Load Studies Using AMI Data. Gregory A. Wolven, P.E. Director of Engineering WIN Energy REMC

Transcription

1 Load Studies Using AMI Data Gregory A. Wolven, P.E. Director of Engineering WIN Energy REMC

2 Introduction Most utilities have progressed to the point of implementing wide scale AMI systems. This session will discuss some useful ways to use this AMI information to make your load models more accurate than using the traditional 30 day kwh allocated methods. Hopefully, we can make a use case as well.

3 WIN Energy REMC System Statistics WIN Energy stands for Western INdiana Energy REMC Employees: 53 Miles of distribution line: 2,644 miles Number of Substations: 34 Active Meters: 17,000 Territory: Miles North to South: 91 Miles East to West: 51 Peak NCP KW : 139 MW Jan 2018

4 Where is WIN Energy located?

5 Steps in Leveraging AMI in an EA Model 1. Create, and maintain, a detailed Engineering Analysis (EA) model Validate your impedance values (what is you data source?) The connectivity needs to go to the meter level 2. Obtain a reliable AMI system High interval reliability 15 minute interval on all meters is preferable 3. Have a way to store the AMI data in a format that can be stored and then extracted into the EA model 4. Have a method to validate your load flows Bring back voltages in the same time frame and compare calculated values to metered values on low or no use meters (mitigates issues from transformer voltage drop) SCADA can be used for this, IF you have that.

6 1. Create, and maintain, a detailed EA model The starting point of a good load allocation is a good model. In my mind, the model you need to set as a goal is a detailed model.

7 Stations: 72,916 Miles of line: 2,644 miles Number of Subs: 34 Number of circuits: 74 Number of meters: 17,000 Detailed Model

8 Detailed Model Having a detailed model allows you to apply the metered load at the specific point on the detailed Engineering Analysis (EA) model where the load is located. Start with running circuit diagnostics and clean up all errors found (goal of no errors and no warnings)

9 Detailed Model From what source did you get your impedance data?

10 2. Obtain a reliable AMI system WIN Energy has been involved in AMI, in some form, since In 2015 WIN Energy moved from a PLC system to an RF AMI solution (Landis & Gyr Gridstream RF)

11 AMI Reliability is important Highly reliable readings, give us the confidence to look at multiple goals: PLC did not have the interval capability, or the reliability, for our cooperative s mission Reliable existing EA loading (not projected or calculated) What if? scenarios (emergency and planned work) Different techniques for load growth projections Different rates to encourage load shift

12 Verifying Data As anyone who has done a traditional Construction Work Plan (CWP) can tell you, one of the issues with writing a CWP has been how to verify that the actual loading values are the same values that are calculated in WindMil. Since all of the meters can (depending on the AMI System) bring back voltage as well, verifying your base case model with your Voltage Drop Calculation can be achieved by using actual metering values and comparing to the calculated values at the same physical location.

13 3. Have a way to store the AMI data in a format that can be stored and then applied into the EA model Store all the AMI metrics you can get (Blink count, voltages, currents, kwh, kvarh, ) Bring 15 minute energy values back for a specified period of time. Convert 15 minute energy (kwh) to 15 minute average demand (KW) [kwh ¼ hr = Kw, or kwh x 4] Apply demand multipliers, if any. Suggest we ALWAYS do this, even if value is 1

14 4. Have a method to validate your load flows 1. Bring back voltages in the same time frame and compare calculated values to metered values on low, or no, use meters (cuts out transformer voltage drop) SCADA can be used for this, IF you have that. Review mismatches in the calculations versus metered Resolve and re-run Once these are resolved you have your base case.

15 Pilot Project

16 Test Project Pick a date and time: 2 January January minute Union Substation (4 Sub) 4-1 circuit (#1 ckt out of the 4 Sub)

17 Rural Area Good mix of: Residential Small commercial Single phase Two phase Three phase 155 active accounts 29 multi ph acc One circuit out of Sub 4 Test Project Area

18 The.cld file: Place the values for the specific date and time into a *.cld file Notice that the file requires phased referenced loading: Section Identifier (Map Point Name) kw A,B,C kvar A,B,C Consumers A,B,C (not needed in this case)

19 The.cld file: To start this process, we wrote an export (into Excel) for the date and time, then we wrote a formula to place the values in the correct phasing:

20 The.cld file: The processed file MUST be placed into the following directory (at this time): C:\Milsoft\Database\WindMil LLM E-CMS.wm

21 The.cld file:

22 The.cld file:

23 The.cld file: Hopefully, you get this message.

24 The.cld file: Once the import is complete, check a location and see if the value you wanted was actually placed where you thought it should be.

25 Voltage Drop At this stage, you are ready to run the voltage drop. Once this is run, find a no use active meter, very low use active meter or primary metered account (watch out for p.t. multipliers here). Obtain the actual voltage at that location and compare that value to the calculated voltage at that same location For this experiment, we purposely picked a time that KVAR should not have been a factor. 2 January The first pass did NOT apply kvar even IF it was available. SPOT checking several residential locations with zero, or near zero, usage produced encouraging results. (this was on a 15 minute interval) More Trials are needed!

26 Applying System Improvements Project management Proposed CWP jobs and their effectiveness By using the project management built into WindMil you can look at various scenarios to solve CWP issues more easily. Staged approach to CWP problems, single phase to three phase conversion, load shifting,

27 Applying System Improvements Existing Model Voltage at the end of the circuit is 118

28 Applying System Improvements Set up projects you feel will be the solution set for the particular issue. I only am using one, for clarity, marked by the arrow below. 3ph 1/0 ACSR to 3ph MCM ACSR

29 Applying System Improvements The project area is selected in red in the picture on the right. Notice the change in voltage, 118 to 125.

30 Load Growth Use of Spot loads for load growth Let s face it, uniform load growth is not how a system grows in real life. Using historical growth patterns, instead of uniformly spreading projected growth over the entire substation seems to be a more focused approach. Why spread the growth to ALL accounts on a substation? Finding the areas of past growth, reviewing to see if that makes sense into the future (subdivisions for example), can be a better stressor for the distribution grid.

31 Load GROWTH allocation

32 Use case A CWP is useful, but what if situations happen a lot in a distribution system. With seasoned personnel leaving cooperatives, how do we get the system knowledge in a format that it isn t a guess? (SWAG or WAG) Having an accurate model that reflects the dynamic system, using near real time loading (from AMI), building in a pass or no pass test (voltage, sectionalizing, balance..), should help those personnel stepping up to see what experience felt was important and allow them time to modify the parameters once they see what actions create unacceptable outcomes.

33 WIN Energy distribution lines (1/0 ACSR) supporting the 345KV - April 6, 2016 ( and April and June 2011)

34 Building a business case While engineering reasons are good enough, for most of us, making the business case helps us sell the concept of using AMI for more than just billing to the rest of the management team.

35 Cost of Service Studies Process WIN Energy desires to group meters by Rate Schedule By rate schedule, determine NCP contribution CP contribution On-Peak KWH usage Off-Peak KWH usage Calculate PF, as applicable Calculate the Wholesale Power Cost of each rate class Using the same data, calculate the WIN Energy billing metrics (Retail) Using the above process, WIN Energy should be able to calculate what each rate class contributes to the Wholesale power bill and what each rate class generates in billing. The difference, less power factor and line losses, should be our margins by rate class. WIN Energy is working with Milsoft/NRECA on the DARPA Grid State Project to make this happen (More on this at the Milsoft Real Time Analytics Presentation Thursday at 10am, Stan McHann presenting)

36 Data That Is Actionable Voltage:Over

37 Data That Is Actionable Voltage:Drill Down

38 Concluding Remarks AMI is NOT just for billing! We can use the information provided to do: CWP Real-time analysis of system voltages (have our CWP assumptions been changed due to loading that we did not anticipate?) real-time load flow, what if, scenarios Looking at high and low voltages for system violations, CVR - DVR, peaking and load transfer issues and verification With the connectivity, use blink counts to locate system disturbances BEFORE outages occur. Cost of Service studies

39 Further references ( in date order) United States Rural Electrification Administration. (1963, June). Demand tables. REA Bulletin The A and B factor method of load allocation Kersting, W.H., & Phillips, W.H. (2008, May). Load allocation based upon automatic meter readings doi: /TDC McHann, S.E. (2013). Grid analytics: How much data do you really need? DOI: /REPCCon_ Wolven, G.A. (2016). An integrated approach to electric utility processes. doi: / REPC

40 Questions?

41 Thank you for your time! Gregory A. Wolven, P.E Director of Engineering WIN Energy REMC