Clean Energy Capability Portfolio | Grid Transformation |
Virtual Power Plants Based on Energy
Storage Systems
The coordination of a large number of energy storage systems ( ESS ) can be simplified by dynamically clustering them into virtual power plants ( VPPs ). This creates an integrated network that functions as a unified and flexible power plant , which offers several benefits . Managing variability and intermittency associated with individual systems becomes easier through VPPs . By combining the capacities of multiple ESS , VPPs can optimise energy usage , reduce peak demand and facilitate a more resilient and reliable grid . The primary technical challenge involves harmonising different types and capacities of ESS , while addressing the unique behaviours of individual customers . It requires monitoring the continual connections and disconnections of ESS , as well as potential changes in the power network . |
Competitive Advantage • Expertise in developing distributed multi-agent control strategies for ESS and their aggregation into virtual power plants based on operating requirements and energy storage properties
Impact • VPPs can reduce network costs by improving the utilisation of the network asset , and providing opportunities through technical innovation , for peerto-peer trading in the future
• VPPs can help reduce the roadblock associated with limited hosting capacities on feeders
Successful Applications • Development of algorithms for online peer-to-peer based distributed aggregation of ESS into virtual power plants , thereby improving the utilisation of available energy storage capacity and reducing grid power losses
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Capabilities and Facilities Real-Time Digital Simulators that facilitate :
• Real-time verification of algorithms and simulation of power networks combined with accurate models of energy storage systems and power converters
• Hardware-in-the-loop simulation ( the final step before field verification ) that presents an opportunity for rapid research , development and verification – this is necessary for translating theoretical advances in multi-agent cooperative control and aggregation algorithms into new strategies suitable for deployment in power system networks
More Information Dr Branislav Hredzak
School of Electrical Engineering and Telecommunications
T : + 61 2 9385 4895
E : b . hredzak @ unsw . edu . au
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