Risk-averse restoration of coupled power and water systems with small pumped-hydro storage and stochastic rooftop renewables

Yesen Yang, Zhengmao Li, Pradeep V. Mandapaka, Edmond Y.M. Lo*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

42 Citations (Scopus)

Abstract

Modern coupled power and water (CPW) systems exhibit increasing integration and interdependence, which challenges system performance to disasters and makes service restoration complex during post-disruption. Meanwhile, new technologies, such as small pumped-hydro storage (PHS) and rooftop renewables, are being widely installed and further deepen the interdependencies. To capture these features and improve overall performance, this paper proposes a coordinated restoration framework for a CPW system to respond to disruptions. The proposed CPW model comprises physical networks and mechanisms, considering available units, such as water desalination/treatment plants, pump stations and small PHS, in the water system, and rooftop renewables, distributed generators, in power system. The interdependencies are modeled through component-wise connections and consumer behavior, then grouped into three phases: production, distribution, and consumption. Aggregate service loss with respect to different consumer loads and time periods, is chosen as performance metric and to be minimized using network reconfiguration, energy/water dispatching, load curtailment, and operation management of components. A two-stage risk-averse stochastic programming is applied for reliable restoration and manage risks, to tackle the uncertainties in renewable power generations and water/power demands that affect method effectiveness. Finally, the method is implemented on a modified 33-bus/25-node CPW system, and the results demonstrate the effectiveness of the proposed restoration framework.

Original languageEnglish
Article number120953
JournalApplied Energy
Volume339
DOIs
Publication statusPublished - 1 Jun 2023
MoE publication typeA1 Journal article-refereed

Keywords

  • Critical infrastructure
  • Interdependency
  • Optimization model
  • Power-water systems
  • Restoration
  • Risk-averse stochastic programming

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