Due to their high energy intensity, buildings play a major role in the current worldwide transition. Building models are ubiquitous since they needed at each stage of life buildings, i.e. for design, retrofitting, and control operations. Classical white-box models, based on physical equations, bound follow laws physics but specific design underlying structure might hinder expressiveness hence accuracy. On other hand, black-box better suited capture nonlinear building dynamics thus can often...

Because physics-based building models are difficult to obtain as each is individual, there an increasing interest in generating suitable for MPC directly from measurement data. Machine learning methods have been widely applied this problem and validated mostly simulation; are, however, few studies on a direct comparison of different or validation real buildings be found the literature. Methods that indeed application often lead computationally complex non-convex optimization problems. Here...

The planning of future energy policies and systems requires an understanding the intricate relationships between climate change, technology uptake, population growth building demand. Building cooling demand is expected to increase considerably in many parts world as warms on average. In temperate climates, this be particularly large due number days when required maintain a comfortable indoor temperature. We quantify impact device uptake based population-weighted models, scenarios measured...

In recent years, renewable energy resources have been increasingly embedded in the distribution grids, raising new issues such as reverse power flows, and challenging traditional system operation. order to mitigate these issues, it has proposed operate more flexibly. For instance, residential buildings are ideal candidates offer flexibility locally defer avoidable expensive expansions. Due advances smart meter technologies trends towards digitalization, becomes common that electrical...

The optimal design of borehole thermal energy storage systems can ensure their techno-economical goals are met. Current optimization methods either employ detailed modelling unsuitable for numerical or use simplified models that do not consider operational conditions. This paper proposes an optimization-oriented model and a non-convex formulation that, differently from other studies in the literature, influence seasonal size temperature on its capacity, losses, heat transfer rate, efficiency...

Active building energy management can facilitate the development of low-carbon buildings and support flexible operations future smart cities, thanks to advancements in digitalization To fully leverage these benefits, it is essential integrate diverse objectives engage multiple stakeholders. However, a gap remains comprehensive field insights into emission reduction, flexibility provision, user impacts. This study examined how real occupied building, with all its assets, could function as an...

To enable the widespread integration of volatile renewable energy for decarbonization, electricity systems will need to become significantly more flexible absorb power fluctuations. Therefore, current fossil-fueled generation have be complemented and partially replaced by decentralized flexibility. address flexibility challenges, multi-energy system (MES) is a promising concept. In this paper, MES design operation optimization model developed considering provision. technologies are harnessed...

With more and data being collected, data-driven modeling methods have been gaining in popularity recent years. While physically sound, classical gray-box models are often cumbersome to identify scale, their accuracy might be hindered by limited expressiveness. On the other hand, black-box methods, typically relying on Neural Networks (NNs) nowadays, achieve impressive performance, even at deriving statistical patterns from data. However, they remain completely oblivious underlying physical...

We study the problem of tuning parameters a room temperature controller to minimize its energy consumption, subject constraint that daily cumulative thermal discomfort occupants is below given threshold. formulate it as an online constrained black-box optimization where, on each day, we observe some relevant environmental context and adaptively select parameters. In this paper, propose use data-driven Primal-Dual Contextual Bayesian Optimization (PDCBO) approach solve problem. simulation...

This work presents a fully data-driven, black-box pipeline to obtain an optimal control policy for multi-loop building problem based on historical and weather data, thus without the need complex physics-based modelling. We demonstrate method joint of room temperature bidirectional EV charging maximize occupant thermal comfort energy savings while leaving enough in battery next trip. modelled with recurrent neural network piece-wise linear function. Using these models as simulation...

With the increased amount of volatile renewable energy sources connected to electricity grid, and phase-out fossil fuel based power plants, there is an need for frequency regulation. On demand side, regulation services can be offered by buildings or districts that are equipped with electric heating cooling systems, exploiting their thermal inertia. Existing approaches tapping into this potential typically rely on dynamic building models, which in practice challenging obtain maintain. As a...

Due to their thermal inertia, buildings equipped with electric heating and cooling systems can help stabilize the electricity grid by shifting load in time, thus facilitate energy flexible urban right control system place. Because of minimum capacity requirements, they often only participate demand response schemes, such as secondary frequency reserves through aggregation. Such an aggregation could also take form entire district connected that are supplied large-scale heat pumps chillers....

Ice storage systems can be used as an efficient cooling source during summer, well a heat for pumps winter. The non-linear behaviour of the exchange process in makes formulations optimising design and operation these technologies complex. In this work, we propose quadratically-constrained mixed-integer programming formulation, that capture latent sensible its impact on delivery heating cooling. A building demonstrator integrating ice device was case study. Monitoring data were to validate...

Demand side management is perceived as a tool to support secure and reliable energy system operation amid growing integration of renewable resources. However, the lack scalable modeling control procedures hinders practical implementation. To address this challenge, paper proposes novel signal matrix model predictive algorithm. Compared existing data-driven methods, approach explicitly provides stochastic predictions considering both disturbance measurement errors with few tuning parameters,...

Despite the immense success of neural networks in modeling system dynamics from data, they often remain physics-agnostic black boxes. In particular case physical systems, might consequently make physically inconsistent predictions, which makes them unreliable practice. this paper, we leverage framework Irreversible port-Hamiltonian Systems (IPHS), can describe most multi-physics and rely on Neural Ordinary Differential Equations (NODEs) to learn their parameters data. Since IPHS models are...

The increasing penetration of renewable energy resources has transformed the system from a traditional hierarchical delivery paradigm to distributed structure. Local hubs activates synergies among carriers rendering flexibility and gives rise possible trading networked local hubs. Joint operation such peer-to-peer between them can improve efficiency support integration resources. However, for complex systems involving multiple stakeholders, both computational tractability privacy concerns...

La calidad en la innovación dentro del sector de construcción debe ser rápidamente adaptada para cumplir con los inmediatos desafíos relacionados mejora las edificaciones actuales. NEST es una plataforma investigación y transferencia tecnológica flexible abierta a universidades e industrias donde nuevas soluciones pueden implementadas validadas un entorno real. consiste estructura fija serie módulos individuales que son utilizados como oficinas o apartamentos poder vivir trabajar. Además,...

In this paper, we consider the problem of controller tuning for an operating unit in a building energy system. As illustrative plant example focus on heat pump. Since is use, method supposed to not intervene with its operation. Moreover, procedure be online, model-free, based only historical data and needs provide safety guarantees regard, formulate as black-box optimization adopt safe Bayesian approaches parameter tuning. These are relatively new control community intensively studied...

Model Predictive Control in buildings can significantly reduce their energy consumption. The cost and effort necessary for creating maintaining first principle models make data-driven modelling an attractive alternative this domain. In MPC the form basis optimization problem whose solution provides control signals to be applied system. fact that has solved repeatedly real-time implies restrictions on learning architectures used. Here, we adapt Input Convex Neural Networks are generally only...

Energy systems are undergoing a profound transition worldwide, substituting nuclear and thermal power with intermittent renewable energy sources (RES), creating discrepancies between the production consumption of electricity increasing their dependence on greenhouse gas (GHG) intensive imports from neighboring systems. In this study, we analyze concurrent electrification mobility sector investigate impact electric vehicles (EVs) large share sources. particular, build an optimization...

This paper details the use of piece-wise linear regression and non-linear optimisation to determine heat transfer properties two ice thermal stores different volumes (85 m3 11 m3). The available energy each storage was determined by fraction stored in vessel. loss coefficient using an algorithm. Using this approach it possible coefficients occurring at layers storage. Validation yielded a relative mean error 5.4% 3.8% for 85 respectively. is dependent on measurement temperature segments...

This paper presents a pipeline for creating digital twins of building energy systems, which is shared as an open test-environment controller benchmarking.The twin calibrated based on extensive dataset including wide variety data with fine temporal resolutions.The comprehensive list controllable variables, the resolution measurements, and real-time capabilities distinguish this work from existing test environments.A case study also provided to exemplify use environment benchmarking...