The effect of spatial and temporal randomness of stochastically generated occupancy schedules on the energy performance of a multiresidential building

Carlucci, Salvatore; Lobaccaro, Gabriele; Li, Yong; Lucchino, Elena Catto; Ramaci, Roberta

doi:10.1016/j.enbuild.2016.05.023

Cited by 28 publications

(11 citation statements)

References 33 publications

(39 reference statements)

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“…The building is conceived as living lab, thus occupied by real users whose presence has influenced the operation of technical building systems and the activation of the control strategies [47], but it has indirectly provided information on users' perception of the environment. During the period of the analysis the house has been occupied by one, two or three persons; erratic occupation has been recorded during July 2017 and June 2018, whereas during the other months the building has been occupied more regularly.…”

Section: Occupation Conditionmentioning

confidence: 99%

Yearly operational performance of a nZEB in the Mediterranean climate

Causone

Tatti

Pietrobon

et al. 2019

Energy and Buildings

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Over the last decades, the reduction of the energy use in the building sector has become a topic of major investigation and policy development worldwide. Guidelines have been defined to drive governments and building construction stakeholders towards the retrofit of the existing building stock and to the construction of new highperformance buildings. However, availability of operational data is often limited, especially when it comes to high performance buildings in warm climates, although it is essential to define design approaches targeted to energy efficiency, to design smart energy grids and demand-response oriented energy programs. Buildings, such as living laboratories, may offer opportunities to implement and develop energy databases, to provide benchmarks and to study occupant behaviour under different operational conditions. The paper investigates the energy and thermal comfort performance of a residential building in the Mediterranean climate. The building, certified as Passivhaus and equipped with an advanced monitoring system, allows to test different control strategies, to study occupant behaviour and to provide real time operational data. In particular, the data analysis showed a positive energy balance on yearly basis, i.e. an energy use of 59.7 kWh/m 2 net/year vs. an on-site energy generation of 76.0 kWh/m 2 net/year. The energy breakdown highlighted, that energy uses related to user behaviour and comfort requests account for about 72 % of the total energy use, confirming that occupant behaviour is one of the major drivers of the operational energy use (and the related services) in high performance buildings.

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Section: Occupation Conditionmentioning

confidence: 99%

Yearly operational performance of a nZEB in the Mediterranean climate

Causone

Tatti

Pietrobon

et al. 2019

Energy and Buildings

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“…It was found that the highest heat consumption was up to twenty times higher than the lowest due to the occupant's behavior [114]. Users' habits play a key role related to energy use [115,116]. Other studies [34,111,117] pointed out that users can efficiently operate in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customers' preferences and comfort level.…”

Section: Challenges Benefits and Motivations Related To The Usersmentioning

confidence: 99%

A Review of Systems and Technologies for Smart Homes and Smart Grids

2016

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In the actual era of smart homes and smart grids, advanced technological systems that allow the automation of domestic tasks are developing rapidly. There are numerous technologies and applications that can be installed in smart homes today. They enable communication between home appliances and users, and enhance home appliances' automation, monitoring and remote control capabilities. This review article, by introducing the concept of the smart home and the advent of the smart grid, investigates technologies for smart homes. The technical descriptions of the systems are presented and point out advantages and disadvantages of each technology and product today available on the market. Barriers, challenges, benefits and future trends regarding the technologies and the role of users have also been discussed.

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“…All over the world, the building sector is one of the major users of energy and materials [1,2]; therefore, in the last decades, the interest in reducing its impact has greatly increased [3,4]. At the end of 2018, the European Union launched new directives [5][6][7][8] to increase the energy efficiency of existing and new buildings and to enhance the use of renewable energy.…”

Section: Introductionmentioning

confidence: 99%

“…Occupant Behaviour (OB) represents one of the biggest uncertainties in building energy modelling [9,10] and has a significant impact on energy usage in buildings [11][12][13][14][15][16][17][18], especially in the residential sector [2,19,20]. Commercial software tools, nevertheless, usually lack the capacity to describe individual actions of building users and assume generic user schedules, which are not able to directly reproduce the unpredictability of OB over time [4,12,21,22]. This is becoming a relevant problem, since, in new highperformance buildings, the share of energy demand affected by OB is constantly rising [2,23,24]; thus, the interest on OB models is gaining momentum [4].…”

Section: Introductionmentioning

confidence: 99%

A data-driven procedure to model occupancy and occupant-related electric load profiles in residential buildings for energy simulation

Causone

Carlucci

Ferrando

et al. 2019

Energy and Buildings

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Improving the reliability of energy simulation outputs is becoming a pressing task to reduce the performance gap between the design and the operation of buildings. Occupant behaviour modelling is one of the most relevant sources of uncertainty in building energy modelling and is typically modelled via a priori choices made by modellers. Thus, an improvement in the description of occupant behaviour is needed. To this regard, the availability of smart meter recordings might help to generate more reliable input data for building energy models. This paper discusses a novel data-driven procedure that enables to create yearly occupancy and occupantrelated electric load profiles to inform building energy modelling, using a typical uneven database made available by energy operators. The procedure is subdivided into three main tasks. The first has the intent to detect representative occupant-related electric load profiles from smart meters readings. The second task aims to generate yearly occupancy profiles from the same database. The last task assesses the impact of the generated occupancy and occupant-related electric load profiles on building energy simulation outputs. The procedure is applied to the case study of a multi-residential building in Milan, Italy and is meant to show the possibility to overcome deterministic inputs that might have little relation with the actual building operation. It showed a substantial improvement in the reliability of building energy simulation and that occupant related load profiles may account for about 8 % of the building's energy need for space heating.

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The effect of spatial and temporal randomness of stochastically generated occupancy schedules on the energy performance of a multiresidential building

Cited by 28 publications

References 33 publications

Yearly operational performance of a nZEB in the Mediterranean climate

Yearly operational performance of a nZEB in the Mediterranean climate

A Review of Systems and Technologies for Smart Homes and Smart Grids

A data-driven procedure to model occupancy and occupant-related electric load profiles in residential buildings for energy simulation

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