Power sector according to the regulator | Political Economy

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He has released its half -annual report, which has denying responsibility for any mistakes, released his half -annual report with notes, which means, which means, should be charged with distribution and breeding companies, which provides most of it. Although there are a lot of data and one can begin to look at the samples in it, withdrawal damages the reputation of the report and can be confident in any result.

Some mistakes are absolute. For example, in some examples, the number of faulty meters is below zero. How is this possible? Nevertheless, the report documents documents where some disco report a negative number for defective meters at the end of the month and a positive number at the beginning of the month. The irregularities are for Sipco for five out of six months reported. Either the data recording is a mistake or an attempt to misrepresent.

There are contradictions in data reporting in different sections. For example, the number of ‘lost’ units or accumulated taxes varies slightly in many tables. Pandit malfunction of defective meters does not often increase. This raises doubts not only on operational performance but also on maintenance data as used units are not similar to bills.

Failure is clear in Iesco, Lesco, FESCO, GEPCO and PESCO. These contradictions, seemingly minor, complicates the understanding of data and eliminates confidence in the overall accuracy of the report.

A fair and sustainable water policy should be built on environmental facts, not on imaginary concepts. It should respect historical rights, empower all provinces and guide through a comprehensive federal mechanism like the Commonwealth Council.

Recovery ratio and contradictions in revenue data further clarify these issues. For example, Hesco’s data includes billing and collection – July 2024 tables and recovery – tariff vice consumers, sales units, revenue bills and various data per unit table and different data from the table. Similarly, PESCO’s data has contradictions in various tables and contradictions in units.

All effective rates rely on these figures. Why is it that variations need to be thoroughly evaluated to ensure accuracy? In addition, the applicable tariff under Hesco and SAPCO compared to the rest of the disco. It seems that both Sipco and Hesco consumers enjoy a low tax rate. This can explain their extraordinary high (over 100 %) recovery rates.

Consumer complaints documents are another interesting area. Some disco, especially in the GEPCO, had the performance of complaints that it resolved more complaints more during July -September. This shows that it had either an important AA’s back blog from which it goes through or that the data is misleading.

There are many examples where data is required by a regulatory body provided by the regulatory body but no one has been included. For example, the proportion of Lesco’s restoration is 108 %, with tariff Rs 41. Fisco, with low tariffs, however, the rehabilitation ratio has been published 99 %. The report’s analysis of transmission and sending losses often fails to explain the basic reasons.

Recovery proportion can be misleading due to disconnection and lack of transparency. The clear improvement in recovery rates can reflect accounting adjustments rather than sustainable improvement in oppression tools (for example, aggressive disconnection policies) or collection strategies.

This report faces widespread procedure weaknesses that limit its effectiveness as a diagnostic tool. Putting the contradictions in the data aside, the performance reports highlighted the disco’s stand that has faced a new set of challenges for the past few years – changing the largest energy consumption samples.

Due to the recent rapid solarization, fewer consumers rely fully on the grid for their power needs. This is reflected in the entire country with the low use of plants. Economic and industrial development has also suppressed the demand. As a result, the use factor does not lag back two -thirds in any type of generation. During the summer months (July to September), the average factor was less than 50. Under use results in high costs of consumers because they have to bear a high portion of the fixed costs regardless of use.

The author is a senior economic representative in this news, can be reached @Jabwadar