Agent-based Modeling of Electricity Consumption in an Office Building under a Tiered Pricing Mechanism

Lin, Haiyang; Wang, Qinxing; Yu, Wenbin; Wennerstern, Ronald; Sun, Qiang

doi:10.1016/j.egypro.2016.12.056

Cited by 15 publications

(4 citation statements)

References 14 publications

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“…De Hann et al [19] used an agent-based model to study consumers' decisions to buy energy-efficient cars. Lin et al [20] developed an agent-based model to simulate electricity consumption in an office building.…”

Section: Introductionmentioning

confidence: 99%

An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels

Mohamed

Wang

2017

Sustainability

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Abstract:To assess whether China's emissions will peak around 2030, we forecast energy consumption and carbon emissions in China. We use an agent-based model driven by enterprises' innovation. Results show some differences in both energy consumption peaks and carbon emission peaks when we compare trends at different levels. We find that carbon emissions and energy consumption will peak in 2027 and 2028, respectively. However, the primary, secondary, and tertiary industries will reach energy consumption in different years: 2023, 2029, and 2022, respectively, and reach carbon emission peaks in 2022, 2028, and 2022, respectively. At the sectoral level, we find a wider range of energy consumption peaks and carbon emission peaks. Peak energy consumption occurs between 2020 and 2034, and peak carbon emissions between 2020 and 2032. Commercial and catering businesses, utilities and resident services, and finance and insurance achieve peak energy consumption and carbon emissions earliest in 2020, while building materials and other non-metallic mineral products manufacturing and metal products manufacturing are the two latest sectors to reach peak energy consumption and emissions, in 2034 and 2032, respectively.

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Section: Introductionmentioning

confidence: 99%

An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels

Mohamed

Wang

2017

Sustainability

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“…For example, TCP implemented across China from 2012 helped households change alter inefficient patterns of electricity consumption [98,100]. Implementing TCP in public buildings could raising public awareness on energy saving, influence occupants energy usage pattern in terms of lighting, computer and other appliances, and reduce building energy use obviously [101].…”

Section: B) Habitual Behavior Related Building Energy Incentivesmentioning

confidence: 99%

A systematic review of occupant behavior in building energy policy

Yan

Azar

et al. 2020

Building and Environment

133

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Buildings play a dominant role in global efforts towards energy consumption reduction, greenhouse gas (GHG) emission mitigation, as well as global clean energy transition. Building Energy Policies (BEP) improved globally and quickly with a growing number of building codes implemented over the past decade. Occupant Behavior (OB) has significant impacts on building energy performance and occupant comfort, despite often being not well understood and oversimplified in BEPs. This paper highlighted the research needs of properly integrating OB in building energy polices by presenting a literature review to identify the key questions and challenges related to building technical standards and regulations, building information policies, building energy incentives, and policy evaluations and way forward. Challenges and opportunities of OB in BEP are also discussed with respect to technical innovation and digitalization, as well as concerns related to energy efficiency and fairness. There has been growing interests, research and applications in this field, but significant challenges and opportunities still lie ahead. Keywords: Occupant behavior; building energy policy; climate change policy; building energy efficiency;HVAC system 1. Introduction Occupant behavior in building energy policyBuildings play a dominant role in global efforts towards energy consumption reduction, greenhouse gas (GHG) emission mitigation, as well as global clean energy transition. Facing global climate change and national energy security challenges, international agreements, initiatives, and building sector energy policies are providing 2 promising alternatives to the status quo. In recent years, Building Energy Policies (BEP) improved globally and quickly with a growing number of building codes implemented over the past decade. In contrast, global final energy consumption in buildings increased by more than 5% between 2010 and 2017, as energy efficiency gains were outpaced by continued growth in the building sector size and resulting energy service demands [1]. Among various factors, Occupant Behavior (OB) plays an essential role in building energy demand increases and activity growth. In addition, OB has significant impacts on building energy performance and occupant comfort, despite often being not well understood and oversimplified in BEPs due to its stochastic, diverse, complex and interdisciplinary nature [2]. Definition, estimation and intervention of OB become essential research challenges during building energy policy making, implementation and evaluation processes. Real OB US OB China OB EU OB EU regulation China regulation OB in regulation US regulation Country X OB Country X regulation Gap 2 Gap 1 Gap 3

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“…38 Lin et al used multi-ABMS to study electric vehicle penetration rates and their charging patterns to investigate smart charging strategies. 39 Philipp et al reviewed the use of ABMS approach in context of the smart electricity grids and markets. 15…”

Section: Agent-based Modelsmentioning

confidence: 99%

A hierarchical multi-resolution agent-based modeling and simulation framework for household electricity demand profile

et al. 2020

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Analyzing demand behavior of end consumers is pivotal in long term energy planning. Various models exist for simulating household load profiles to cater different purposes. A macroscopic viewpoint necessitates modeling of a large-scale population at an aggregate level, whereas a microscopic perspective requires measuring loads at a granular level, pertinent to the individual devices of a household. Both aspects have lucrative benefits, instigating the need to combine them into a modeling framework which allows model scalability and flexibility, and to analyze domestic electricity consumption at different resolutions. In this applied research, we propose a multi-resolution agent-based modeling and simulation (ABMS) framework for estimating domestic electricity consumption. Our proposed framework simulates per minute electricity consumption by combining large neighborhoods, the behavior of household individuals, their interactions with the electrical appliances, their sociological habits and the effects of exogenous conditions such as weather and seasons. In comparison with the existing energy models, our framework uniquely provides a hierarchical, multi-scale, multi-resolution implementation using a multi-layer architecture. This allows the modelers flexibility in order to model large-scale neighborhoods at one end, without any loss of expressiveness in modeling microscopic details of individuals’ activities at house level, and energy consumption at the appliance level, at the other end. The validity of our framework is demonstrated using a case study of 264 houses. A validated ABMS framework will support: (a) Effective energy planning; (b) Estimation of the future energy demand; (c) and the analysis of the complex dynamic behavior of the consumers.

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Agent-based Modeling of Electricity Consumption in an Office Building under a Tiered Pricing Mechanism

Cited by 15 publications

References 14 publications

An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels

An Agent-Based Model to Project China’s Energy Consumption and Carbon Emission Peaks at Multiple Levels

A systematic review of occupant behavior in building energy policy

A hierarchical multi-resolution agent-based modeling and simulation framework for household electricity demand profile

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