes and processors in both, the lower and the upper floor of the nZEB building is shown in Figure IoT nodes distribution in the nZEB. On the lower floor, M2 type IoT nodes red square are located at different ground depths T1, T2, T3, and T4 to measure underground temperature Figure 12 a.

Another M2 sensor red circle measures indoor temperature Ti. On the upper floor, the M2 nodes measure indoor, walls and window temperatures Figure 12 b. The M3 node has built-in webserver capabilities, being an instance of a new generation sensor web enablement [ 33 , 34 ]. Presence sensors blue circles are located on both floors. Figure 13 shows some of the real sensors and actuators that have been installed in the nZEB building.

A low resolution light webserver screen, that corresponds to a M3 node of the solar collector is presented in Figure 14 , where real-time sensor values are shown. Besides, users have access to the last 48 hours statistical data, and to the IoT node configuration ID, location, sampling rate. Moreover, users can send commands from this node, such as directing the thermal flow from the solar collector to the dynamic thermal barrier. At this level of the architecture, two main elements are considered: a fuzzy logic controller and virtual sensors.

On the one hand, the thermal energy flow is qualitatively modelled by linguistic terms due to the imprecision inherent to the values of the variables involved in the system. Therefore, the control action that calculates the fluid flow to feed the dynamic thermal barrier is obtained by a fuzzy controller. Fuzzy logic exploits imprecision and uncertainty, and provides simple and low-computational cost solutions. On the other hand, virtual sensors have been designed and implemented to monitor the thermal barrier and to include context information and user preferences. The fuzzy logic based controller has been designed to determine the thermal energy zone of the ground heat exchanger that has to be selected in order to reach the desired temperature at the thermal barrier Figure Negative values mean that the direction of the flow may be in opposite direction in cold days.

The output variable is the desired output temperature at the thermal barrier, which is mapped to the corresponding ground heat exchanger zone GHX that has to send the heat flow. The fuzzy knowledge base is presented in Table 3. Usually, the fluid flows through the walls in periods of less than 6 min. Input and output temperatures at the manifolds are checked to confirm that the thermal energy is dispatched. Virtual sensor integrate multiple and heterogeneous information, such as expert and historical knowledge, user profiles, and data from physical sensors and actuators.

They can be defined as a tuple Equation 12 :. This virtual sensor structure allows to process raw data adding semantics information and also to build context information for later use.

The fuzzy controller selects the ground heat exchanger zone, accordingly to the indoor temperature and the thermal energy flow on the exterior walls. These modules are part of the main real time application running at the central processor. Besides, additional information such as wall properties or thermal fluid flow characteristics is structured as an XML file and introduced in the virtual sensor, so that the TBVS not only integrates raw data but also semantic information Figure 16 a.

The data flow is shown in Figure 16 b, where sensor raw data and wall properties are used to compute heat flow. Thermal Barrier Virtual Sensor. This information allows planning ahead the control of the thermal flow. Second, the presence sensor provides information on the user location. In this case, the focus is on the second floor where two sensors are strategically located to act on the dynamic thermal barrier. Third, weather conditions such as solar irradiation or outdoor air temperature.

The top layer of the three-level proposed architecture uses a parser to extract information from the virtual sensors and to make a decision on the activation of the dynamic thermal barrier. In this case, a decision tree with a few rules is applied to determine whether the thermal barrier must be activated and the zone of the heat exchanger to send the thermal flow.

City of Chicago :: Chicago Construction Codes

The decision tree Figure 18 root node has the output of the fuzzy controller as the root node, i. The node at the second level of the tree is the ground heat exchanger zone, in this case GHX. Whenever any presence sensor is activated, the temperature at each roof face north, south, east and west of the solar collector is checked to determine whether or not it can supply the thermal energy demanded. Otherwise the dynamic thermal barrier is not activated. Remark that the solar collector temperatures are sampled each 15 min.

Enforcement of Residential Building Energy Efficiency Codes in Tianjin

Usually in summer and during the daylight time, the south collector thermal energy flow is exclusively led to the hot zone of the ground heat exchanger. Safety Concern, Occupied Building. Building Permit and Inspection Records. Building Permit Application Status. Vacant Building Registration. Chicago Data Portal: Buildings. The Chicago Construction Codes establishe minimum standards for the construction, alteration, repair, maintenance, and demolition of buildings and other structures in order to protect public health, safety and welfare.

This section provides a guide to locating provisions on specific topics within the Chicago Building Code. Some buildings or projects may also be required to meet additional state or federal accessibility requirements. Existing businesses may also have obligations to provide accessible services under the City of Chicago Human Rights Ordinance Chapter Additional requirements may apply to regulated businesses, and these requirements are found in the applicable business license provisions in Title 4. For users more familiar with the International Building Code organization, the Department of Buildings has prepared a table which correlates provisions of the Municipal Code of Chicago to chapters within the Common Code Format topical groups.

These requirements are partially based on and incorporate provisions of model codes published by the American Society of Mechanical Engineers ASME and other standards development organizations. These documents are available for purchase from their respective publishers:. These provisions are incorporated by reference and not reprinted in the ordinance. For frequent users of the code, this compiled version of the Chicago Electrical Code is available for purchase from NFPA in various formats.