In the context of increasing decentralised electricity generation, choosing the right regulation policy is a complex decision problem which is key to the economically sustainable integration of distributed generation technologies. The complexity of this problem lies mainly in the fact that distribution network (DN) prices dynamically adapt to the evolution of decentralised generation, due to the cost recovery schemes of the distribution network operators. Such evolution, in return, is strongly influenced by DN prices.
Under certain regulation policies, the introduction of distributed generation may create what is known as a death spiral, by which an uncontrolled growth in electricity prices may take place as a response to the decrease in the overall electricity demand of the system, due to the integration of distributed generation in the electricity distribution system. This effect is illustrated in the following figure.
Our paper introduces a computational tool capable of assessing the impact of different regulation policies on the dynamic evolution of DN prices, and on the deployment of distributed renewable energy (DRE) generation. Our model includes all mechanisms that force electricity prices to dynamically adapt with the evolution of decentralised electricity production. Furthermore, to the best of our knowledge, there is no other simulator in the literature that enables testing of various regulation policies, regarding their suitability for fostering distributed generation in an economically sustainable fashion (without inducing a death spiral), accounting for the dynamic evolution of DNs.
More precisely, we model individual electricity consumers as rational agents, who may invest in optimised distributed renewable energy installations, if they are cost-efficient when compared to the network tariff. By modelling the cost recovery scheme of the distribution system operator, the simulator then computes the evolution of the network tariff in response to a change in the consumption and generation of the consumers in the DN, due to the deployment of distributed generation. The simulator is illustrated with various regulation policies.
This work as has been achieved in collaboration with the department of economy of the University of Liege (HEC Liege), sharing our respective visions of the problem, and working together in the modelling of the simulator.
Our simulator may help attain a better understanding of tarification issues and provide insight into how to design new distribution tariffs. We would be honoured to assist regulators worldwide looking for new (smart) ways of designing distribution tariff policies.