To facilitate energy transition, in several countries regulators have devised ‘regulatory sandboxes’ to create a participatory experimentation environment for exploring revision of energy law. These sandboxes allow for a two-way regulatory dialogue between an experimenter and an approachable regulator to innovate regulation and enable new socio-technical arrangements. However, these experiments do not take place in a vacuum but need to be formulated and implemented in a multi-actor, polycentric decision-making system through collaboration with the regulator but also energy sector incumbents such as the distribution system operator. We are, therefore, exploring new roles and power division changes in the energy sector as a result of such a regulatory sandbox. We research the Dutch Energy Experimentation Decree (EED) that invites homeowners’ associations and energy cooperatives to propose projects prohibited by extant regulation. In order to localize, democratize and decentralize energy provision, local experimenters can, for instance, organise peer-to-peer supply and determine their own tariffs for energy transport. Theoretically, we rely on Ostrom’s concept of polycentricity to study the dynamics between actors involved in and engaging with the participatory experiments. Empirically, we examine 4 approved EED experiments through interviews and document analysis. Our conclusions focus on the potential and limitations of bottom-up, participatory innovation in a polycentric system. The most important lessons are that a more holistic approach to experimentation, inter-actor alignment, providing more incentives, and expert and financial support would benefit bottom-up participatory innovation.
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The energy transition requires the transformation of communities and neighbourhoods. It will have huge ramifications throughout society. Many cities, towns and villages have put together ambitious visions about how to achieve e.g. energy neutrality, zero-emission or zero-impact. What is happening at the local level towards realizing these ambitions? In a set of case study’s we investigate the following questions: How are self-organized local energy initiatives performing their self-set tasks? What obstacles are present in the current societal set-up that can hinder decentralized energy production? In our cases local leadership, vision, level of communication and type of organisation are important factors of the strength of the ‘local network’. (Inter)national energy policy and existing energy companies largely determine the ‘global’ or outside network. Stronger regional and national support structures, as well as an enabling environment for decentralized energy production, are needed to make decentralized sustainable energy production a success.
The increasing share of renewable production like wind and PV poses new challenges to our energy system. The intermittent behavior and lack of controllability on these sources requires flexibility measures like storage and conversion. Production, consumption, transportation, storage and conversion systems become more intertwined. The increasing complexity of the system requires new control strategies to fulfill existing requirements.The SynergyS project addresses the main question how to operate increasingly complex energy systems in a controllable, robust, safe, affordable, and reliable way. Goal of the project is to develop and test a smart control system for a multi-commodity energy system (MCES), with electricity, hydrogen and heat. In scope are an industrial cluster (Chemistry Park Delfzijl) and a residential cluster (Leeuwarden) and their mutual interaction. Results are experimentally tested in two real-life demo-sites scale models: Centre of Expertise Energy (EnTranCe) and The Green Village (TU Delft) represent respectively the industrial and residential cluster.The result will be a market-driven control system to operate a multi-commodity energy system, integrating the industrial and residential cluster. The experimental setup is a combination of physical demo-site assets complemented with (digital) asset models. Experimental validation is based on a demo-scenario including real time data, simulated data and several stress tests.In this session we’ll elaborate more on the project and present (preliminary) results on the testing criteria, scenarios and experimental setup.
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