An assessment of the load modifying potential of model predictive controlled dynamic facades within the California context

California is making major strides towards meeting its greenhouse gas emission reduction goals with the transformation of its electrical grid to accommodate renewable generation, aggressive promotion of building energy efficiency, and increased emphasis on moving toward electrification of end uses (e.g., residential heating, etc.). As a result of this activity, the State is faced with significant challenges of systemwide resource adequacy, power quality and grid reliability that could be addressed in part with demand responsive (DR) load modifying strategies using controllable building technologies. Dynamic facades have the ability to potentially shift and shed loads at critical times of the day in combination with daylighting and HVAC controls. This study explores the technical potential of dynamic facades to support net load shape objectives. A model predictive controller (MPC) was designed based on reduced order thermal (Modelica) and window (Radiance) models. Using an automated workflow (involving JModelica.org and MPCPy), these models were converted and differentiated to formulate a non-linear optimization problem. A gradient-based, non-linear programming problem solver (IPOPT) was used to derive an optimal control strategy, then a post-optimization step was used to convert the solution to a discrete state for facade actuation. Continuous state modulation of the façade was also modeled. The performance of the MPC controller with and without activation of thermal mass was evaluated in a south-facing perimeter office zone with a three-zone electrochromic window for a clear sunny week during summer and winter periods in Oakland and Burbank, California. MPC strategies reduced total energy cost by 9–28% and critical coincident peak demand was reduced by up to 0.58 W/ft2-floor or 19–43% in the 4.6 m (15 ft) deep south zone on sunny summer days in Oakland compared to state-of-the-art heuristic control. Similar savings were achieved for the hotter, Burbank climate in Southern California. This outcome supports the argument that MPC control of dynamic facades can provide significant electricity cost reductions and net load management capabilities of benefit to both the building owner and evolving electrical grid

Building fault detection data to aid diagnostic algorithm creation and performance testing.

It is estimated that approximately 4-5% of national energy consumption can be saved through corrections to existing commercial building controls infrastructure and resulting improvements to efficiency. Correspondingly, automated fault detection and diagnostics (FDD) algorithms are designed to identify the presence of operational faults and their root causes. A diversity of techniques is used for FDD spanning physical models, black box, and rule-based approaches. A persistent challenge has been the lack of common datasets and test methods to benchmark their performance accuracy. This article presents a first of its kind public dataset with ground-truth data on the presence and absence of building faults. This dataset spans a range of seasons and operational conditions and encompasses multiple building system types. It contains information on fault severity, as well as data points reflective of the measurements in building control systems that FDD algorithms typically have access to. The data were created using simulation models as well as experimental test facilities, and will be expanded over time

The reservoir network: A new network topology for district heating and cooling

Thermal district networks are effective solutions to substitute fossil fuels with renewable energy sources for heating and cooling. Moreover, thermal networking of buildings allows energy efficiency to be further increased. The waste heat from cooling can be reused for heating in thermal district systems. Because of bidirectional energy flows between prosumers, thermal networks require new hydraulic concepts. In this work, we present a novel network topology for simultaneous heating and cooling: the reservoir network. The reservoir network is robust in operation due to hydraulic decoupling of transfer stations, integrates heat sources and heat sinks at various temperature levels and is flexible in terms of network expansion. We used Modelica simulations to compare the new single-pipe reservoir network to a basecase double-pipe network, taking yearly demand profiles of different building types for heating and cooling. The electric energy consumed by the heat pumps and circulations pumps differs between the reservoir and base case networks by less than 1%. However, if the reservoir network is operated with constant instead of variable mass flow rate, the total electrical consumption can increase by 48% compared to the base case. As with any other network topology, the design and control of such networks is crucial to achieving energy efficient operation. Investment costs for piping and trenching depend on the district layout and dimensioning of the network. If a ring layout is applied in a district, the reservoir network with its single-pipe configuration is more economical than other topologies. For a linear layout, the piping costs are slightly higher for the reservoir network than for the base case because of larger pipe diameters

Modelling of high temperature storage systems for latent heat

There is a huge demand for heat storages for evaporation applications. Thermal storage systems are used to increase the efficiency of thermal systems by an improved adaption of energy availability and energy demand. In this paper a possible solution for modular storage systems from 200-600 °C and pressures up to 100 bar is presented. The application of steam as a working medium requires the availability of isothermal storage if charging/discharging should take place at almost constant pressure. The saturation temperature range is between 200°C and 320°C. Therefore nitrate salts are used as phase change material (PCM). The solution developed at DLR is characterized by a modular concept of tube register storages surrounded by both sensible and latent heat storage material. The focus in this paper is on modelling of the PCM storage. A model is introduced for melting and freezing of the PCM. To perform with an acceptable heat transfer rate inside the PCM, fins are used to increase the overall thermal conductivity. Instead introducing mean storage material parameters, like thermal conductivity or specific heat capacity, the geometry of the finned tube is modelled by using discrete elements. Therefore the model allows detailed studies on heat transfer during space and time. The fin design can be varied in order to find an optimal configuration. A set of partial differential equations is created and solved. When considering a stand alone system, that means tube, fin and PCM, without a connection to other components, investigation is quite effective. In case of the PCM storage there is the big advantage, compared with a sensible regenerator, that the almost constant fluid temperature, when evaporating or condensing, leads to a uniform temperature distribution in fluid flow direction. Therefore only a very rough discretisation in axial direction is needed, what even allows bonding with other components e.g. from the Modelica Fluid Library. Sensible storages as they are used for preheating and superheating have a characteristic temperature gradient in axial direction. To describe their thermal behaviour concentrated models, using dimensionless numbers, are used

Energy efficient renovation of heritage residential buildings using modelica simulations

Historic homesteads can be found on a large scale in Europe and particularly in Flanders. In Flanders there are hundreds of homesteads in desperate need of renovation. Within the framework of the Europe 2020 objectives both CO2 emission and energy use need to be reduced with 20% by 2020. Unlike for the average residential building renovation, focus lies on synergy between respect to heritage and achieving an optimal energetic effectiveness. The object of this research is a case study homestead in Bruges, named the Schipjes. The first step in energy efficient renovation is to lower energy use by optimizing the building physics, therefore dynamic simulations in Modelica are performed to evaluate primary energy demand, especially for heating, and thermal comfort. The second step is the choice of the most energy efficient technical installations for a district heating system as will be used for Schipjes. Five different scenarios or combinations of heat production and distribution systems are developed as input options for future research simulations and energetic equations in Modelica

Application of large underground seasonal thermal energy storage in district heating system: A model-based energy performance assessment of a pilot system in Chifeng, China

Seasonal thermal energy storage (STES) technology is a proven solution to resolve the seasonal discrepancy between heating energy generation from renewables and building heating demands. This research focuses on the performance assessment of district heating (DH) systems powered by low-grade energy sources with large-scale, high temperature underground STES technology. A pilot DH system, located in Chifeng, China that integrates a 0.5 million m3 borehole thermal energy storage system, an on-site solar thermal plant and excess heat from a copper plant is presented. The research in this paper adopts a model-based approach using Modelica to analyze the energy performance of the STES for two district heating system configurations. Several performance indicators such as the extraction heat, the injection heat and the storage coefficient are selected to assess the STES system performance. Results show that a lower STES discharge temperature leads to a better energy performance. A sensitivity analysis of the site properties illustrates that the thermal conductivity of soil is the most influential parameter on the STES system performance. The long-term performance of the STES is also discussed and a shorter stabilization time between one and two years could be achieved by discharging the STES at a lower temperature.This research is part of the seasonal storage for solar and industrial waste heat utilization for urban district heating project funded by the Joint Scientific Thematic Research Programme (JSTP)–Smart Energy in Smart Cities. We gratefully acknowledge the financial support from the Netherlands Organisation for Scientific Research (NWO). We would also like to thank our research partners from Tsinghua University working on the project of the International S&T Cooperation Programof China (ISTCP) (project No. 2015DFG62410). Without their efforts, we would not have been able to obtain the technical data to conduct the case study