Design, Operating Strategies And Potential Of A Biogenic CHP Swarm

Main content

An increasing share of electricity production coming from fluctuating renewable energy sources (e.g. photovoltaic, wind) prompts the need for more flexibility in order to preserve the balance between generation and consumption, which is a fundamental requirement in a power system: indeed, any significant mismatch between energy supply and demand entails unwanted variations in grid frequency that can disrupt system operation and even jeopardize its overall stability, leading to blackouts in the worst case scenario. Decentralised biogenic combined heat and power (CHP) plants could play a significant role in this context, since they are dispatchable, flexible units featuring relatively short ramp-up/down times. They are furthermore based on an environment-friendly technology and are readily available, making them suitable for practical deployment in accordance with the aims of the Energy Strategy 2050.

Outlook

The development of a CHP swarm model based on technological and geographical information enables the assessment of the potential of this concept for selected Swiss regions within a liberalised market environment. A CHP swarm consists of a large number of small, locally placed
units that are collectively operated in a coordinated fashion in order to provide a sizeable amount of controllable power to the grid. To this end suitable CHP technologies must first of all be investigated and optimally selected for the purpose of effective, sustainable operation. Successively, the geographical characteristics of the chosen location must be analysed in order to establish the availability of biomass and biogas fuels, heating requirements and typical weather patterns. The topological features of the local electrical network must also be taken into account in order to develop adequate dispatch algorithms aiming at preserving grid stability. Lastly, the overall scheme must not only be technologically viable but also economically profitable, requiring the simulation of the developed approach over a number of future long-term electricity market and energy policy scenarios.

 
 
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Sat Jun 24 22:50:46 CEST 2017
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