Dynamic modeling and ICT integration for Demand Side Management (DSM) of systems for heating, cooling and related electrical loads

Nowadays the energy usage is increasing the urban areas due to lifestyle changes and an increase in the population of cities. Consumers care more about their comfort level which affects energy usage. Improvement of energy efficiency of cooling and heating systems of buildings is a suitable approach for energy consumption reduction of urban areas. In existing buildings, it is difficult to intervene on the building envelope. Therefore, an alternative solution is using a smart controller for heating and cooling systems of buildings to make the total system more efficient. In the current work, first, a general energy model is designed and developed to be implementable to different kinds of buildings. The model contains different elements including boiler, chiller, fan coil, radiator, pipe, heat exchanger, air heat exchanger, zone, mixer, solver, and bridge. Then, the model is implemented on the case study building based on the heating and cooling plants of that. The model is validated in terms of indoor temperature in heating and cooling systems and $CO_{2}$ concentration. Next, two different approaches are studied, one for an islanded building, and another for the connected buildings. For the islanded building, it is planned to just keep the thermal comfort and decrease the energy consumption. Therefore, in this case, the load shape in a neighborhood will not be considered. Different scenarios are designed to be compared in terms of energy consumption and thermal comfort, including the basic, the indoor temperature, the weather prediction, and the smart scenarios. The other approach, which is the modeling through a neighborhood, helps to decrease energy consumption and improve the power load shape in the neighborhood. Meanwhile, the thermal comfort will be kept in a suitable range. Different scenarios are designed to be compared in terms of energy consumption, power load shape, and thermal comfort, including the basic connected, the smart connected scenarios. As the results show, implementing smart solutions in both approaches, islanded and connected, can improve the energy consumptions of the existing buildings. For energy consumption of islanded approach in the heating system, the smart scenario is the most effective in terms of energy consumption, which can reduce the energy consumption compared to the basic scenario about 10.7%. In that of the cooling system, the smart scenario can save more energy compared to the other scenarios, which is 9.7%, compared to the basic scenario. In the connected approach, using a smart controller interacting through the blockchain decreases the PAR by 15% compared to that of basic, and it decreases total energy consumption by 11%. The smart scenario brings 7% more thermal comfort compared to the basic scenario.