Investigating the effect of summer night ventilation on the urban buildings’ thermal and energy performance using numerical approaches

The present study aims to evaluate by simulation means, the effect of different night ventilations rates on the thermal and energy performance of typical building units, located in dense urban areas in Thessaloniki, Greece, both under thermostatic control and free-floating conditions. The numerical assessment is conducted with the dynamic building energy performance simulation model EnergyPlus. A parametric analysis, involving 4 different air flow rates (i.e., 3 ACH, 5ACH, 10ACH, 15ACH) has been carried out for 8 typical building units, located in 4 different urban areas in the city of Thessaloniki, presenting different morphological characteristics. In all cases, single side ventilation has been considered rather than cross ventilation, to evaluate the less optimal, building configuration scenario. The obtained simulation results revealed the significant effect of night ventilation on improving the thermal and energy performance of all the examined building units. Still, the morphological characteristics of the case study areas in which the examined building units are located, also affected the obtained simulation results and the achieved cooling energy savings.

Temperature compensation design and experiment for a giant magnetostrictive actuator

Because the performance of giant magnetostrictive materials (GMMs) can vary at different temperatures, the positioning accuracy of a giant magnetostrictive actuator is affected by heat. In this work, a new simplified control strategy under compulsory water cooling is proposed to maintain a constant GMM temperature. Based on this strategy, a coupled turbulent flow field and temperature field finite element model is created for a GMM smart component. The model is simulated using COMSOL Multiphysics software version 5.3. Through simulations, the temperature field distribution of GMM smart components is analysed under different drive input currents and cooling water flow rates. Based on the obtained simulation results, a GMM intelligent component temperature control device is constructed. The experimental results are in good agreement with the simulation results; a thermostatic control effect is achieved in the thermostat of the giant magnetostrictive rod. Thus, the proposed temperature control strategy is proven effective via simulations and experiments.

Control of Heat Pumps with CO2 Emission Intensity Forecasts

An optimized heat pump control for building heating was developed for minimizing CO 2 emissions from related electrical power generation. The control is using weather and CO 2 emission forecasts as inputs to a Model Predictive Control (MPC)—a multivariate control algorithm using a dynamic process model, constraints and a cost function to be minimized. In a simulation study, the control was applied using weather and power grid conditions during a full-year period in 2017–2018 for the power bidding zone DK2 (East, Denmark). Two scenarios were studied; one with a family house and one with an office building. The buildings were dimensioned based on standards and building codes/regulations. The main results are measured as the CO 2 emission savings relative to a classical thermostatic control. Note that this only measures the gain achieved using the MPC control, that is, the energy flexibility, not the absolute savings. The results show that around 16% of savings could have been achieved during the period in well-insulated new buildings with floor heating. Further, a sensitivity analysis was carried out to evaluate the effect of various building properties, for example, level of insulation and thermal capacity. Danish building codes from 1977 and forward were used as benchmarks for insulation levels. It was shown that both insulation and thermal mass influence the achievable flexibility savings, especially for floor heating. Buildings that comply with building codes later than 1979 could provide flexibility emission savings of around 10%, while buildings that comply with earlier codes provided savings in the range of 0–5% depending on the heating system and thermal mass.

Modeling and Energy Cost Optimization of Air Conditioning Loads in Smart Grid Environments

Electricity for heating, ventilation, and air condition (HVAC) machines takes up a large percentage of energy consumption in the buildings and thus in turn, a large portion of the energy monetary cost. Optimization of air conditioners use throughout the day will reduce energy consumption and expenditure. This study introduces a second-order differential equation model to capture the indoor temperature dynamics of a building. An experimental test bed is developed to collect a set of indoor/outdoor temperature and sunlight data. Using a least-squares-based system identification process, the model parameters are identified and checked through simulation. Optimization of the room temperature is then determined by solving a mixed-integer quadratic programming problem in relation to the hourly-updated energy prices. Mixed-integer quadratic programming solution is compared to a two-point thermostatic control system. A hybrid solution compromising the quadratic programming algorithm and the conventional thermostatic control scheme is proposed as a tractable approach for the near-optimal energy management of the system.