A Multi Criteria Decision Making electrical load restoration framework that prioritizes and restores distribution-level loads during high-impact, low-frequency (HILF) events by combining expert weighting, TOPSIS (multi-criteria ranking), and a MILP that co-optimizes network-feasible restoration and unserved energy costs.
1) Motivation
Extreme events (weather, supply disruptions, partial network failures) force temporary resource inadequacy. Not all loads are equal in social consequence, technical criticality, or economic value. This project creates a transparent, auditable process that (i) scores and ranks facilities/loads across social–technical–economic criteria and (ii) commits restoration actions that respect power-flow, feeder limits, DER availability, and time constraints.
3) Method at a glance
Stage 1 — Criteria & data. Define criteria across four lenses: Criticality, Social, Technical, Economic (e.g., life safety, vulnerable populations, backup capability, feeder location, VoLL/CSI, service time limits).
Stage 2 — Expert-informed weights (AHP). Build a pairwise matrix; derive normalized principal eigenvector and consistency ratio.
Stage 3 — Non-critical ranking (TOPSIS). Create a decision matrix; compute weighted normalized scores; derive closeness to ideal best/worst to rank loads.
Stage 4 — Operations (MILP). Embed priority scores as penalty weights; co-optimize load restoration, DER dispatch, and switching subject to network and timing constraints.
Sangar Shanthanam 
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