Exploring biogas stakeholder interaction in the Netherlands: An Agent Based Modeling approach to explore location specific biogas system performance under different scenarios

Biogas networks can reduce CO2 emissions by replacing natural gas consumption with biogas consumption. This means that biogas production can contribute to the Dutch targets to reduce CO2 emissions by 20% and increase renewable energy production to 16% by 2020 compared to 1990 levels. It is unclear how the biogas infrastructure system will develop over the coming years in the Netherlands and therefore how it will contribute to the Dutch CO2 reduction and renewable energy production targets. A deep understanding of the biogas infrastructure system and the impact of different policies and external factors over the long term is currently missing. Current scientific literature proposes policy changes to develop the Dutch biogas system, but it does not quantify the effects of these proposals. Linear programming approaches have been used to quantify the impact of different model parameters, but are unsuitable to capture system development and policy changes due to their over simplification of reality. Nevertheless, computer simulation of the biogas system is a useful way to assess the impact of policies and scenarios over a long period of time. In fact, simulation is necessary since biogas networks are an innovation in biogas production and there are only a few existing biogas pipelines and biogas grids under development in the Netherlands. Agent based modeling is useful for modeling system developments and policy changes by separately modeling the institutions, technical system and stakeholder interactions. Agent based simulation of biogas networks is relatively new, which leads to the following research questions: How can we develop a simulation model to explore the conditions for, and characteristics of a robust biogas infrastructure system? 1. What social aspects are relevant to model for the biogas infrastructure system? 2. What technical aspects are relevant to model for the biogas infrastructure system? 3. What operational aspects are relevant to model for the biogas infrastructure system? 4. What parameters is the simulation model sensitive to? Models are simplifications of reality, which is why the first research objective is: To create a conceptual model which captures the biogas system concepts in a structured way and which serves as a bridge between the real world and computer simulation model. In order to study the biogas system it has to be implemented in a computer simulation model, resulting in the second research objective: To run experiments on the biogas simulation model to explore the conditions for and characteristics of a robust biogas system. Outcomes In this research a conceptual model of the Dutch biogas infrastructure system was created using the MAIA meta-model. The conceptual model focusses on the biogas production by agricultural firms and water treatments. The conceptual model can be used by programmers, without any prior knowledge of the biogas infrastructure system, to implement a simulation model. In this research the conceptual model was implement in an agent based model using NetLogo and experiments were performed on the simulation model to explore the conditions for and characteristics of a robust biogas system. The outcomes provide insights in the possible development of the biogas infrastructure system and the parameters that drive these developments. Results A robust biogas infrastructure system can develop without any subsidies, but the future is very uncertain. In 54% of the cases there is no biogas production since it is not economically viable. In the remaining 46% agricultural biogas projects have a positive cash flow. However, around 69% of the projects have a negative Net Present Value. External market prices for co-substrates, natural gas and CO2 largely determine the feasibility and profitability of biogas production. Longer depreciation periods as well as increasing natural gas prices increase the initial profitability of biogas, but also expose agricultural firms to the risks and uncertainty of external price developments. Socialization of biogas pipeline costs does not increase the biogas systems’ performance in terms of biogas production and yearly profits. Renegotiating biogas prices for existing contracts increases the profitability of biogas projects, because it reduces the risks of changing external market prices for biogas producers. Reflection The conceptual model should be expanded with additional sub-systems, such as local manure and co-substrate markets, to better understand their dynamics and impacts. There is little information available about the production and direct use of biogas. Assumptions underlying the Net Present Value calculations largely determine experimental outcomes, which makes it harder to meaningfully interpret and use the data. Few policy options were explored during the experiments, limiting the amount of policy recommendations that can be made. Policy recommendations The following policy recommendations are expected to reduce the uncertainty of biogas production and profitability. Policy implementation is expected to increase biogas production by 37% and average cash flows by 64%. However, around 66% of the biogas projects are still expected to have a negative Net Present Value. Expand the positieve lijst to allow agricultural firms to use a wider range of co-substrates as well as local waste streams. This is expected to lower the costs of co-substrates for agricultural biogas producers. 1. Increase depreciation periods to 15 years, but operate the biogas production for the duration of its (longer) technical lifetime. Investments in biogas projects should be earned back within a reasonable period, but technical lifetimes far exceed the economic lifetimes of biogas assets. 2. Redistribute uncertainty in a fair way by periodically renegotiating contract prices. Biogas contracts have a long lifetime and the price of biogas should be adjusted to changes in the prices of natural gas, co-substrates and CO2. Future research More research domains should be combined by expanding the conceptual model, resulting in a richer model that can better explain emerging system behavior. Especially the manure and co-substrate sub-systems are important candidates due to their high impacts on operational costs of agricultural biogas producers. Efforts should be made to compare simulation models of the biogas system in terms of structure and output. As more simulation models are being created comparisons can lead to new insights, or comparisons can put simulation results into perspective. Additionally, the usefulness of different simulation methods can be assessed. Smart agents should be implemented to allow for better decision making in the dynamic biogas system. This allows the agents to make predictions and decisions based on historical and current information. Persisting trends are not recognized by normal agents, which can put them at risk in a biogas system where the value of biogas and the price of co-substrates are not linked together. Further research should be done to challenge and improve the underlying assumptions of the Net Present Value calculations of biogas projects. Other measures, such as Return on Investment, should also be explored. Collaborative modeling can help in creating scenarios that are accepted by the involved stakeholders. These simulations of the biogas system focus on exploring the possibilities of biogas rather than predicting developments in biogas production.Systems Engineering, Policy Analysis and ManagementEnergy & IndustryTechnology, Policy and Managemen