Reducing Weighted Average Cost Of Generation In Pakistan Through Time Of Use (Tou) Pricing Models Of Flexible Electric Loads

Theme/Relevant Ministry:

M/o Power; NEPRA; Alternate Energy Development Board; NTDC; DISCOs

Project Brief:

Pakistan has faced under and over supply of electricity over the past decades. Historically Pakistan has faced a shortfall of upto 7000 MW but at present the country has 12000 MW of excess capacity even after meeting the peak summer demand. The undersupply curtailed the GDP growth and is a major cause of industrial slow down, but the present oversupply is constantly causing an incremental rise in electricity prices and circular debt. Intelligent management of electricity demand may help reduce electricity prices and may also curtail the circular debt accumulation.

Demand Side Management (DSM) techniques allow intelligent management of electricity load where electricity distribution companies provide various financial incentives to shift demand from peak to off-peak times to reduce the Weighted Average Cost of Generation (WACG). In this report we present a DSM tool that performs in-depth data analytics to assess the impact of demand shifts at hourly basis. Using authentic and verified data from the power sector the tool provides impact of demand shifts on WACG. The tool encodes not only the tariffs of all generating units operating of Pakistan but also considers other financial conditions including mandatory capacity and energy payments from IPP agreements in calculating its results. The tool also incorporates the technical parameters of all generating units to create a digital twin of the generation sector. Moreover, the tool also calculates the impact on environment through operating various sets of generation units.

Public Policy Relevance:

In the last few years, Pakistan has surplus generation capacity. This surplus generation capacity has resulted in an accumulation of a large circular debt and a huge sum of capacity payments is paid to compensate the surplus generation capacity. This study examines the development of a dynamic artificial intelligence (AI) based Time-of-Use (ToU) pricing tool for off-peak utilization of generation capacity. The study seeks to develop the ToU pricing mechanism for various categories of flexible load. Through the ToU pricing mechanism lower tariff rates can be charged to the end-users without compromising the revenue of the utility companies and other power sector entities.


Final Research Report, Policy Brief and Journal article can be downloaded from the link:


CGP 01-055
Naveed Arshad
Associate Professor, LUMS Lahore (PI)
12 months
Rs. 3,939,758