21:35 22 Nov 24
Info Report Check
Submission incomplete:
As per the paragraphs 358, 359 and 360 of VVS for PoA version 2 and the paragraph 22 of AMS-II.C, version 15, the DOE is requested to further substantiate how it has verified the operating hour by providing the information on:
1) How it has verified that each of the CPAs meet the condition that operating hours during the project are equal to the operating hours in the baseline since there was no information on the operating hours in the baseline equipment;
2) How it has verified seasonal variation considering that i) the Verification Report (p 53) states that “Survey was conducted between August 2018 – April 2019 to account for any seasonal variations so that it covers rainy season, winter season and also the summer season”; ii) the spreadsheet shows that most of datapoints are concentrated from November to December for CPA1, from August to September for CPA2, from September to October for CPA3, and from December to January for CPA4; and iii) operating hours during the winter are usually longer than in summer and the resulted values may not be conservative;
3) How it has verified the outliers and the raw data considering that 1) the Verification Report (p 31) states that “While calculating the average value, the CME has not considered the meters which collected data for less than 90 days or the meters which gave abysmally high values”; and 2) the spreadsheet shows some extremely high average values (e.g. 22 hours/day in CPA1 and CPA3) and also for some of days some users in all 4 CPAs claim 24 hours as operating hours, as per “Guidelines for sampling and surveys for CDM project activities and programmes of activities” which requires that “It is vitally important to scrutinize the raw data carefully prior to estimating the mean and checking its reliability, and this can be done using graphical summaries such as histograms, boxplots, and normal probability plots. These plots would show up outliers in the data or any skewness in the distribution of the data. An outlier can be the result of a mistake (wrongly recorded, or wrongly entered onto the computer in which case it can be corrected); or it could be real value - in which case it must be left as it is and included in the analysis”.
4) How it verified the raw data of the time-meters since the spreadsheet shows that approximately 95% of the raw data for average usage hours of CPA1 and CPA3 are exactly the same.
As per the paragraphs 358, 359 and 360 of VVS for PoA version 2 and the paragraph 22 of AMS-II.C, version 15, the DOE is requested to further substantiate how it has verified the operating hour by providing the information on:
1) How it has verified that each of the CPAs meet the condition that operating hours during the project are equal to the operating hours in the baseline since there was no information on the operating hours in the baseline equipment;
2) How it has verified seasonal variation considering that i) the Verification Report (p 53) states that “Survey was conducted between August 2018 – April 2019 to account for any seasonal variations so that it covers rainy season, winter season and also the summer season”; ii) the spreadsheet shows that most of datapoints are concentrated from November to December for CPA1, from August to September for CPA2, from September to October for CPA3, and from December to January for CPA4; and iii) operating hours during the winter are usually longer than in summer and the resulted values may not be conservative;
3) How it has verified the outliers and the raw data considering that 1) the Verification Report (p 31) states that “While calculating the average value, the CME has not considered the meters which collected data for less than 90 days or the meters which gave abysmally high values”; and 2) the spreadsheet shows some extremely high average values (e.g. 22 hours/day in CPA1 and CPA3) and also for some of days some users in all 4 CPAs claim 24 hours as operating hours, as per “Guidelines for sampling and surveys for CDM project activities and programmes of activities” which requires that “It is vitally important to scrutinize the raw data carefully prior to estimating the mean and checking its reliability, and this can be done using graphical summaries such as histograms, boxplots, and normal probability plots. These plots would show up outliers in the data or any skewness in the distribution of the data. An outlier can be the result of a mistake (wrongly recorded, or wrongly entered onto the computer in which case it can be corrected); or it could be real value - in which case it must be left as it is and included in the analysis”.
4) How it verified the raw data of the time-meters since the spreadsheet shows that approximately 95% of the raw data for average usage hours of CPA1 and CPA3 are exactly the same.
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