TECHNICAL AND NON-TECHNICAL LOSS ANALYSIS IN PAKISTANI DISTRIBUTION COMPANIES (DISCOS): CAUSES, ECONOMIC IMPACT AND MITIGATION STRATEGIES

Abstract

Pakistan’s power sector faces a perpetual socio-economic crisis characterized by escalating circular debt, highly volatile operational inefficiencies and large-scale financial imbalances. At the heart of this structural collapse lie severe transmission and distribution (T&D) losses within the Power Distribution Companies (DISCOs). This comprehensive research paper provides an extensive diagnostic evaluation of Technical Losses (TL) and Non-Technical Losses (NTL) across six prominent DISCOs: IESCO, LESCO, K-Electric, PESCO, HESCO and SEPCO. Technical losses, originating from line resistance, aging transformers, overloaded feeders and unoptimized high-voltage transmission layouts, are systematically distinguished from non-technical losses, which comprise direct power theft via illegal hooking (kundas), advanced meter tampering, systemic billing inaccuracies and abysmal revenue collection efficiencies. Utilizing multi-year empirical datasets spanning from 2018 to 2025 derived from the National Electric Power Regulatory Authority (NEPRA), the Ministry of Energy and individual corporate distribution audits, this study conducts statistical trend mapping, comparative performance evaluation and rigorous economic impact analysis. The empirical evidence reveals a dramatic polarization: while IESCO and LESCO demonstrate robust operational performance with T&D losses stabilizing near NEPRA-allowed limits (8.2% and 11.4% respectively), peripheral DISCOs such as PESCO, HESCO and SEPCO suffer from catastrophic, unmitigated losses exceeding 37%, driven primarily by pervasive commercial theft and deeply institutionalized billing recovery inefficiencies. Economically, these losses directly exacerbate the national circular debt—which has reached an alarming PKR 2.48 trillion by fiscal year 2025—choking public liquidity and severely constraining macroeconomic growth. To reverse this structural hemorrhage, this study proposes a comprehensive, multi-layered technological framework anchored on Advanced Metering Infrastructure (AMI), automated distribution transformer energy balancing, artificial intelligence-driven data mining for predictive fraud detection and robust legal-institutional reforms. This integrated blueprint offers a realistic path toward financial stability, system reliability and sustainable energy governance within Pakistan's power network