Predicting Rooftop Photovoltaic Adoption In The Residential Consumers of PLN Using Agent-Based Modeling

Haryadi, Fajar Nurrohman; Imron, Muhammad Ali; Indrawan, Harry; Triani, Meiri

doi:10.1109/ieeeconf48524.2019.9102558

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…For example, Barakat and Khoury (2016) used ABM to study occupant multi-comfort level to reduce energy consumption within academic buildings. Haryadi et al (2019) predicted future rooftop photovoltaic adoption through ABM to understand the impact of the decisionmaking behavior on electricity utilization. Feng et al (2019) proposed an ABM approach to model and evaluate the reliability and performance of a complex human-machine system through a case study of an aircraft carrier.…”

Section: Methodsmentioning

confidence: 99%

Pull planning versus push planning: Investigating impacts on crew performance from a location-based perspective

Ghanem

Hamzeh

Seppänen

et al. 2022

Front. Built Environ.

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Push planning and pull planning are different approaches used for production planning and control. Push planning uses predetermined dates to control a project, whereas pull planning utilizes the system’s current state. Although researchers have compared these approaches from production planning perspective to improve project performance, the differences between push and pull in construction and their impacts on crew performance and congestion have not yet been explored. Therefore, this research aims to investigate the underlying mechanisms of applying pull and push approaches at the location level through simulation, in addition to proposing hypotheses relating push and pull approaches to project and crew performance metrics. Agent-based modeling is used to simulate and describe how push and pull approaches affect crew performance. Results show that pull approaches can achieve significantly higher productivity, less idle time, lower crew turnover, and fewer task interruptions, although they can result in slightly increased project durations. Cross-analyzing the mentioned results with other performance metrics reveals that push and pull approaches should be applied together to achieve a flexible production control system. The significance of this study is embedded in exploring and understanding how the choice of push and pull planning approaches impacts the location-based management of tasks and crew performance. Such impacts on productivity, crew performance, and the flow of site operations enable a convergence to generalized conclusions regarding the efficacy of each method.

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Section: Methodsmentioning

confidence: 99%

Pull planning versus push planning: Investigating impacts on crew performance from a location-based perspective

Ghanem

Hamzeh

Seppänen

et al. 2022

Front. Built Environ.

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“…Ref. [21] stressed the importance of social interaction and exposure to social media without detailing how these variables affect decisions. Ref.…”

Section: Agent-based Modelsmentioning

confidence: 99%

Simulating the Diffusion of Residential Rooftop Photovoltaic, Battery Storage Systems and Electric Cars in Italy. An Exploratory Study Combining a Discrete Choice and Agent-Based Modelling Approach

et al. 2023

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Rooftop solar photovoltaic (PV) systems could significantly contribute to renewable energy production and reduce domestic energy costs. In Italy, as in other countries, the current incentives generate a modest annual increase after the generous fiscal incentives that kick-started the PV market in the 2008–2013 period. Several factors are, however, at play that can speed up the installation process, such as the improvements in PV technology at declining prices, the increased availability of battery-storage (BS) systems, the growing use of electric appliances, the uptake of electric cars, and the increased environmental awareness. We integrate two research methodologies, discrete choice modeling and agent-based modeling, to understand how these factors will influence households’ decisions regarding PV and BS installations and how agents interact in their socioeconomic environment. We predict that in Italy, given the preference structure of homeowners, the continuing decline in costs, and the social interaction, 40–45% of homeowners will have PV or PV and BS installed by 2030, thanks to the existing investment tax credit policy.

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“…Agent-based diffusion models share four basic components: heterogeneous agents, network structure, interpersonal communications, and adoption decision rules (Zhang, Lu & Chen, 2018). The Overview, Design concepts, and Details (ODD) protocol is widely adopted when describing the ABM (Haryadi, Ali Imron, Indrawan & Triani, 2019;Mittal, Krejci & Dorneich, 2019;Moglia, Podkalicka & McGregor, 2018) as it helps to standardize the description by providing the structure and dynamics of the model in a logical and readable manner (Grimm et al, 2020). Most of the papers focus on scenario analysis.…”

Section: Energy Efficiency Diffusion Agent-based Modelsmentioning

confidence: 99%

Modelling energy-efficient renovation adoption and diffusion process for households: A review and a way forward

Hua

Han

Vries

2022

Sustainable Cities and Society

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Predicting Rooftop Photovoltaic Adoption In The Residential Consumers of PLN Using Agent-Based Modeling

Cited by 6 publications

References 11 publications

Pull planning versus push planning: Investigating impacts on crew performance from a location-based perspective

Pull planning versus push planning: Investigating impacts on crew performance from a location-based perspective

Simulating the Diffusion of Residential Rooftop Photovoltaic, Battery Storage Systems and Electric Cars in Italy. An Exploratory Study Combining a Discrete Choice and Agent-Based Modelling Approach

Modelling energy-efficient renovation adoption and diffusion process for households: A review and a way forward

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