Abstract:
This paper details the design and application of the Power Purchase Price (PPP) forecasting model which aims at improving the predictability of tariffs and lessening the impact of Fuel Cost Adjustment (FCA) fluctuation in Pakistan electricity sector. The growth in the cost of power purchasing, lack of regularity in the tariff adjustments, and the constant mounting consumer challenge coupled with external shocks like depreciation of the currency, changes in fuel prices, the variability in hydrology and the rising circular debt all point to the extreme need of a data-driven forecasting projection. In the analysis of the future PPP values, employing the historical PPP records, scenario modelling, sensitivity analysis and performance variance analysis, the study develops a multi-layered analytical model, which is able to project faithfully the future PPP values and correlate them with the NEPRA tariff requirements. Close correlation between the values projected and actual PPP was observed because of pilot testing during selected months, and this creates high reliability and low variance. Sector-wide issues of operation, such as the weaknesses of governance, slowing of tariff determination, reliance on fuel, high T and D losses, ineffective recovery of costs, and inconsistency of regulatory data, are also measured in the study. To address these concerns a holistic improvement plan was created, including privatization models, internal process restructuring, integration of advanced analytics, automation of activities digitally, and cross-institutional synergy between CPPA-G, DISCOs, ISMO, and NEPRA. Liquidity, profitability, asset efficiency, leverage, and the ratio of returns can be improved in the financial and statistical analysis, which indicates that the planning enhancement through the PPP can be used to significantly increase financial sustainability. The paper finds that when institutionalized and constantly improved, PPP forecasting can provide a revolutionary mechanism to stabilize tariffs, decrease FCA burdens, and improve sector transparency and reduce the circular growth of debt, which, in the end, will increase consumer confidence and economic stability. This framework offers a viable way of achieving efficiency in long-term planning and financial recovery to policymakers, regulators and utility managers.
