Further Optimized Scheduling of Micro Grids via Dispatching Virtual Electricity Storage Offered by Deferrable Power-Driven Demands

Hoach The Nguyen, Ameena Saad Al-Sumaiti, Konstantin Turitsyn, Qifeng Li, Mohamed Shawky El Moursi

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

Deferrable power-driven demands such as water and thermal ones possess a capability of energy storage which can be exploited to further optimize electric systems. This paper proposes a new optimized scheduling framework for electric grids by simultaneously exploiting the high-inertia thermal dynamics and lossless water storage. Unlike previous ideas in the literature, both water and thermal demands are managed to realize the long-term and short-term load-shifting strategies, respectively. First, distributed water/thermal loads are aggregated where the virtual storage can be represented by battery models. Then, a further optimized scheduling framework is proposed with a mixed-integer nonlinear programing problem. Comparative studies show that the water storage offers outstanding flexibility for electric system via pumps scheduling, especially for the electric load-shifting strategy in a long time-horizon thanks to the lossless water-storage process. Meanwhile, the thermal storage can directly support short-term electric load-shifting to avoid price spikes of electricity. Numerical results show that the proposed method can reduce the total cost of micro-grids by maximizing the usage of renewable energy sources, avoiding price spikes, and reducing dependence on high-cost centralized energy-storage facilities provided that the critical water-energy demands are preserved.

Original languageBritish English
Article number9026960
Pages (from-to)3494-3505
Number of pages12
JournalIEEE Transactions on Power Systems
Volume35
Issue number5
DOIs
StatePublished - Sep 2020

Keywords

  • Aggregator
  • demand response
  • distributed storage
  • generalized battery model
  • optimal power flow
  • water distribution network

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