Building Clusters Research Articles

Developing a CCHP- microgrid operation decision model under uncertainty

Abstract In this study, we present a collaborative decision model to study the energy exchange among building clusters where the buildings share a combined cooling, heating and power system, thermal storage, and battery, and each building aims to minimize its energy consumption cost under electricity demand uncertainty. The problem is formulated as a two-stage stochastic programming model and then solved using a hybrid decomposition algorithm that combines Sample Average Approximation algorithm with an enhanced Benders decomposition algorithm. Numerical experiments reveal that the hybrid decomposition algorithm provides high quality feasible solution in solving the realistic large-scale building cluster problem in a reasonable amount of time. Experimental results allow the investors to decide the optimal sizing of thermal and battery storage and PGU capacities under power demand uncertainty. Further, the model can assist decision makers to choose the appropriate pricing mechanism (i.e., an optimal pricing plan) under different electricity demand variability level. Finally, we observe that the CCHP-microgrid system is more sensitive to an increase in heating demand than the cooling demand.

De-aggregation of community resilience goals to obtain minimum performance objectives for buildings under tornado hazards

The paradigm of performance-based engineering (PBE) provides a framework for engineers and planners to achieve desired levels of performance and functionality of building clusters and civil infrastructure systems that are essential for community resilience and well-being. While it is recognized that resilience of a community must be supported by individual buildings and engineered facilities, the relation between community resilience goals and minimum performance criteria of individual structures enabling such goals through engineering practices does not yet exist. In this study, we first propose a path forward to establish this relation in a quantitative manner. We then illustrate the feasibility of the proposed framework by de-aggregating the resilience goals of a community residential building cluster through an inverse multi-objective optimization formulation to obtain the minimum performance objectives for residential buildings, for tornado hazards. Once the minimum building performance criteria are determined, they can be utilized as the target building performance for new constructions, pre-event strengthening or post-event reconstruction. The overarching aim of this framework is to relate engineering design and retrofit practices to socioeconomic expectations of a community as a whole, and to provide a vehicle for risk-informed resilience-based decision-making under natural hazard events.

Enclosure and recommoning in Wanchai, Hong Kong: The struggle of local community development in Asia’s World City

Wanchai, situated east of the Central Business District of Hong Kong, Asia’s World City, is a highly accessible and mixed community with old and new buildings constructed over the years through successive waves of reclamation. The less well-off population in the District was hard hit by the Asian Financial crisis in the late 1990s, followed by another wave of redevelopment as the economy recovered. This paper examines how the local stakeholders have worked together to resist wholesale redevelopment (‘enclosure’) as well as the interrelated practices of ‘recommoning’. With the help of a local charity, St James Settlement (set up in 1949 modelled after the Settlement Movement in UK), local residents have succeeded in saving a heritage building cluster, the Blue House, and are using it as a hub to further develop their community and rebuild the socio-economic network within a rapidly gentrifying area.

Unlocking flexibility by exploiting the thermal capacity of concrete core activation

Due to its inherent large thermal inertia, concrete core activation (CCA) could assist in active demand response schemes. By shifting the injection or extraction of thermal power in time, demand peaks that normally occur more or less simultaneously in clusters of buildings can be spread out in time. Furthermore, thanks to the low temperature differences allowed with respect to the room temperature, CCA is ideally combined with technologies that have increasing renewable potential, such as heat pumps, low temperature district heating and high temperature district cooling. This paper illustrates the flexibility potential of concrete core activation through the exploitation of its thermal energy storage capacity by dynamic simulations. A validated RC thermal model of a CCA is coupled with a detailed building model, including user occupancy and weather disturbances. The flexibility indicator is calculated based on a method presented in the literature, but using an extended version that allows application to more complex systems, including heat losses. Balancing the building between minimal and maximal temperature, the thermal power needed to heat or cool the building can be modulated up- or downward with respect to the reference energy use. The method is applied to various building types with different insulation levels, in order to map the flexibility potential of CCA heating compared to buildings heated with radiators.

Vibration control of a cluster of buildings through the Vibrating Barrier

Abstract A novel device, called Vibrating Barrier (ViBa), that aims to reduce the vibrations of adjacent structures subjected to ground motion waves has been recently proposed. The ViBa is a structure buried in the soil and detached from surrounding buildings that is able to absorb a significant portion of the dynamic energy arising from the ground motion. The working principle exploits the dynamic interaction among vibrating structures due to the propagation of waves through the soil, namely the structure–soil–structure interaction. In this paper the efficiency of the ViBa is investigated to control the vibrations of a cluster of buildings. To this aim, a discrete model of structures-site interaction involving multiple buildings and the ViBa is developed where the effects of the soil on the structures, i.e. the soil-structure interaction (SSI), the structure-soil-structure interaction (SSSI) as well as the ViBa-soil-structures interaction are taken into account by means of linear elastic springs. Closed-form solutions are derived to design the ViBa in the case of harmonic excitation from the analysis of the discrete model. Advanced finite element numerical simulations are performed in order to assess the efficiency of the ViBa for protecting more than a single building. Parametric studies are also conducted to identify beneficial/adverse effects in the use of the proposed vibration control strategy to protect cluster of buildings. Finally, experimental shake table tests are performed to a prototype of a cluster of two buildings protected by the ViBa device for validating the proposed numerical models.

The Problem of Airflow Around Building Clusters in Different Configurations

Abstract In the paper, the authors discuss the construction of a model of an exemplary urban layout. Numerical simulation has been performed by means of a commercial software Fluent using two different turbulence models: the popular k-ε realizable one, and the Reynolds Stress Model (RSM), which is still being developed. The former is a 2-equations model, while the latter – is a RSM model – that consists of 7 equations. The studies have shown that, in this specific case, a more complex model of turbulence is not necessary. The results obtained with this model are not more accurate than the ones obtained using the RKE model. The model, scale 1:400, was tested in a wind tunnel. The pressure measurement near buildings, oil visualization and scour technique were undertaken and described accordingly. Measurements gave the quantitative and qualitative information describing the nature of the flow. Finally, the data were compared with the results of the experiments performed. The pressure coefficients resulting from the experiment were compared with the coefficients obtained from the numerical simulation. At the same time velocity maps and streamlines obtained from the calculations were combined with the results of the oil visualisation and scour technique.

Exploring RapidIO Technology Within a DAQ System Event Building Network

RapidIO ( http://rapidio.org/ ) technology is a packet-switched high-performance fabric, which has been under active development since 1997. The technology is used in all 4G/LTE base stations worldwide. RapidIO is also used in embedded systems that require high reliability, low latency, and deterministic operations in a heterogeneous environment. RapidIO has several offloading features in hardware, therefore relieving the CPUs from time- and power-consuming work. Most importantly, it allows for remote direct memory access and thus zero-copy data transfer. In addition, it lends itself readily to integration with field-programmable gate arrays. In this paper, we investigate RapidIO as a technology for high-speed data acquisition (DAQ) networks, in particular the DAQ system of an LHC experiment. We present measurements using a generic multiprotocol event-building emulation tool that was developed for the LHCb experiment. Event building using a local area network, such as the one foreseen for the future LHCb DAQ, puts heavy requirements on the underlying network as all data sources from the collider will want to send to the same destinations at the same time. This may lead to an instantaneous overcommitment of the output buffers of the switches. We will present results from implementing an event building cluster based on RapidIO interconnect, focusing on the bandwidth capabilities of the technology as well as its scalability.

Numerical Study on the Urban Ventilation in Regulating Microclimate and Pollutant Dispersion in Urban Street Canyon: A Case Study of Nanjing New Region, China

Urban ventilation plays an important role in regulating city climate and air quality. A numerical study was conducted to explore the ventilation effectiveness on the microclimate and pollutant removal in the urban street canyon based on the rebuilt Southern New Town region in Nanjing, China. The RNG k − ε turbulence model in the computational fluid dynamics (CFD) was employed to study the street canyon under parallel and perpendicular wind directions, respectively. Velocity inside of the street canyon and temperature on the building envelopes were obtained. A novel pressure coefficient was defined, and three methods were applied to evaluate the urban ventilation effectiveness. Results revealed that there was little comfort difference for the human body under two ventilation patterns in the street canyon. Air stagnation occurred easily in dense building clusters, especially under the perpendicular wind direction. In addition, large pressure coefficients ( C P > 1 ) appeared at the windward region, contributing to promising ventilation. The air age was introduced to evaluate the “freshness” of the air in the street canyon and illustrated the ventilation effectiveness on the pollutant removal. It was found that the young air distributed where the corresponding ventilation was favorable and the wind speed was large. The results from this study can be useful in further city renovation for the street canyon construction and municipal planning.

Design optimization and sensitivity analysis of a biomass-fired combined cooling, heating and power system with thermal energy storage systems

In this work, an operation strategy for a biomass-fired combined cooling, heating and power system, composed of a cogeneration unit, an absorption chiller, and a thermal energy storage system, is formulated in order to satisfy time-varying energy demands of an Italian cluster of residential multi-apartment buildings. This operation strategy is adopted for performing the economical optimization of the design of two of the devices composing the combined cooling, heating and power system, namely the absorption chiller and the storage system. A sensitivity analysis is carried out in order to evaluate the impact of the incentive for the electricity generation on the optimized results, and also to evaluate, separately, the effects of the variation of the absorption chiller size, and the effects of the variation of the thermal energy storage system size on the system performance. In addition, the inclusion into the system of a cold thermal energy storage system is analyzed, as well, assuming different possible values for the cold storage system cost. The results of the sensitivity analysis indicate that the most influencing factors from the economical point of view are represented by the incentive for the electricity generation and the absorption chiller power. Results also show that the combined use of a thermal energy storage and of a cold thermal energy storage during the hot season could represent a viable solution from the economical point of view.

Earthquake responses of near-fault building clusters in mountain city considering viscoelasticity of earth medium and process of fault rupture

A new algorithm is proposed to implement viscoelastic wave propagation in earth medium with surface topography by introducing history variables into integral type GZB constitutive equations and by using the recursive formulae of these history variables. Combining the proposed algorithm with the flexural wave algorithm for frame structure and the algorithm for bidirectional wave propagation, a new type of integrated method is developed for earthquake response analyses of near-fault building clusters in mountain city due to rupture of causative fault. The earthquake responses of building clusters of frame structures situated at different sites of a mountain in Chongqing city, China, are studied during a hypothetical Mw 6.2 near-fault earthquake. The numerical results show that, for the multi-story buildings, the maximum peak value of beam-end bending moments appears in the building on the hill top and the earthquake risk positions are mainly at the bottom and/or the top of the buildings. For the high-rise buildings, the maximum peak value of beam-end bending moments appears in the building on the mountainside and the earthquake risk positions are mainly at the bottom and/or the middle of the buildings.

A District Approach to Building Renovation for the Integral Energy Redevelopment of Existing Residential Areas

Building energy renovation quotas are not currently being met due to unfavorable conditions such as complex building regulations, limited investment incentives, historical preservation priorities, and technical limitations. The traditional strategy has been to incrementally lower the energy consumption of the building stock, instead of raising the efficiency of the energy supply through a broader use of renewable sources. This strategy requires an integral redefinition of the approach to energy building renovations. The joint project SWIVT elaborates on a district redevelopment strategy that combines a reduction in the energy demand of existing buildings and their physical interconnection within a local micro-grid and heating network. The district is equipped with energy generation and distribution technologies as well as hybrid thermal and electrical energy storage systems, steered by an optimizing energy management controller. This strategy is explored through three scenarios designed for an existing residential area in Darmstadt, Germany, and benchmarked against measured data. Presented findings show that a total primary energy balance at least 30% lower than that of a standard building renovation can be achieved by a cluster of buildings with different thermal qualities and connected energy generation, conversion, and storage systems, with only minimal physical intervention to existing buildings.

Analysis of a Biomass-fired CCHP System Considering Different Design Configurations

Abstract This work aims to present the results of an energetic and economic analysis of a biomass fueled CCHP system operating according to different design configurations. The investigated system consists of a biomass-fueled cogeneration unit, an absorption chiller, a thermal energy storage system and a cold one, providing electricity, heat and cooling to an Italian cluster of buildings. For each simulated configuration, the feasible investment cost of the CHP unit is evaluated considering the economic savings obtained with respect to separate generation of electricity, heat and cooling. The best configuration from the economic point of view is indicated, and the incidence of the variation of the absorption chiller and storage systems sizes on the feasible investment cost of the CHP unit is evaluated and discussed as well. Results indicate that the most influencing parameter is represented by the absorption chiller power.

Strategies for the seismic upgrading of pairs of buildings in a historic precinct

This paper reports on a theoretical student design project to seismically upgrade buildings in a historic precinct of Wellington. The unique feature of the structural upgrading, heritage retention and adaptation, and new building interventions in the precinct was that all retrofitting designs were applied to pairs or clusters of buildings in order to develop new strategies for their seismic retrofit.
 The tying of buildings together as part of retrofitting is rarely encountered in earthquake engineering practice but this can be an important retrofitting approach as shown by the following design outcomes and case-study example. The main finding from the architectural design and seismic retrofit of 70 clusters of two to three buildings was the diversity of the retrofitting strategies that were applied. Two primary categories of retrofitting were identified; tying existing buildings together, and tying existing buildings to new buildings, with each category incorporating several variants. This paper highlights the advantages of retrofitting clusters of buildings to prevent seismic pounding, and for other economic and architectural reasons.

Forecasting power consumption for higher educational institutions based on machine learning

Electric power consumption is affected by diverse factors. In particular, a university campus, which is one of the highest power consuming institutions, shows a wide variation of electric load depending on time and environment. For stable operation of such institution, reliable electric power supply should be guaranteed. One of possible methods to do that is to forecast the electric load accurately and supply power accordingly. Even though various influencing factors of power consumption have been discovered for educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative forecasting of their electric load. In this paper, we build a power consumption forecasting model using various machine learning algorithms. To evaluate their effectiveness, we consider four building clusters in a university and collect their power consumption data of 15-min interval over more than one year. For the data, we first extract features based on the periodic characteristic and then perform the principal component analysis and factor analysis for the features. We build two electric load forecasting models using artificial neural network and support vector regression. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to actual electric load. The experimental results show that the two forecasting models can achieve average error rate of 3.46–10 % for all clusters.

A high-speed DAQ framework for future high-level trigger and event building clusters

Modern data acquisition and trigger systems require a throughput of several GB/s and latencies of the order of microseconds. To satisfy such requirements, a heterogeneous readout system based on FPGA readout cards and GPU-based computing nodes coupled by InfiniBand has been developed. The incoming data from the back-end electronics is delivered directly into the internal memory of GPUs through a dedicated peer-to-peer PCIe communication. High performance DMA engines have been developed for direct communication between FPGAs and GPUs using “DirectGMA (AMD)” and “GPUDirect (NVIDIA)” technologies. The proposed infrastructure is a candidate for future generations of event building clusters, high-level trigger filter farms and low-level trigger system. In this paper the heterogeneous FPGA-GPU architecture will be presented and its performance be discussed.

Multiscale interaction between a cluster of buildings and the ABL developing over a real terrain

A nested Large Eddy Simulation (LES) is used to compute the multiscale interaction between the Atmospheric Boundary Layer (ABL) and an existing cluster of buildings over the real topography. A Neutral ABL (NBL) and a Convective ABL (CBL) are simulated. As the ABLs develop over a no-flat terrain with heterogeneous roughness elements, standard ABL-LES with cyclic boundary condition cannot be used. Instead, a synthetic inflow generator is used to generate realistic turbulent NBL and CBL over the real terrain. The outer domain of the nested-LES is dedicated to solve the ABL flow, with the building parametrized with a rough wall model, whereas the inner domain computes the flow through the cluster of buildings. Both LES are connected with a one-way downscale nesting procedure. The effects of the NBL and the CBL are clearly visible at building scale. The horizontal turbulent flux and the vertical turbulent flux are enhanced in the CBL compared to the NBL. The temperature difference between the air within the cluster of buildings and the rural surrounding is similar for both ABL condition, even if the turbulent mixing is higher in the CLB case. We further show that the critical part of the nested simulation is the ability of the ABL-LES to properly compute the roughness layer near the ground. Current rough wall models used to parametrize urban area are not able to reproduce such layer, which can negatively impact the flow inside the building-resolved LES.

The Cluster of City Buildings Based on the SOM Neural Network

The clustering of buildings on the city map is an important field of cartographic and the main step to resolve issues related to the scale of the city map transformation process. The development of computer technology promotes the studies of cartographic and modelling algorithms. In order to achieve automatic clustering of map elements, the domestic and foreign scholars have proposed numerous automatic clustering algorithms. Although each algorithm works for specific problems, all algorithms are based on the graphical analysis transformation of building polygons on the map. By reading and analyzing current development of domestic and foreign researches, we find out that map building clustering needs more inspiring interactive features and automatic integrated decision-making simulation functions. It needs to improve the visualization software and integrated automatic intelligence, increase the proportion of the batch to support implementation of automated cartographic generalization to a higher level.

Prediction Model on Room Temperature Side Effect due to FastADR Aggregation for a Cluster of Building Air‐Conditioning Facilities

SUMMARYIn this paper, we have constructed an auto regressive and neural network combined type prediction model for responsive change in the room temperature trend due to the fast automated demand response (FastADR) power limitation of office building air‐conditioning facilities. We defined the average of differences between room temperature and set point of each indoor unit for the entire building as a FastADR side effect index for the building. Prediction experiments using an actual office building showed that the root mean square prediction error of our model was 0.23 °C for 5 min after the FastADR. This prediction ability is considered sufficient to estimate the side effect of FastADR power limitation.

Spatial clustering for district heating integration in urban energy systems: Application to geothermal energy

Given the challenges related to climate change and dependency from fossil fuels, modification of the energy systems infrastructure to increase the share of renewable energy is a priority in urban energy planning. The high heating density in cities makes it more economically competitive to deploy district heating (DH), which is essential for large-scale integration of renewable energy sources. Combining georeferenced data with district heating design methods allows to improve the quality of the system design. However, increasing the spatial resolution can lead to intractable model sizes.This paper presents a methodology to spatially assess the integration of DH networks in urban energy systems. Given georeferenced data of buildings, resource availability and road networks, the methodology allows the identification of promising sites for DH deployment. First, an Integer Linear Programming (ILP) model divides the urban system into spatial clusters (of buildings). Graph theory and routing methods are then used to optimally design the DH configuration in each cluster considering the road network in the routing algorithm. A Mixed-Integer Linear Programming (MILP) model is formulated in order to economically evaluate the DH integration over the whole urban area.The proposed methodology is applied to an example case study, evaluating the use of geothermal energy (deep aquifer) for direct heat supply. The results of the optimization show the interest of deploying geothermal DH in some of the clusters. The profitability of DH integration is strongly affected by the spatial density of the heating demand.

ビルマルチ空調設備群FastADR閉ループ制御のための非対称定率増減伝達関数モデル

ビルマルチ空調設備群FastADR閉ループ制御のための非対称定率増減伝達関数モデル