Power Industry Services and Solutions
Power Market Forecasting
Forecasting wholesale power market prices requires an in-depth understanding of the drivers behind today’s market prices, and how the markets will change based on future regulations, investment decisions, and availability of natural resources. Anchor Power Solutions’ EnCompass simulation model, with the National Database, is able to produce accurate price forecasts under expected conditions and multiple future scenarios.
Economic Transmission Analysis
Transmission companies are required to participate in a regional planning process that considers alternative projects from independent developers on equal footing. Anchor Power Solutions’ EnCompass software enables economic transmission analysis by performing a security-constrained unit commitment (SCUC) and economic dispatch (SCED) using a detailed DC powerflow including N-1 contingency constraints.
Integrated Resource Planning
We help electric utilities face the complexity in power supply planning, as well as balancing requirements for reliability and environmental compliance in the most cost-effective manner. EnCompass determines not only the best way to utilize resources, but also which technologies should be added in the future, or existing resources that should be converted or retired.
Valuation and Risk Assessment
Projecting future operations and cash flows of either a single power project or a portfolio of energy assets requires a detailed commitment and dispatch optimization model to capture all operating constraints. Valuations produced by Anchor Power can be used for project finance, tax assessments, budgeting, rate cases, and developing hedging strategies.
Power Market Forecasting
Forecasting wholesale power market prices requires an in-depth understanding of the drivers behind today’s market prices, and how the markets will change based on future regulations, investment decisions, and availability of natural resources. Anchor Power Solutions’ EnCompass simulation model with the National Database is able to produce accurate price forecasts under expected conditions and multiple future scenarios. Price forecasts can include detailed energy and ancillary service components for mid-term (1 month to 3 years) trading and budgeting purposes, as well as long-term energy and capacity forecasts (out to 30 years) to support capital investment decisions.
EnCompass can forecast hourly day-ahead energy prices and sub-hourly real-time prices.
Regional ancillary service requirements are co-optimized along with area load to ensure enough resources are available for uncertain events. Contingency reserves may be set with both a spinning (responsive) and a non-spinning (supplemental) component. Regulation reserves are defined with up and down requirements, and resources that provide regulation may be restricted to be dispatched within a given capacity range. Reserve regions may overlap so that subareas must maintain a minimum level of reserves in addition to market-wide requirements, or they may span multiple balancing authorities to provide reserve sharing. EnCompass has the ability to dynamically adjust energy and ancillary bids to account for start-up and no-load costs, and minimize the amount of uplift that would be needed to make generators whole.
EnCompass can also forecast annual capacity prices using the same type of methodology used in PJM and New York, including downward-sloping demand curves.
New capital projects and resources eligible for retirement will submit capacity bids to recover fixed operating and capital carrying costs, less any profits from the energy and ancillary service markets. If no capacity market is modeled, or if there are still unrecovered costs, EnCompass dynamically adjusts energy and ancillary service bids, similar to the scarcity pricing mechanism used in ERCOT. Each balancing authority modeled may have a reserve margin requirement set which is satisfied based on the firm capacity of existing resources and new capital projects. In addition to the normal zonal transmission constraints, each zone may have net capacity import and/or export limits set. This could potentially force capacity to be shifted into transmission-constrained regions, similar to the New York ISO Local Capacity Requirement (LCR) and the PJM Locational Deliverability Area (LDA).
Robust Dataset for the Wholesale Power Market
One of the biggest challenges in forecasting long-term market prices is developing a robust dataset for the wholesale power market. Horizons Energy, an Anchor Power Solutions affiliate, developed and provides a comprehensive EnCompass database for North American power markets. The National Database (NDB) includes all market data needed for performing a wide range of studies, including: market price forecasting, portfolio/asset valuation, resource planning and scenario/stochastic analysis.
Horizons Energy has benchmarked the 76 distinct zonal areas included in NDB, representing hourly demand and over 13,000 generation resources. The NDB contains individual market rules and zonal transmission costs/limits. Underlying technology-specific detail includes multiple block offer curves, start costs, minimum up/down time for thermal resources, hourly representation of wind and solar resources, pondage-based hydro, and interruptible demand. The database also includes Horizon Energy’s 30-year forward views of fuel markets, environmental compliance and new resource economics.
Synapse Energy Economics utilized Anchor Power Solutions’ EnCompass software to perform several market studies and resource planning projects on behalf of their clients:
- The state policy impacts on New England’s natural gas use from the power sector though 2040 used EnCompass to model multiple emission limits and renewable energy standards: New England’s Shrinking Need for Natural Gas
- The Massachusetts renewable portfolio standard (RPS) applied EnCompass to model different future scenarios: Analysis of Massachusetts Renewable Portfolio Standard
- A pathway for 100 percent renewable energy in Los Angeles by 2030 used EnCompass to model the entire Western Interconnection: Clean Energy for Los Angeles
Economic Transmission Analysis
With the Federal Energy Regulatory Commission’s Order 1000 rule, transmission companies are required to participate in a regional planning process that considers alternative projects from independent developers on an equal footing. For utilities within a transmission planning region, understanding and validating the cost allocation of these new transmission projects is an important but complicated task.
EnCompass enables economic transmission analysis by performing a security-constrained unit commitment (SCUC) and economic dispatch (SCED) using a detailed DC powerflow including N-1 contingency constraints. As part of a nodal simulation, EnCompass calculates the locational marginal price (LMP) for each node in the network. LMP reports show the statistics for average, on-peak, off-peak, minimum, and maximum LMP, as well as the congestion components from each binding transmission constraint.
EnCompass includes all of the necessary transmission detail to effectively combine generation and transmission planning, and evaluation of portfolios in nodal markets.
Transmission lines can be modeled with planned outages as well as unplanned forced outages. Powerflow control devices such as phase-shifting transformers and DC ties can be used to manage congestion. Summary reports display the total congestion value of binding constraints to help identify transmission projects with economic value. A complete nodal dataset is available for ERCOT and WECC, including all detailed transmission elements with selected contingency constraints. In the coming months, additional nodal datasets will be developed for the Eastern Interconnection.
Integrated Resource Planning
Electric utilities are faced with increasing complexity in power supply planning, balancing requirements for reliability and environmental compliance in the most cost-effective manner. EnCompass can be used to develop a resource plan that considers all potential options including: central station construction, purchased power agreements, renewable energy, bulk storage, new transmission projects, energy efficiency programs, and demand response. EnCompass can determine not only the best way to utilize resources, but also which technologies should be added in the future, or existing resources that should be converted or retired.
This is accomplished through Capital Projects, which specify not only the operating life and constraints for adding new resources, but also the capital expenditures and project financing parameters, which includes assumptions on debt, taxes, return on equity, property taxes, insurance, and unregulated vs. rate base financing.
The selection of new capital projects and existing resource conversions and retirements is optimized using Mixed Integer Programming. The optimization may span multiple years or be broken up into yearly overlapping segments. And multiple least-cost plans, each one unique up to a specified year within the simulation period, may be generated, ranked, and selected for further analysis. Using the structured scenario approach in EnCompass, the results from a capital project optimization may be used in multiple child scenarios, where a more detailed simulation with the new capacity mix can be evaluated.
EnCompass has the most complete set of functions for modeling complex environmental programs, such as the Clean Power Plan and overlapping renewable portfolio standards.
Resources can be part of any number of programs, which may be annual or seasonal mass-based emission allowance programs, rate-based emission programs with subcategories and generation-shifting incentives for natural gas combined cycle units, or generation-based renewable energy credits. Rate-based emission programs may also include designated renewable and energy efficiency resources, which will produce emission rate credits that can be sold to fossil fuel generators.
Price forecasts for these allowances and credits may be directly input into EnCompass, or annual program limits can be enforced which will also produce allowance or credit prices. Each program may also include a bank, which allows for over-compliance in early years to offset tighter limits in later years. A penalty price for exceeding annual limits acts as a reliability safety valve, so that allowances or credits can be borrowed from future years under extreme conditions.
By combining the program limits with capital project optimization, EnCompass determines the best combination of new unit additions, retrofits, and retirements to meet a complex array of environmental regulations.
Arizona Electric Power Cooperative, Inc. (“AEPCO”) filed its resource plan with the Arizona Corporation Commission under docket E-000000V-15-0094. For its analysis, AEPCO used EnCompass, “which analyzes hundreds of resource combinations in order to recommend lowest-cost resource portfolios that satisfy the peak demand obligations of the Cooperative load. By varying the assumed futures AEPCO and its Members may face, this tool assists AEPCO and its Members in making decisions aimed at low-cost, low-risk, reliable power supply for Cooperative customers.” AEPCO considered six different scenarios, three of which included the Clean Power Plan beginning in 2023. Two scenarios assumed Arizona would adopt a single rate-based plan with emission rate credits, and the third assumed a subcategory rate plan, with lower targets for combined cycle units and higher targets for all other affected fossil units.
Valuation & Risk Assessment
Projecting future operations and financial metrics of either a single power project or a portfolio of energy assets requires a detailed commitment and dispatch optimization model to capture all operating constraints. Optimal decision making requires not only forecasting expected future market conditions, but assessing the risk associated with uncertain and volatile market drivers. Valuations produced using EnCompass can be used for project finance, tax assessments, budgeting, rate cases, and developing hedging strategies.
EnCompass is capable of performing a full optimization of all resources, subject to a complete set of operating costs and constraints. By utilizing Mixed Integer Programming, the software determines the best combination of resources to commit and the appropriate dispatch levels for each interval of the operating day. In addition to minimum uptime and downtime requirements, EnCompass can also cap the number of starts and shutdowns, and recognize costs and fuel requirements for hot, warm, and cold starts and shutdowns.
Heat rates and dispatch costs are set for the minimum (no-load) operating level, as well as any number of blocks up to maximum capacity. Any number of fuels may be defined for a resource, and EnCompass will utilize the least-cost fuel, subject to minimum and maximum limits. Dependency constraints and waste heat recovery allow combined cycle resources to be modeled as complete configurations or as individual components. Resources may be assigned to multiple environmental programs, which may include mass-based emission allowances, rate-based emission rate credits, or renewable energy credits.
EnCompass will also co-optimize limited energy resources such as hydro, storage, and demand response with load shifting or “bounce back.” Intermittent renewable resources such as wind and solar may be modeled with daily profile shapes down to the 1-minute level. Combined with the ramp rate restrictions on dispatchable resources, EnCompass provides all of the necessary features to quantify the impacts of renewable and storage integration at the sub-hourly level.
Planned maintenance for resources may be entered with historical or planned dates that repeat in the future every 12 or 18 months, for example. Each potential outage may also have an allowable shift, which allows EnCompass to determine the optimal timing of planned outages within a region. Unplanned outages can then be randomly determined for each resource based on input forced outage rates and lengths. The structured scenarios within EnCompass make it easy to use the same outage schedule from a long-term parent scenario to multiple child scenarios.
EnCompass employs advanced risk modeling that can be applied to any time series value, including but not limited to commodity prices, interest rates, production costs, demand, and renewable generation. One of the primary options is a two-factor mean-reverting model, with short-term market volatility that tends toward a long-term fundamental outlook, which can also be uncertain. Probably distributions can be lognormal, suitable for prices which are positive and skewed higher, as well as normal or uniform. Historical distributions that draw from actual conditions that occurred in the past may be used for weather-related variables such as demand and renewable generation. Correlation can also be defined among time series to represent the inter-dependence on market drivers.
EnCompass uses Monte Carlo sampling to assess market and portfolio impacts due to uncertainty. This sampling can be completely random, or utilize Latin Hypercube Sampling, which takes points equally across a distribution and requires fewer draws for convergence. The Position report displays a complete picture of all possible outcomes and calculates and displays relevant statistics including mean, deviation, confidence intervals, and correlation factors. Scatter plots and box-and-whiskers charts provide a visual indication of relationships and distributions. Financial contracts such as fuel cost hedges can be added after simulations to assess the impacts on expected values and volatility.
The Hawaii Division of Consumer Advocacy (“CA”) filed testimony and exhibits with the Hawaii Public Utilities Commission as a party to Hawaii Electric Light Company’s (“HELCO”) rate case under docket 2015-0170 and Hawaiian Electric Company’s (“HECO”) rate case under docket 2016-0328. The CA’s consultants, Sawvel and Associates, used EnCompass to review HELCO’s 2016 test year and HECO’s 2017 test year analyses and recommend changes to those results. Sawvel considered detailed operational constraints including regulation up and down requirements, dual-train combined cycle modeling, daily start limits, minimum local generation to prevent transmission overloading, commitment operating constraints, and minimum fuel burn requirements.