ADVANCED INTEGRATED PLANNING THE DER DRIVEN TRANSFORMATION IMPERATIVE SEPA GRID EVOLUTION SUMMIT JULY 27, 2017
Erik Gilbert
[email protected] 1
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OUR VIEW ON THE INDUSTRY TRANSFORMATION THE ENERGY CLOUD1
TODAY: TRADITIONAL POWER GRID Central, One-Way Power System
EMERGING: THE ENERGY CLOUD Distributed, Two-Way Power Flows
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Navigating the Energy Transformation: Building a Competitive Advantage for Energy Cloud 2.0 (white paper) / ©2017 NAVIGANT CONSULTING, INC. ALL RIGHTS RESERVED
(Source: Navigant Consulting)
PUBLIC UTILITIES FORTNIGHTLY: STATE & FUTURE OF THE POWER INDUSTRY Survey of 400+ key industry professionals – July, 2017 “Which one of the following trends is the most disruptive to traditional utility business models over the next decade?” • Nearly half of the respondents cite increased penetration of DER as the most disruptive threat to traditional utility business models over the coming decade. • The effects of DER are industry-wide and will have a deep impact on the existing market. • DER was by far the dominant trend cited among respondents, with all other trends receiving only a small fraction of votes.
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DISTRIBIUTED ENERGY RESOURCES (DER): WHAT’S INCLUDED?
Distributed Generation
Demand Response
Distributed Storage
Energy Efficiency
Microgrids
Electric Vehicles
Resources can be utility, customer, or 3rd party owned on the grid in front of the meter or customer owned behind the meter. 4
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DER IN THE UNITED STATES WE FORECAST STRONG DER PENETRATION GROWTH OVER THE NEXT DECADE
Annual Installed DER Power Capacity Additions by DER Technology, United States: 2015-2024 Distributed Generation Distributed Energy Storage Microgrids Electric Vehicle Charging Load Demand Response Energy Efficiency
70,000
60,000
(MW)
50,000
40,000
30,000
20,000
10,000
2015
2016
2017
2018
2019
2020
(Source: Navigant Research)
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2021
2022
2023
2024
Observations • DER deployments will reach ~30 GW this year in the US, versus new central station generation (19.7GW) • On a 5-year basis (2015-2019), DER in the US is growing almost 3 times faster than central generation (168 GW vs. 57 GW).
EXAMPLE CHALLENGE: LOAD FORECASTING TRADITIONAL TECHNIQUES SHOWING SIGNS OF AGE •
“Past performance is no guarantee of future results” -
DERs are less predictable (both in installed capacity, and daily performance) Weather patterns seem to be breaking from long term trends Customer behavior (in some cases) is evolving New types of load not predicted or well understood yet (e.g., EVs, grow-ops)
•
Geo-special granularity now required
•
Recent system-wide forecasting misses—a few examples: -
•
Implications: -
•
Large Eastern utility misses spring/winter forecast: points to unusual weather Southern utility misses annual forecast significantly: reasons under review Mid-sized Northern IOU misses peak forecast on high-side for several years running: weather? Mid-Atlantic utility load forecast used to justify construction of large generating station: actual loads falling far short (economic downturn played a clear role here, and no-one predicted it, to be fair)
Under- or over- investment Investment/upgrades in wrong or too many locations revenue shortfalls
And there are challenges beyond forecasting…
Note: the availability of advanced modeling techniques and cost-effective big data computing power are no longer impediments to conducting advanced analytics & load forecasting with these data
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PLANNING MUST BE MORE AUTOMATED AS WELL AS INTEGRATED = ADVANCED INTEGRATED PLANNING Traditional Planning: • Largely internal to utility • Some coordination between planning functions • Stakeholder process engaged at the end of the cycle
Advanced Integrated Planning: • Integrated internal functions, as well as stakeholder process • “Optimization” of investment across customer, distribution, transmission, generation • Uncertainty and risk analysis fundamentally integrated Customer adoption scenarios: load and DER forecasts at zone/feeder level
Distribution planning
Load forecasting
Stakeholder processes Integrated Resource Planning
Regulators, City Council, etc.
Transmission planning
2-3 year planning cycle 7
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Revise programs and adjust strategies based on results and market feedback
Program and DER procurement priorities and grid investment
Stakeholder and regulatory input and adjustment
Sub-year iterations
Integrated customer, distribution, transmission and resource analysis
Strategic grid and resource investment and risk assessment
ADVANCED INTEGRATED PLANNING: HIGH LEVEL ANALYTICAL FRAMEWORK External Market:
Evolving technology and vendor landscape, new service providers, etc.
Internal Operations:
People and processes within utility planning functions
Visualization and Planning Management Layer
Internal Systems Context: OT/IT production
5. Coordination, Analysis and Integration (coordinated data flows with integrated benefit-cost and reliability analysis)
systems
1. Advanced Load and DER Forecasting (with integrated customer program / resource scenarios)
Add: Load profile management (daily, hourly); geospecial granularity
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DER Scenarios
Analysis coordination, automation and data flow control
Add: Cross Team and cross analysis coordination
Automation and Coordination
Wholesale Values of Capacity/Energy
Dynamic, standardized data exchange Impact of DER Installations Add: dynamic analysis (transient impacts)
2. Distribution Planning & Analysis
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Geo-special scenario data
Aggregate Load/DER
4. Integrated Resource Planning (IRP)
Add: system stability analysis: voltage oscillation risk
3. Transmission Planning & Analysis
Add: Criteria— Reliability Economic Environmental Risk/Uncertainty
ADVANCED INTEGRATED PLANNING: CAN START WITH EXISTING TOOL SETS
Visualization and Planning Management Layer
Broad array of commercial tools in use today
1. Advanced Load and DER Forecasting
• • • • • • • • • 9
Excel R dB/SQL SAS Analytica TROVE IA Energia Others evolving
5. Coordination, Analysis and Integration
• CYMDist (steady state & dynamic) • Synergi • Milsoft • DEW • GridLabD • PSSE: Network models needed to assess advanced concepts (e.g. networked systems)
2. Distribution Planning & Analysis
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• Python (Pandas, Django, d3.js, crossfilter.js, dc.js, leaflet.js) • HTML5
• Python Scripting • GRID+ (Benefit/Cost Analysis, Risk Assessment)
• Siemens PTI - PSSE, Python, MUST • Power world • GE - PLSF • Power Gem - TARA • Matlab • EMTP • PSCAD • Gridview
3. Transmission Planning & Analysis
4. Integrated Resource Planning (IRP) • • • • •
Promod Plexos Aurora Strategist POM
ANALYSIS OF CIRCUIT UPGRADE COSTS TO MEET DER PENETRATION LEVELS High-Level approach: • Analyze dynamic performance of distribution feeder for high penetration DER
System Upgrade Cost ($000)
Objectives: • Apply predictive modeling on representative distribution feeders to assess PQ impacts from variable renewable output • Assess the capability of advanced inverter functionality to mitigate PQ impacts
Standard Inverters $6,000
$5,000 $4,000
$3,000 $2,000 $1,000 $0%
50%
100%
DER Penetration (% of Feeder Thermal Rating)
= violation
Advanced Inverters $6,000 $5,000 $4,000
$3,000 $2,000 $1,000 $0%
50%
100%
DER Penetration (% of Feeder Thermal Rating)
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INVESTMENT OPTIMIZATION - ANALYSIS EXAMPLE OF GRID+ TOOL OUTPUTS
The net present value of deployed distribution grid capabilities is $3.2B Annual benefits and costs of investments (nominal $B)
Net present value of investments (2016 $B) 1.0
$3.2B
2.0
0.6
$B (nominal)
3.0
$B (present value)
Environmental Reliability Economic Costs
0.8
4.0
$1.5B
1.0
0.4 0.2 0.0 -0.2
0.0
-0.4 -1.0 -2.0 2005
-0.6 2005 2010
2015
2020
2025
2030
2035
2040
-4
-2
Scenario
Best
Expected
Worst
6.0
NPV ($B)
5.0
3.2
1.0
4.0
The best and worst case represent the 95th and 5th percentile outcomes, respectively.
0
2 4 $B (present value)
6
8
2020
2025
2030
2035
2040
2045
Distribution of costs and benefits across the value chain (2016 $B)
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$B (present value)
Likelihood of Occurrence -6
2015
2045
Uncertainty analysis for net present value (2016 $B)
Approximately 3% chance of negative NPV
2010
Environmental Reliability Economic Cost
2.0 0.0 -2.0 -4.0 -6.0
Generation
Transmission
Distribution
Customers
TO MEET THE IMPERATIVE… • Convene a cross-functional team charged with planning in a high-DER environment: -
examine how existing planning tool sets are used, and whether they can meet the more dynamic needs of high DER planning - understand the gaps, and what external tools are available and appropriate - Develop internal tools to coordinate across external planning tools processes
• Develop DER adoption scenarios that will impact the business - Develop corresponding load forecasts using newer, advanced techniques (bottom-up, data rich)
• Perform planning analyses for relevant parts of value chain (e.g. customer programs, distribution, transmission) • Optimize across potential investment and program areas • Iterate quickly, as situation on the ground and external market forces evolve
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