IMPLEMENTATION OF COST –EFFECTIVE MEASUREMENT AND VERIFICATION PROCESS IN DSM LOAD MANAGEMENT PROJECTS IN MINING SECTOR GS Donev, OD Dintchev Tshwane University of Technology ABSTRACT The purpose of this paper is to demonstrate how a Was the Project successful? cost effective M&V process could use all available Did the energy bill go down? DSM project resources to verify an energy saving Did the Project perform as specified? project’s power and energy impacts. Did the guaranteed savings actually occur? How much has been saved and are the A case study is presented for a large mine load savings being sustained? shifting project, where a cost effective and accurate M&V process was developed and For all these question Measurement and Verification implemented. (M&V) is the language and discipline that can provide the answers. 1. BACKGROUND M&V is a way of addressing both the engineering and legal issues so that the stakeholders can mutually The lack of generation capacity created an electrical agree on the results of energy investments. energy crisis in meeting the ever growing electricity demand in South Africa. The reduction of the energy Usually the stakeholders fail to agree on the simple demand and peak load is one of the main ways to keep question: “What makes M&V so difficult?” the electrical supply uninterruptible. The answer is that: ‘Things CHANGE’. The mining industry offers excellent opportunities to reduce the peak demand of the country. The dynamics in DSM projects make it difficult and certainly not preferable to assign any one of the stakeholders to deliver an objective assessment of the 2. MEASUREMENT AND VERIFICATION savings. (M&V) OF DSM PROJECTS There is a critical problem for those whose 2.1 DSM PROJECT STAKEHOLDERS AND responsibility is to quantify the energy savings as STAGES opposed to energy delivered: Savings cannot be measured directly. The DSM project usually follows the process as shown in Figure 1. Proper M&V processes are crucial for the success of any DSM load management and energy efficient project. However, the cost of M&V might reduce the amount of savings resulted from the DSM projects. Thus, a proper and cost-effective M&V process is needed to identify and quantify the savings that result from the DSM projects. 3. CASE STUDY 3.1. PROBLEM STATEMENT The case study is illustrating the implementation of Figure 1: DSM Project Stakeholders and Stages cost –effective measurement and verification process in a DSM project in the mining sector. 2.2 PERFORMANCE MONITORING OF According to ‘M&V Guidelines for Pump Scheduling DSM PROJECTS Projects in the Mining Industry’ , M&V has the function of quantifying and verifying the impacts of For any DSM project the following questions are the above projects. The process is structured in a relevant: staged approach with a number of deliverable outputs that are circulated between the project stakeholders. To surface filter plant The major steps are to develop the baseline and the Pumps 16.3MW 2-5 level performance assessment as well the savings Pumps 3 17 calculations. MW level Pumps 3 MW Pumps 8 23-60 Periodical recalculations are also done for these steps MW level to ensure that the baseline cater for the changing 31 pumping activities on the mine. level Pumps 15 MW 32 Due to the scale and complexity of the project, the level M&V option SA-B (direct measurement of the Pumps 8 39 required parameters) is adopted as recommended by Water storage dams MW level ‘The M&V Guideline for DSM Projects’ , since it offers the highest possible accuracy for the M&V Figure 2: Simplified pumping reticulation diagram process. The mine’s simplified underground pumping layout is shown on Figure 2. This process requires independent power measurements for the pumps involved, as well as independent communication network that is using A neural network expert system with learning optic fibre double armoured cables all the way to the capabilities is used to optimize, control and sustain last level at Main Shaft of the mine. Multiple cores savings. The total load shift target is 6.45 MW. The should also be used for purposes of optimal reliability project’s cost is R 10 612 748 and the rand cost per and elimination of loss of communications down kW is R 1645. stream. This is approximately 6000 meters of optic fibre installed underground. 3.3 THE PROPOSED SOLUTION The cost implication of such kind of communication network and the significant number of individual The M&V team used low-cost logging equipment to power meters / analyzers can be economically verify the working schedule of the pumping load and unacceptable. also the accuracy of the metering installed by the ESCO. 3.2 THE PROJECT’S BACKGROUND 3.4 BASELINE METERING The project that has been identified for the cost- effective measurement and verification The baseline metering is organized and performed as implementation is targeting maximum demand control follows: through pumping load shifting in a large gold mine in The metering in the project is done using 41 ‘PM 171’ South Africa. The load shift savings are achieved by Energy Meters with data logging capabilities, shifting the peak pumping load, half to off - peak and installed to each pump individually. the other half to standard time of use. This will result in savings of approximately R 2.285 million annually. The meters are using dedicated software for The forty one shifted pumping loads in question are programming and retrieving the logged data. The located on four different underground levels: software is provided by the supplier of the meters. The measuring period for establishing the baseline is for one month – between 1.04.2006 and 30.04.2006. • 1800 kW at 2-5 level The meters / data loggers are permanently installed on • 1800 kW at 23-60 level the pumps concerned, performing the baseline and the • 1500 kW at 32 level post implementation measurements. • 1350 kW at 39 level The metering interval is a standard half hour one as normally used for energy saving projects. 3.5 INDEPENDENT METERING VERIFICATION The independent control measurements for the duration of the baseline determination period are performed on each pump, using 41 HOBO H06-004- 02 motor ‘on-off’ data loggers. The loggers are programmed and downloaded using dedicated The above co-efficient shows a close correlation software ‘Boxcar BCP 4.3-DL’. Since the loggers between the shapes of the curves. only record the ‘on-off’ state of the motors, the ‘on’ state was considered to be the motors rating as it was It is important to point out that the power assigned to audited earlier, using installed motor protection the HOBO curve is the sum of the pumps’ nominal relays/meters and the amp-meters installed for each power ratings, which may differ from the actual pump. power drawn by the pumps as it is registered by the PM 171 meters. The data were downloaded manually since the communications underground would be extremely To illustrate the trend of power vs. time, fourth order costly. The data from the loggers was compared to the polynomials were fitted to both sets of data as data recorded by the installed PM 171 meters and it It is shown on Figure 4. was established very close co-relation between the two sets of data. The performance tracking of the Independent verification project was done on monthly basis in accordance with kW Trendline 4th order the M&V Guidelines. 35000 30000 25000 The differences in the values for the recorded active 20000 power can be explained with some differences in the 15000 loading of the pumps throughout their hours of 10000 5000 operation. 0 time 00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 It is clear that the data obtained by the PM 171 power PM171 HOBO hobo trendline PM171 trendline meter/data logger is more accurate and the baseline th will be built using it after verifying the operation Figure 4: 4 Order Polynomial trend-lines of HOBO hours of the pumps by the HOBO loggers. and PM 171 data sets A comparison of the two sets of data is given on The modelling polynomials are: Figure 3. Y1 = -0.0846X14 + 9.0271X13 - 318.2X12 + 4017.7X1 + 15700 (HOBO) Independent verification kW 35000 Y2 = -0.0868X24 + 9.1958X23 - 318.62X22 + 30000 25000 3903.1X2+ 14143 (PM171) 20000 15000 The deviation between the two trend-line curves can 10000 be evaluated throughout the day. 5000 0 time It is of a particular interest during the evening peak ( 18:00 till 20:00 ), where it is: 00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 Phobo − PPM 171 PM171 HOBO Figure 3: Verification of the Measured Data for an ΔP = .100 = 5.9% Average Weekday PPM 171 The correlation between the two sets of data from the The post-implementation data is based on PM 171 and HOBO loggers can be compared using measurements between 18.02.2007 and 21.03 2007 the correlation co-efficient as follows: and can be considered a representative set of data that was gathered for more than a month and reflects a cov( x1 , x2 ) time slot outside the holidays season. ρ= = 0.97 σx1 .σx2 The metering for the post implementation stage does not differ from the baseline metering and uses the where: same types and numbers of data loggers on the same locations. ρ – correlation co-efficient The proposed measurement and verification method is cov(x1,x2) – co-variance of the two independent equally applicable for the baseline development and variables from the two sets of measurement post-implementation verification. σx1, σx2 – standard deviations for these variables 4. CONCLUSIONS E-mail addresses: firstname.lastname@example.org or email@example.com Based on the independent verification of the M&V results and their interpretation, the methodology used Presenter: This paper will be presented by by the M&V team proved to be successful. The G.S.Donev. evaluation showed acceptable correlation both in the time and power [kW] as it is shown above. The usage of low-cost, ‘on-off’, field detecting data loggers allowed the M&V process to be performed at relatively low-cost. The methodology used by the M&V team allow to use the metering equipment installed by the ESCO for the needs of the client as part of the DSM project. Thus, considerable expenses and time were avoided without compromising the independent measurement and verification process. 5. REFERENCES  M&V Guidelines for Pump Scheduling Projects in the Mining Industry, Prof LJ Grobler and Dr W.L.R den Heijer, School for Mechanical and Materials Engineering, North-West University.  The M&V Guideline for DSM Projects’, ESKOM CTAD ,2008  CMVP International Performance Measurement & Verification Protocol Volume 1 DOE/GO-10202002-1554  www.eskom.co.za 6. AUTORS Principal author: G.S. Donev is a Senior lecturer at the Department of Electrical Engineering of the Tshwane University of Technology. His fields of expertise and interests are Renewable Energies, Energy Management, Energy Efficiency, Measurement & Verification, E-mail addresses: firstname.lastname@example.org or email@example.com Co-author: O.D. Dintchev is a professor at the Department of Electrical Engineering of the Tshwane University of Technology. His fields of expertise and interests are Renewable Energies, Sustainable Energy Management, Energy efficiency, Measurement & Verification, Rural Development Projects based on application of sustainable energy sources.