Towards including policy modelling in linear optimization cluster modelling

Abstract

How well spent is public money concerning sustainability goals? How effective and efficient are these policies? Even though it is widely acknowledged that actions against climate change are urgently needed in the near future, policy makers little insight in how potential policies can be designed most effectively. To evaluate the impacts of sustainability policies on industry, such as carbon taxes and hydrogen subsidies, policies should be included within industrial cluster models. This policy modelling approach leads to effective and efficient use of public finance and time. This research foresees in this demand by applying a module thinking strategy. This allows for the creation of plug-and-play policy modules that can be used in future research to determine the most effective or efficient policy to achieve sustainable industrial clusters. To this end, scope variables are identified that provide buttons to design policies. Future research should focus on validating these scope variables to a further extend and potentially enable generalisation of the policy modules. The authors choice to use linear optimization resulted in only being able to evaluate generation based policies (like feed-in tariffs). Designing also investment based policies (like lump-sum subsidies) requires further attention.