Customized Energy Solutions for Meter Data Analytics
- 1. METER DATA ANALYTICS: DERIVING MAXIMUM VALUE FROM METER DATA www.wiproecoenergy.com ANALYZE. ACHIEVE. ACCELERATE
- 2. 2 Table of Contents 03 .................................................................................... Introduction 03 .................................................................................... Benchmarking 04 .................................................................................... Schedule Mismatch 04 .................................................................................... Base Load 05 .................................................................................... Seasonality and Weather Impact 05 .................................................................................... Load Breakup 05 .................................................................................... Analytics & Forecasting 06 .................................................................................... Peak Shaving/Shifting 07 .................................................................................... Contract Demand 06 .................................................................................... Equipment Effeciency 07 .................................................................................... Loss Reduction 07 .................................................................................... Utility Meter Faults & Billing Errors 07 .................................................................................... Billing at multi-tenanted sites 07 .................................................................................... Emissions Reporting 07 .................................................................................... About the Author
- 3. Energy metering and sub-metering is being proposed as a crucial element of energy efficiency at almost every organization. With a maxim of “Measure to save”, over 5 % of energy cost saving is often pegged to granular metering. Presently, the energy consumption is tracked at least once a month at facility level, if not more. This explains the consumption at overall facility level and helps one compare the energy consumption of a facility during same months over the years and tracks any anomalies. Depending on the objective and availability of funds, sub-metering may be considered to provide load-wise energy consumption details. Through advanced meters that are being deployed nowadays, it is additionally possible to get time series data at pre-determined intervals. Over a period of time, these can generate a huge set of valuable data. A successful metering strategy requires more than installing the meters. This article explains how to derive maximum value out of metered data. 3 Introduction ANALYZE. ACHIEVE. ACCELERATE Especially from interval-metering and sub-metering of energy consumption in an organization. Benchmarking: In multi-facility organizations, it becomes imperative for management teams to know how each of the different facilities are performing in terms of energy consumption and how they fare in terms of efficiency. While metered data gives a direct view of energy consumption at each of the facilities, it also acts as the fundamental piece of information in computing appropriate efficiency metrics. Metrics used could be ones like Energy Usage Intensity (EUI) which is kWh per sq.m/sq.ft or Power Usage Effectiveness (PUE) which is Total Facility Energy divided by IT Energy. These kinds of metrics not only enable determining which facility is efficient irrespective of the magnitude of energy consumption, but also helps in comparing with other peers and industry benchmarks. This enables organizations to set efficiency goals and charter a plan for achieving them.
- 4. 4 Base Load: Data collected during off-hour periods indicate the base load of the facility. It is the energy requirement of the facility irrespective of any active operations. Hence this is the minimum energy that is used by the facility and incur at least this much cost. However, the observed base load may not be justified. By understanding the loads that are expected to be operational, the actual energy consumption data could be verified and it may turn out to be more than expected.Any reduction that is subsequently achieved in base load will bring about the most savings for single shift facilities and gradually to a lesser extent for extended hours or multi shift facilities. Schedule Mismatch: Most organizations have schedules of operation that impact energy consumption.They could be based on work hours of employees,varying equipment/business loads in different shifts, off-hours/holiday/weekend schedules etc.Analyzing metered data helps identify compliance to these schedules.Any deviation observed is a potential area for energy savings. For e.g., consider the working hours of a facility to be from 9 am to 6 pm.However,energy consumption data could indicate that 70% to 80% of work hour energy consumption continues on till 8pm which may be unjustifiable.The situation can then be investigated and appropriate corrective action taken. FACILITY EUI (kWh/Sq. Ft./Yr) TYPE ANNUAL ENERGY (kWh) AREA (Sq.Ft.) Site A Site B Site C Site E Site D Office Office Office Office Office 17000 20000 15000 8000 13500 357000 360000 285000 184000 27000 21 18 19 23 20 As can be seen, the highest consuming facility is not necessarily the most inefficient. Fig. 1: Schedule Mismatch 1800 1600 1400 1200 1000 800 600 400 200 0 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 00:00 BaseLoad Off-Hours Off-HoursWork Hours
- 5. 5 ANALYZE. ACHIEVE. ACCELERATE Seasonality and Weather Impact: Energy consumption of facilities could follow a seasonal pattern based either on weather, business cycles or holidays/festival periods. Analyzing data over longer time horizons of at least a year helps in identifying these patterns. And checking if these are in line with known events or cycles could identify energy saving opportunities. Comparison could also be done of cycles across multiple years which could bring out differences in consumption pattern. Investigation into the root-cause of differences would help control energy consumption better. Typical optimizations here relate to thermal insulation of facilities, equipment energy efficiency and controls. Analytics & Forecasting: One of the significant values of having metered data over long periods of time is in enabling prediction of energy consumption. Energy models of building take into account various infrastructure details, geo-specific weather data and other key impacting parameters to forecast energy consumption. The accuracy of prediction improves when historical data is considered, as enabled through metering and monitoring of different key parameters. In day-to-day operations, the Load Break-up: One of the primary reasons and benefits of sub-metering is to gain an insight into load breakup and identify loads that are sub-optimal in energy efficiency. This could either be based on absolute consumption details or in relation to other load values. For e.g., in a Data Center what is the HVAC load with respect to IT load. The load relationship could also be studied for different time periods to understand the way it is changing. For e.g., how is it varying between day and night, work and off day, summer and winter etc. These insights would help justify or improve the energy consumption. 55%32% 5% 8% Fig. 3: Load Distribution Business Load HVAC Lighting Others forecasted consumption can be used as a reference to control energy consumption proactively rather than reactively. Dynamic operating environments can provide energy saving opportunities on a continuous basis. Analytics of metered data on an ongoing basis would enable organizations to leverage maximum potential at the earliest opportunity. For example, they could highlight spikes, anomalies in usage pattern, growth or drop in energy consumption, changes in key impacting parameters etc. 1,800 1,750 1,700 1,650 1,600 1,550 1,500 1,450 1,400 30.00 25.00 20.00 15.00 10.00 Jan Feb Mar Apr JunMay Jul Aug Sep Oct Nov Dec Fig. 2: Seasonal Consumption Pattern Energy Consumption (MWh) Mean Temp (C)
- 6. 6 Equipment Efficiency: With appropriate level of sub-metering it is possible to determine the actual performing efficiency of equipment. This not only tells whether the units are performing at expected levels, but also brings to attention any maintenance needs when it drops unexpectedly. This prevents avoidable losses in terms of energy as well as cost. For e.g., it would be possible to determine the efficiencies of equipment like UPS and CRAC units using sub-metered data. Metrics like EER used for CRAC units would require other associated parameters to be monitored as well. Peak Shaving/Shifting: Metered data can be used to identify usage patterns, sources of energy consumption and classification of peak loads into critical and non-critical. This insight can then be used to determine if any of the peak loads can be shifted to non-peak hours or if non-critical loads be reduced. This helps in decreasing the peak load charges. With increasing demand for energy and supply lagging behind, utility companies face challenge in providing peak demand requirements. While augmenting their peak supply capacities, some utility companies offer demand response programs that incentivize end-users to reduce their demand. Metered data analysis and peak shaving/shifting would also enable one to participate in such demand response programs and claim incentives. Fig. 4: Actual vs. Predicted Consumption 1800 1600 1400 1200 1000 800 600 400 200 0 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 00:00 Predicted Actual Fig. 5a: Pre Peak Load Shaving 1000 900 800 700 600 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Base Load Non-Critical Load Cooling Load Fig. 5b: Post Peak Load Shaving Base Load Non-Critical Load Cooling Load 1000 900 800 700 600 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
- 7. 7 ANALYZE. ACHIEVE. ACCELERATE Contract Demand: It is typical of organizations to forecast their business growth and associated energy requirements while applying for a contract demand from utilities. And the requested demand would be much more than what is required presently. This unutilized capacity comes at additional recurring cost which is justified by many to be worth the hassle/risk of getting additional capacity at short notice. However, it would be a worthwhile exercise to periodically review the predicted business growth and energy requirement. It can so happen that due to business decisions or turbulent market conditions, actual energy requirement will be much below the predicted. Even considering the lead time of procuring additional capacity, such instances can enable releasing of excess capacity and make the exercise cash positive. Metered data provides a strong basis for analyzing the peak demand requirement and the demand growth that has actually been seen over a period of time to make this call. Loss Reduction: Quality of power has a bearing on performance reliability, efficiency and life of equipment. Many meters allow data points to be monitored that enable determination of power quality like Power Factor and Harmonics. Enabling them could highlight problem areas which could then be addressed appropriately to the extent possible. Utility Meter Faults & Billing Errors: The availability of sub-metering on main lines enables one to detect any fault in the main utility meters. Though rare, utility meter fault could go undetected especially if it has been present over a period of Raviraj Kadiyala heads the Energy Management Services practice atWipro EcoEnergy forTelecom,Transportation and Logistics customers. His current work encompasses developing propositions that deliver energy efficiency,reduce energy costs and add value to core business needs of customers through M2M, IoT, analytics, central monitoring and managed services. His experience in the fields of Energy Management and Telecom Networks covers solution architecture, product development, pre-sales, commercials and delivery. He can be reached at raviraj.kadiyala@wipro.com. About the Author time. Installation of sub-meters enables one to detect existing problem as well any new ones that may arise. With granular view into consumption, metered data can be used to compute utility charges independently. This can then be used to verify the correctness of received invoices and reconcile with utility companies. Billing at multi-tenanted sites: In multi-tenanted facilities, contracts could be in place that charge based on occupied area and not necessarily on energy consumption. Metered data can be used by organizations to renegotiate contracts that charge more in line with their actual consumption or restructure them to be charged, based on actuals. Emissions Reporting: One of the big challenges in reporting emissions is collecting reliable data on energy consumption. Metered data monitored through a central system not only enables auditable data, but also dramatically reduces the time required in data collection and report preparation. Metering and monitoring requires investment. And at times, it becomes difficult to justify it. However it has also been seen that at places where investments have already been made, the use of data is restricted only to a limited subset. It is the author’s hope that readers of this article would be able to tap the full value of benefits realizable from their metered data. This article was published in Energyn Manager magazine, Volume 5, Issue 1, Jan-Mar 2012 This paper was also included in the Resource library of Retail Industry Leaders Association
- 8. IND/BRD/AUG 2015–OCT 2016 Wipro EcoEnergy is the energy services business division of Wipro Limited that provides intelligent, sustainable solutions for energy consumption and management. Utilizing leading edge analytical tools we deliver energy-efficient solutions to our clients that help reduce their carbon footprint, energy usage and recover avoidable energy losses. Our Managed Energy Services holistically address the entire spectrum of energy and sustainability, providing sustained energy savings. We have created a strong local ecosystem of partners in North America, Europe and APAC, and have deployed our Energy Management Services for a number of companies around the world. Our clients have realized substantial energy savings and cost reduction during the course of their engagement with us. For more information please visit www.wiproecoenergy.com or write to ecoenergy.info@wipro.com About Wipro EcoEnergy © WIPRO LTD 2015