Hybrid Approach for Modelling the Uptake of Residential Solar PV Systems, with Case Study Application in Melbourne, Australia

M. Moglia, C. Nygaard, Stephen Glackin, S. Cook, S. Tapsuwan
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Abstract

: Understanding the processes of residential solar PV uptake is critical to developing planning and policy energy transition pathways. This paper outlines a novel hybrid Agent-Based-Modelling/statistical adoption prediction framework that addresses several drawbacks in current modelling approaches. Specifically, we extend the capabilities of similar previous models and incorporate empirical data, behavioural theory, social networks and explicitly considers the spatial context. We provide empirical data affecting households’ propensity to adopt, including perceptions of solar PV systems, the role of tenure and urban location. We demonstrate the approach in the context of Melbourne metropolitan region, Australia; and draw on housing approval data to demonstrate the role of housing construction in accelerating adoption. Finally, we explore the approach’s validity against real-world data with promising results that also indicate key areas for further research and improvement.
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模拟住宅太阳能光伏系统吸收的混合方法,在澳大利亚墨尔本的案例研究应用
了解住宅太阳能光伏吸收的过程对于制定能源转型路径的规划和政策至关重要。本文概述了一种新的基于智能体的建模/统计采用混合预测框架,该框架解决了当前建模方法中的几个缺点。具体而言,我们扩展了类似先前模型的功能,并结合了经验数据、行为理论、社会网络,并明确考虑了空间背景。我们提供了影响家庭采用太阳能光伏系统的倾向的经验数据,包括对太阳能光伏系统的看法,使用权和城市位置的作用。我们在澳大利亚墨尔本大都市区的背景下展示了这种方法;并利用住房审批数据来论证住房建设对加快收养的作用。最后,我们探讨了该方法对现实世界数据的有效性,并获得了有希望的结果,也表明了进一步研究和改进的关键领域。
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