Flexibility services by a community microgrid
Quantifying the value of flexibility services by a community microgrid in the context of the Dutch electricity sector using Schoonschip as case study
C.G.J. Hügel (TU Delft - Electrical Engineering, Mathematics and Computer Science)
H.L. la Poutré – Mentor
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Abstract
The volatile production of renewable energy sources is often considered a key issue in future sustainable energy systems. Drawing on microgrid research, we argue that the potential synergy between microgrid energy management and provision of flexibility services to the wider grid could be further explored. In addition, the trade-off between cost minimisation and energy autarky of a community microgrid has not yet been fully investigated. This study therefore investigates the role of community microgrids in managing the volatility of renewable energy production in the wider grid, while also considering local optimisation trade-offs. The goal of this study is threefold: (1) identifying possibilities for market interactions, (2) developing simulation models and optimization/decision software, and (3) conducting exploratory experiments.
To illustrate our ideas, the community microgrid of Schoonschip was used as a case study. This Schoonschip microgrid contains 30 floating houseboats, that are equipped with the following energy resources: PV panels, batteries, modulating heat pumps, thermal collectors, buffer tanks, underfloor heating systems and electrical boilers. The resources are centrally controlled by an energy management system and the Schoonschip microgrid is connected via an interconnection of 160kVA. Simulation models were created for simulating the energy resources and heat demand of the houses. Optimization/decision software was developed and used for microgrid energy management and control of flexibility services.
This thesis provides insights into (1) potential market interactions between a community microgrid and the Dutch electricity wholesale market, (2) the trade-off between maximisation of the forecasted solar self-consumption and minimisation of electricity costs, and (3) the potential value and the problems associated with the provision of grid stability services. This study has resulted in a simulation model and decision software, which can also be used and further extended for additional experimental studies into microgrids and flexibility services.