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Understanding the possible transition pathways of the energy system requires the integration of human behaviour in energy system models. In order to model the influence of actor behaviour we have developed ACT (Agent-Based Model of Critical Transitions), an agent-based model inspired by an existing conceptualisation of critical transitions. ACT all...
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... concept of critical transitions [65] explores which system characteristics may lead to different types of transitions. It shows the development of a catastrophe fold; when external condition change a bifurcation point can be passed that makes a previously stable system show a critical transition to another system state (see Fig. 1. Scheffer et al. [65] show several aspects of actor behaviour that are relevant to the analysis of critical transitions. Social aspects such as peer pressure, the absence of leaders, the complexity of the problem and homogeneity of the population can decrease the pace in which society acts to a certain problem (see Section 1). Because ...
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... The role of states in increasing engagement transition processes was not addressed adequately [138,139], and the critical role of public and democratic engagement in low-carbon energy transition has been disregarded in many studies [34,140]. Widespread public acceptance is vital to promote an energy transition toward a low-carbon system [15,87]; also, public engagement increases the reliability of low-carbon technologies and, in general, the acceptability of low-carbon energy transition [13,141]. Behavioral change is needed for public acceptance, stimulating To propose a mathematical model to evaluate the copper availability due on 2050 -active engagement in a decentralized energy system [142]. ...
... Agents have internal properties as well as rules of interaction. These models reproduce complex behaviour from local microeconomic interactions (Epstein and Axtell 1996), which allows for the simulation of a wide variety of phenomena (Kaaronen and Strelkovskii 2020;Waring et al. 2015;Rai and Robinson 2015;Kraan et al. 2019) including the diffusion of cultural traits in a population (Axelrod 1997). Thus, ABMs lend themselves well to the study of cultural and behavioural change as these processes occur through the progressive accumulation of social interactions. ...
... From within this community there is a recognition that the demand side is often underrepresented and that energy models lack insight on consumer behaviour, and as a result risk favouring more quantifiable mitigation options such as emissions removals [80]. These models are found to have limited scope to accommodate the combined effects of investment and commercial decision making under conditions of uncertainty [81]. In short, the roles of consumers, investors and utilities have been relatively poorly incorporated into energy scenarios and futures worksee Table 1. ...
This paper brings together socio-technical transitions theory with strategic foresight and human centred design. The aim is to bring in new methods for analysing the business model element of sustainability transitions. We propose a process for doing business model innovation work. Business models have become a key area of focus, particularly in the energy sector. Recent work shows how the development of new business models co-evolves with elements of the energy system, either driving technological innovation, changing user practices or placing pressure on the institutional or policy regime. At the same time, there is no recognised process for business model research aimed at transition management. It is time therefore to propose a more formalised and theoretically grounded approach to business model innovation work. We use this contribution to synthesise the lessons of a four-year research project centred on energy utility business models with industrial, commercial and government stakeholders. We describe the process adopted, and insights this process generated. We seek to establish this process in the literature, invite others to utilise it, adapt it and critique it.
... In social simulations a trend towards more complex and data driven models can be observed and has been introduced by Edmonds and Moss (2005) under the slogan "Keep it Descriptive, Stupid" (KIDS). Since then, several papers have discussed the KIDS approach and the need for more realistic models to leverage the strengths of ABM to analyze external and internal mechanisms (Pastrav and Dignum (2020); Kraan et al. (2019); Conte and Paolucci (2014)). More complex models also require populations that represent the distribution of a large number of attributes and satisfy several constraints regarding the social network. ...
... It is advantageous to replicate the dynamics of liberalized electricity markets and energy transition progress by incorporating heterogenous actors' behavior [50,51]. It also allows the exploration of the role of community players with their cognitive bias in energy transitions [52]. The exploration of plausible trajectories of energy transitions given uncertain socio-technical conditions is also possible with ABS [53,54]. ...
Energy transitions are complex and involve interrelated changes in the socio-technical dimensions of society. One major barrier to renewable energy transitions is lock-in from the incumbent socio-technical regime. This study evaluates Energy Product–Service Systems (EPSS) as a renewable energy market mechanism. EPSS offer electricity service performance instead of energy products and appliances for household consumers. Through consumers buying the service, the provider company is enabled to choose, manage and control electrical appliances for best-matched service delivery. Given the heterogenous market players and future uncertainties, this study aims to identify the necessary conditions to achieve a sustainable renewable energy market. Simulation-Based Design for EPSS framework is implemented to assess various hypothetical market conditions’ impact on market efficiency in the short term and long term. The results reveal the specific market characteristics that have a higher chance of causing unexpected results. Ultimately, this paper demonstrates the advantage of implementing Simulation-Based Design for EPSS to design retail electricity markets for renewable energy under competing market mechanisms with heterogenous economic agents.
... Currently only two ABM studies address path-dependency in investment decisions. In the ABM developed by Kraan et al. [6,50] path-dependency takes the form of an investor's future investments being influenced by the performance of his past investments. The second study is the study by De Vries et al. [51] which introduces a risk aversion function linked to historical profits in investment decisions in the EMLab model. ...
Market players in the energy sector transition are heterogeneous, have bounded rationality and are influenced by their own past failures, as well as imitating the successes of their competitors. However this agent heterogeneity and complex behaviour in investment choices is not taken into account in traditional energy-economy models used to inform energy sector policies. By using BRAIN-Energy, an agent-based model of investment in electricity generation, which enables to study the impact of actors’ heterogeneous characteristics on the transition pathways of the UK, German and Italian electricity sectors, this paper shows how historic path-dependency in investment choices displaces low-carbon in favour of high-carbon investments under a weak regulatory framework. By contrast, imitation can help the diffusion of renewable technologies, through a self-reinforcing positive feedback when government subsidies to low-carbon investments are in place.
... In fact, M&S has been increasingly used in recent years to study sustainability transitions at a variety of scales from one (relatively) stable socio-ecological equilibrium to another. For example, M&S has been employed to study the importance of local communities and the role of local leaders in encouraging or discouraging low-carbon energy transitions [19], and the importance of broader, collaborative, multi-level adaptive strategies for managing regional and international sustainability transitions [20]. Other models have been able to simulate some of the major historical shifts in human civilizational forms, such as the transition from hunter-gathering to sedentary agriculture [21], the transition from pre-Axial to Axial Age civilizations across the globe during the first millennium BCE [22], and the ongoing modern transition from cultures in which supernatural beliefs play a dominant role in maintaining social cohesion to more naturalistic and secular cultures [23]. ...
... ABMs have also been used to evaluate policies for promoting "climate clubs" oriented toward facilitating cooperation among institutions and states in response to the challenges of the Anthropocene [16,[51][52][53]. Social simulation techniques are increasingly applied in the study of sustainability transitions such as shifts toward low-carbon energy [19,54]. For reviews of other uses of ABMs to address issues related to human adaptation and sustainability, see [17,24,55,56]. ...
This article begins with a brief outline of recent advances in the application of computer modeling to sustainability research, identifying important gaps in coverage and associated limits in methodological capability, particularly in regard to taking account of the tangled human factors that are often impediments to a sustainable future. It then describes some of the ways in which a new transdisciplinary approach within “human simulation” can contribute to the further development of sustainability modeling, more effectively addressing such human factors through its emphasis on stakeholder, policy professional, and subject matter expert participation, and its focus on constructing more realistic cognitive architectures and artificial societies. Finally, the article offers philosophical reflections on some of the ontological, epistemological, and ethical issues raised at the intersection of sustainability research and social simulation, considered in light of the importance of human factors, including values and worldviews, in the modeling process. Based on this philosophical analysis, we encourage more explicit conversations about the value of naturalism and secularism in finding and facilitating effective and ethical strategies for sustainable development.
... There are few analyses of real-world applications [6], and discussions around the virtues and shortcomings of P2P energy trading rest predominantly on theoretical analyses to date (cf. [13,14]). Systematic, empirically-based investigations are needed [12] to move beyond theoretical discussions and to advance our understanding of the effects of P2P energy trading on participants and infrastructure alike (cf. ...
... ABM is a computer simulation technique that uses an in silico approach to model micro-level actions and interactions to study the emergence of macro-level phenomena for complex adaptive systems [18]. Here, we simulate the interactions of prosumers and consumers with the physical, technical, and financial aspects of P2P systems to generate insight about the emerging dynamics of electricity prices [4,14,19]. The ABM framework is applied using empirical data to simulate decentralized electricity trades in an existing residential neighborhood in Perth, Western Australia. ...
The transfer of market power in electric generation from utilities to end-users spurred by the diffusion of distributed energy resources necessitates a new system of settlement in the electricity business that can better manage generation assets at the grid-edge. A new concept in facilitating distributed generation is peer-to-peer energy trading, where households exchange excess power with neighbors at a price they set themselves. However, little is known about the effects of peer-to-peer energy trading on the sociotechnical dynamics of electric power systems. Further, given the novelty of the concept, there are knowledge gaps regarding the impact of alternative electricity market structures and individual decision strategies on neighborhood exchanges and market outcomes. This study develops an empirical agent-based modeling (ABM) framework to simulate peer-to-peer electricity trades in a decentralized residential energy market. The framework is applied for a case study in Perth, Western Australia, where a blockchain-enabled energy trading platform was trialed among 18 households, which acted as prosumers or consumers. The ABM is applied for a set of alternative electricity market structures. Results assess the impact of solar generation forecasting approaches, battery energy storage, and ratio of prosumers to consumers on the dynamics of peer-to-peer energy trading systems. Designing an efficient, equitable, and sustainable future energy system hinges on the recognition of trade-offs on and across, social, technological, economic, and environmental levels. Results demonstrate that the ABM can be applied to manage emerging uncertainties by facilitating the testing and development of management strategies.
... Similarly, in the ABM developed by [38,39], which aims to study the investment behaviours of heterogeneous investors with heterogeneous expectations of the future, policy instruments are exogenous and different CO2 price scenarios are defined at the beginning of the simulations. ...
Achieving electricity sector transitions consistent with stringent climate change mitigation under the Paris Agreement requires a careful understanding both of the coordinating role of national governments and of its interactions with the heterogeneous market players who will make the low-carbon investments in the electricity sector. However, traditional energy models and scenarios generally assume exogenous policy targets and fail to capture this co-evolution between policy-makers and heterogeneous private and public investors. This paper uses BRAIN-Energy, a novel agent-based model of investment in electricity generation to simulate and contrast government and investor dynamics in the transition pathways of the UK, German and Italian electricity sectors. Key findings show that a successful transition – which achieves the energy policy “trilemma” (low carbon, secure, affordable) – requires the co-evolution of the policy dimension (strong and frequently updatable CO2 price, renewable subsidies and capacity market) with the strategies of the heterogeneous market players. If this dynamic balance is maintained then incentives are politically feasible and suppliers learn and evolve (in what we term a virtuous cycle). If either the incentives are too weak to drive learning or too expensive so the policy regime collapses, then the transition fails on one of its key dimensions (in what we term a vicious cycle). Getting this balance right is harder in risky markets that also have players with more pronounced bounded rationality and path dependence in how they make investments.
... Finally, while most reviewed studies examine the effectiveness of policies in reducing emissions-directly or indirectly, as through energy conservation and product/technology diffusion-an equally important feature of policies is their political feasibility, mediated by public opinion. Few ABM studies examine opinion dynamics of agents with regard to climate change and how this affects their voting decisions which translate in political support for, or resistance to, climate policies (Geisendorf, 2016;Kraan, Dalderop, Kramer, & Nikolic, 2019). Such studies, however, were not covered in our sample, as they lack a clear policy instrument or connection to emission reductions or product/technology diffusion. ...
Agent‐based models (ABMs) have recently seen much application to the field of climate mitigation policies. They offer a more realistic description of micro behavior than traditional climate policy models by allowing for agent heterogeneity, bounded rationality and nonmarket interactions over social networks. This enables the analysis of a broader spectrum of policies. Here, we review 61 ABM studies addressing climate‐energy policy aimed at emissions reduction, product and technology diffusion, and energy conservation. This covers a broad set of instruments of climate policy, ranging from carbon taxation, and emissions trading through adoption subsidies to information provision tools such as smart meters and eco‐labels. Our treatment pays specific attention to behavioral assumptions and the structure of social networks. We offer suggestions for future research with ABMs to answer neglected policy questions.
This article is categorized under:
• Climate Economics > Economics of Mitigation
