The importance of decreasing industrial CO2 footprints has become evident, as also highlighted in COP26. As such, the transition to renewable energy in the industrial sector is essential to meet the targets. To this aim, establishing industrial community energy systems (InCES) where industries collectively invest in a shared energy system is an economically and environmentally attractive option. Yet, the emergence and continuity of such collective initiatives among industrial companies has neither received considerable attention in the scientific literature nor in practice. This research, as the first of its kind, aims to investigate institutional design options that allow for such collaboration to take place for the establishment and continuity of an InCES. Given the bottom-up and collaborative nature of such initiatives, we take an agent-based modeling and simulation approach, for the first time in this area, that incorporates the institutional and societal attributes that influence the formation and continuation of an InCES. We take data from an industrial cluster in Arak, one of the most prominent industrial cities in Iran. The results of this study confirm the economic feasibility of an InCES as compared to individual renewable energy investment in the cluster. The results also highlight the importance of flexible membership in increasing the number of investors (i.e., industrial companies) in such initiatives. Other important recommendations are: considering the installation of at least 15% extra capacity for the powerplant, restricting electricity consumption and enforcing on-time payment of monthly premium fees.@en

Considering that the industrial sector consumes almost one-third of the energy demand globally, it is an urgent call to reduce the carbon footprints in this sector. Among different approaches to meet this goal, such as the employment of carbon capture technologies and increasing energy efficiency within industries, transitioning to renewable electricity (RE) would be another outlook to reduce the carbon footprints and increase the energy security of the industries. Collective power generation within communities has shown to be feasible and promising in the industrial sector, where groups of industries collaborate to generate energy and meet their energy demand. In this research, we investigated how the initiation and continuation of industrial community energy systems (InCES) among companies can take place and which financial incentives the government can introduce to support these initiatives. We built an agent-based model that incorporates cost-benefit analysis and cultural factors in the decision making process of industries, to assess the feasibility of initiating/joining an InCES by industries. This study shows that the FIT mechanism had the worst performance in incentivizing the establishment of an InCES among industries. In contrast, the TAX incentive showed the best performance in mobilizing the investments towards InCES. Similarly, the TAX incentive showed relatively superior performance in electricity generation, the number of established InCESs, and the number of companies joining each InCES. Despite the better performance of the TAX incentive, it was also the most expensive option for the governments as a significant share of the establishment costs of an InCES was put on the shoulders of the governments.@en

Like many other sectors, climate change strategies have put various restrictions on industry, the most prominent one being caps on CO₂ and other energy-related emissions. At the same time, and especially in many developing economies, the industry struggles with an increasing gap between the fast development of the sector and lagging energy supply capacity. Collective generation of renewable energy is seen as a promising means of transition, next to other forms of renewable energy generation (centralised, individual). The aim of this research is to investigate factors influencing willingness to participate in Industrial Community Energy Systems (InCES). Using existing literature on Industrial Symbiosis and Community Energy Systems, we formulate plausible hypotheses on the most relevant factors for the willingness of industries to join such initiatives. As one of the largest and most diversified industrial clusters in Iran, Arak industrial park is selected as the case study. Data were collected from the CEOs of 96 companies through survey research. Our results highlight the crucial role of awareness about the benefits of renewable power generation in an InCES. Social identity among industries and trust between them are also determining factors for their willingness to join InCES. Finally, proper institutional design for overcoming the partnership complexities (e.g., conflict resolution) was highlighted as a crucial factor for industries. It can be concluded from the results of this study that policymakers should avoid one-size-fits-all incentive design approaches and reach out to larger companies with targeted incentives, introduce specially designed bank loans for different target groups, and make use of consulting companies as intermediaries to increase the awareness of the industries regarding the benefits of investing in an InCES.

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The industrial sector plays a huge role in creating economic growth. While energy is vital for industries to thrive, various factors are undermining the availability of energy including phasing out of fossil fuels, CO2 emission caps and, the large gap between the fast developments of industrial clusters and the energy supply, especially in developing countries. Recently, enabled by renewable energy technologies, a transition process is taking place towards decentralized settings for energy provision where households in neighbourhoods initiate renewable electricity cooperatives. The question addressed in this research is if or to what extent the model of collective action deployed by citizen cooperatives is applicable to collaborations between industries in an industrial cluster. We identified the conditions for the establishment of Industrial Community Energy Systems (InCES) from a collective action perspective by using Ostrom's Institutional Analysis and Development Framework. The case study selected is the industrial city of Arak, one of the largest and most diversified industrial clusters in Iran. Besides desk research, data was also collected by conducting semi-structured interviews and by holding stakeholder workshops. The results of this study highlight the importance of community spirit and trust for the establishment of InCES, unlike citizen cooperatives where finance and environmental attitude are essential. A transparent legal framework to resolve conflicts that might emerge in industrial partnerships is another crucial element given the many differences among industries such as differences in energy demand and in usage patterns.

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World biofuel production and trade have grown exponentially in the last decade. Nevertheless, the interaction between the markets for oilseeds (food/feed/bioenergy) and liquid vegetable oil-based biofuels is overwhelmingly complex and thus not well understood. In this study, we developed a spatially explicit agent-based model to provide insights into the effect of farmers' behaviour on trade flows and biodiesel production and to shed light on the influence of import tariffs for both palm oil and biodiesel on system behaviour. This new approach enables us to assess different types of rational economic behaviour for the adoption of crops by farmers. Results show that model outcomes can vary substantially based on the assumptions made concerning the behaviour of farmers. Moreover, we found that biodiesel trade and production are more sensitive to a change in the EU-28's biodiesel import tariff than to a change in the EU-28's palm oil import tariff. Overall, our results show that social processes, actors' heterogeneity, and institutions play an important role in the behaviour of the system.

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The aviation industry accounts for more than 2% of global CO ₂ emissions. Biojet fuel is expected to make an essential contribution to the decarbonization of the aviation sector. Brazil is seen as a key player in developing sustainable aviation biofuels owing to its long-standing experience with biofuels. Nevertheless, a clear understanding of what policies may be conducive to the emergence of a biojet fuel supply chain is lacking. We extended a spatially explicit agent-based model to explore the emergence of a biojet fuel supply chain from the existing sugarcane–ethanol supply chain. The model accounts for new policies (feed-in tariff and capital investment subsidy) and new considerations into the decision making about production and investment in processing capacity. We found that in a tax-free gasoline regime, a feed-in tariff above 3 R$/L stimulates the production of biojet fuel. At higher levels of gasoline taxation (i.e., 2.46 R$/L), however, any feed-in tariff is insufficient to ensure the production of biojet fuel. Thus, at these levels of gasoline taxation, it is needed to introduce regulations on the production of biojet fuel to ensure its production. Given the current debate about the future direction of the biofuel policy in Brazil, we recommend further research into the effect of market mechanisms based on greenhouse gas emissions on the emergence of a Brazilian biojet fuel supply chain.

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This chapter explores potential ways to implement, and benefits for policymaking of, the complementary use of two different types of modelling for analysing residential energy consumption and ethnographic research. The more traditional approach of techno-economic modelling is considered alongside agent-based modelling that incorporates both causal and intentional relationships; ethnographic approaches provide 'thick understanding' of the relationships between social and technical elements and the environment. In doing so, the chapter builds on real examples from academic-policy engagement in the EU on energy demand, consumption and services. We examine three myths of the role of modelling in policymaking and propose practical ways of employing different types of modelling in a complementary way to increase policymakers' understanding of residential energy demand, consumption and services. Finally, we make three concrete recommendations for developing future interdisciplinary work on integrating social and technical models for informing policy.

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The Brazilian government aims to increase the share of biofuels in the energy mix to around 18% by 2030, which implies an increase of ethanol production from currently 27 bln liters to over 50 bln liters per year. Biofuel policies play an important role in ethanol production, consumption, and investment in processing capacity. Nevertheless, a clear understanding of how current policies affect the evolution of the market is lacking. We developed a spatially-explicit agent-based model to analyze the impact of different blend mandates and taxes levied on gasoline, hydrous, and anhydrous ethanol on investment in processing capacity and on production and consumption of ethanol. The model uses land use projections by the PCRaster Land Use Change model and incorporates the institutions governing the actors’ strategic decision making with regard to production and consumption of ethanol, and the institutions governing the interaction among actors. From the investigated mix of policy measures, we find that an increase of the gasoline tax leads to the highest increased investments in sugarcane processing capacity. We also find that a gasoline tax above 1.23 R$/l and a tax exemption for hydrous ethanol may lead to doubling the production of ethanol by 2030 (relative to 2016).

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The economic performance of biofuels supply chains depends on the interaction of technical characteristics as technological pathways and logistics, and social structures as actor behavior, their interactions and institutions. Traditional approaches focus on the technical problems only. Little attention has been paid to the institutional analysis of biofuel supply chains. This paper aims to extend the analysis of the effect of institutions on the emergence of biofuel supply chains by developing a conceptual framework that combines elements of complex adaptive systems, (neo) institutional economics and socio-technical systems theory. These elements were formalized into an agent-based model. The proposed method is illustrated by a case study on a biodiesel supply chain in Germany. It was found that the patterns in production capacity result from investors basing their decisions on optimistic perceptions of the market development that increase with a favorable institutional framework. Conversely, patterns in biodiesel production cannot be completely explained by this mechanism. The proposed framework assisted the model conceptualization phase and allowed the incorporation of social structures into the agent-based model. This approach could be developed further to provide insights on the effect of different future deployment strategies on bioenergy systems emergence and development.

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Biofuel production is not cost competitive and thus requires governmental intervention. The effect of the institutional framework on the development of the biofuel sector is not yet well understood. This paper aims to analyze how biofuel production and production capacity could have evolved in Germany in the period 1992–2014. The effects of an agricultural policy intervention (liberalization of the agricultural market) and a bioenergy policy intervention (a tax on biodiesel after an initial exemption) are explored. Elements of the Modeling Agent systems based on Institutional Analysis (MAIA) framework, complex adaptive systems (CAS) theory, and Neo Institutional Economics (NIE) theory were used to conceptualize and formalize the system in an agent-based model. It was found that an early liberalization of the agricultural market led to an under-production of biodiesel; a late liberalization led to the collapse of biodiesel production. An early introduction of the biodiesel tax led to stagnation in biodiesel production and production capacity; a late introduction led to an increase in sunk costs provided that the biofuel quota is binding. Also, a lack of agents’ adaptation mechanism to forecast prices led to a decrease in patterns of biodiesel production when an external shock was introduced in the system. In sum, we argue that system behavior is influenced by individual behavior which is shaped by institutions.

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This paper investigates the impact of the inter-regional transmission grid capacity expansion on China's power sector decarbonization from the energy portfolio, economic efficiency and environmental perspectives. The impact is quantified based on a cluster integer unit commitment model which renders it suitable for modeling large-scale power systems with a high computational performance. The results show that, first, the inter-regional transmission grid capacity expansion has obvious economic benefit in reducing the total variable generation costs, mainly due to the increased ability of transmitting coal power with low marginal generation costs and the reduction in non-served load. Second, the expansion has a very limited impact on reducing the curtailment of renewable generation by 2030, although the extent to which the expansion can mitigate the curtailment of renewable generation increases with the share of renewable power in the generation portfolio. Third, the expansion increases CO₂ emissions of the power supply in 2030 by around 2%, mainly because it facilitates more use of cheap yet low-efficiency coal generation in regions with low fuel prices. To better deliver the value of the inter-regional grid expansion for China's power decarbonization, this paper proposes that: (1) the planning of the inter-regional and intra-regional grid development should be coordinated with the renewable power development; and (2) effective dispatch mechanisms which account for CO₂ emissions or generation efficiency across regions should be established. Additionally, the government plan of the inter-regional transmission capacity in 2030 is basically sufficient in enabling bulk power delivery and promoting renewable generation across regions.

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In this paper we demonstrate how agent-based modelling can be used to understand the emergence of a new infrastructure system, more specifically, a biogas infrastructure in the Netherlands. The innovative element in our modelling approach is the use of MAIA (modelling agent systems using institutional analysis), a meta-model for agent-based modelling of socio-technical systems, to conceptualise and gain insights into the complexity of infrastructure systems. Through our agent-based simulation model we were able to see how the BioNet infrastructure might evolve over three decades, under various conditions of social norms and institutions. We found that current social norms and institutions allow agricultural biogas production to be economically feasible without any subsidies. The simulations also reveal low expected returns on investment and significant risks for farmers in biogas projects.@en

This work investigates different scenarios for electric vehicle (EV) deployment in China and explores the implications thereof with regard to energy portfolio, economics and the environment. Specifically, we investigate how to better deliver the value of EVs by improving designs in the power system and charging strategies, given expected developments by 2030 in both the power system and EV penetration levels. The impact of EV charging is quantified by applying an integrated transportation-power system model on a set of scenarios which represent uncertainties in charging strategies. We find that deploying EVs essentially shifts the use of gasoline to coal-fired power generation in China, thus leading to more coal consumption and CO₂ emissions of the power system. Economically, EVs outperform gasoline-powered vehicles in terms of average fueling costs. However, the impact of EVs in terms of CO₂ emissions at the national level largely depends on the charging strategy. Specifically, controlled charging results in more CO₂ emissions associated with EVs than uncontrolled charging, as it tends to feed EVs with electricity produced by cheap yet low-efficiency coal power plants located in regions where coal prices are low. Still, compared with uncontrolled charging, controlled charging shows absolute advantages in: (1) mitigating the peak load arising from EV charging; (2) facilitating RES generation; and (3) reducing generation costs and EV charging costs. Hence, in light of this trade-off of controlled charging with the goals of energy security, economic efficiency and reducing environmental impacts, policy interventions in the Chinese power system should opt for controlled charging strategies in order to best realize the benefits of EVs. Accordingly, this paper proposes that increasing the use of cleaner forms of electricity generation, such as RES power and gas power, and establishing energy efficiency and CO₂ emission regulations in power dispatch are critical for China. Lastly, this work illustrates what the optimized charging profiles from the power system perspective look like for different regions. These results can inform Chinese policy makers in creating a better integration of the transportation and the power system.

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In dit working paper buigen Weijnen, Correljé en De Vries zich over de vraag of infrastructuren handelingsperspectief bieden voor milieu- en duurzaamheidsbeleid. Vanwege hun kapitaalintensiteit en daarmee samenhangende lange levensduur worden infrastructuren vaak gezien als onderdeel van het duurzaamheidsprobleem, in die zin dat zij onduurzame systemen en routines bestendigen.De auteurs betogen dat infrastructuren ook gezien kunnen worden als (deel van de) oplossing. Hoewel de huidige gefragmenteerde institutionele context de oplossingsruimte beperkt, is er nog een groot onbenut potentieel om de inrichting van fysieke infrastructuren en infrastructuurgebonden markten te sturen ten dienste van duurzaamheidsdoelstellingen. @en