Resilience Oriented Planning of Urban Multi-Energy Systems With Generalized Energy Storage Sources

TLDR

Urban power outages from extreme natural disasters have exposed the inadequacy of traditional reliability‑focused planning, underscoring the need for resilience‑oriented approaches that leverage multi‑energy systems’ ability to shift energy across sectors, use diverse storage resources, and exploit thermal inertia. This study proposes a resilience‑oriented planning method to determine the optimal configuration of distribution‑level multi‑energy systems for urban energy supply, accounting for supply, network, and demand impacts. The method models supply‑side energy shifting, pipe‑network storage, and demand‑side thermal inertia within a unified linear energy‑hub framework, incorporating centralized and distributed storage, pipe network storage, and building heat capacity as generalized storage to enable efficient MES configuration planning.

Abstract

In the last decade, a number of severe urban power outages have been caused by extreme natural disasters, e.g., hurricanes, snowstorms and earthquakes, which highlights the need for rethinking current planning principles of urban energy systems and expanding the classical reliability-oriented view. In addition to being reliable to low-impact and high-probability outages, power system should also have high level of resilience to withstand high-impact and low-probability (HILP) events. Compared with power system, multi-energy systems (MESs) have advantages in improving resilience through energy shifting across multiple energy sectors, a variety of generalized energy storage resources and thermal inertia of heat/cooling loads. This paper proposes a resilience-oriented planning method to determine optimal configuration of distribution level MES, e.g., urban energy supply systems, considering comprehensive impacts from supply, network and demand sides in MES. Impacts of energy shifting at supply side, pipe storage at network side and thermal inertia at demand side are described in the same linear modeling framework using energy hub (EH) model. Generalized energy storage resources including centralized and distributed energy storage devices, pipe network storage and building heat capacity are all modeled into centralized energy storage to facilitate an efficient configuration planning of MES.