Alberta Electric Energy 2006 Market Study

Transcription

1 Alberta Electric Energy 2006 Market Study Getting Load to Say No EDC Associates Ltd. Annual Study

2 Introduction 1 Introduction CHAPTER KEY 1. Introduction 2. Executive Summary 3. Macro Economics 4. Electric Load Forecasts 5. Direct Load Control 6. Supply Resource Development 7. Electricity Price Forecasts 8. Appendices This report constitutes the ninth annual up-date to the original study issued in This series of reports has helped keep readers up to date with the ever changing Alberta electricity market fundamentals, regulatory events and policy changes. This report also extends beyond the Alberta jurisdictional boundary by analyzing key geo-political and international economic events that may also influence the Alberta electricity market. Following more than two years of new transmission policy development (TDP) and wholesale market review, the Alberta electric industry is again set to re-vector its course through the murky waters of competition. In November 2006, the AESO issued a revised draft of the Long Term Adequacy paper. This document reconfirmed the general reluctance to employ out-of-market solutions, especially capacity markets, to manage long term adequacy concerns. At least for the moment, new generation capacity will continue to be developed on the volition of suppliers, based on their unique decision making criteria and view of market conditions albeit under the ever watchful eye of the provincial policy makers. In very dire circumstances, where a breach of a proposed set of adequacy metrics indicated some intervention was to be reluctantly administered, a set of so-called Threshold Actions would be applied, but only in a manner that preserved a strong scarcity pricing signal. A list of Quick Hits developed by much the same group is also awaiting implementation, with the intent of further enhancing price fidelity. These Quick Hits will allow reconstitution of price for Transmission Must Run (TMR) generation and similarly allow imports to once again set price. As a natural consequence of the 2003 Transmission Development Policy, the 20- year hiatus on backbone transmission construction will soon end. The AESO has disclosed its latest plans for large upgrades in all four quadrants of the Province. The first of two major N-S lines has received approval at the Needs Application stage making it possible for both lines to be in service by 2010 and 2012 respectively. The other quadrants will also see significant expenditures, with AESO-initiated construction probably topping $1 Billion in the next 5-10 years, essentially doubling the Transmission Rate Base. Except for a recently imposed 900 MW cap on new wind development, this will remove most transmissioninduced impediments to new generation. It should also enhance export capability, Chapter 1 10

3 ushering in an era of strong growth in Alberta s electricity energy export industry. The new TDP also enables merchant transmission capacity, evidenced by the MATL merchant line scheduled to be in service by mid Without transmission as an impediment to generation development and with a renewed commitment to a competitive energy-only market, one additional key element remains to ensure an open market that spontaneously meets both the short and long-term supply adequacy needs of Alberta consumers. This year s study looks into the decision making processes of load, specifically Demand Response, i.e. actually responding to the price signal in the peak hours. What role can load play in ensuring that just enough new generation is built to maximize the value the end-customer receives from the extraordinarily expensive last units of power it demands? What new programs, technology and regulation are achieving success in other jurisdictions? How will these apply or not apply in Alberta? How will these changes affect different classes of customer (residential, commercial and large industrial)? What are the key risks to be evaluated? If viable, what are the next steps to a smooth approval and implementation? This review and analysis will delve into the minds of load to determine how we go about: Getting Load to Say No. This year s annual study, as all those in the past, continues to focus on the long term Alberta electric industry market fundamentals along with other influencing factors. Although the means by which the analysis is completed remains the same, the approach by which the fundamental market data is analyzed this year is different. EDC still deploys a collection of integrated forecasting models to assess future market supply, demand and price dynamics the means. Future market dynamics were previously developed through the use of scenario analysis, using a collection of discrete input assumptions that defined the forecast, which produced a deterministic result last years approach. Over the last year or so, EDC has spent considerable time and effort enhancing the collection of models to incorporate Monte-Carlo techniques to help better assess the potential range of future market supply, demand and price dynamics by describing the various input assumptions as probabilistic ranges rather than discrete events. This year s approach allows the reader to derive his own appropriate confidence interval around the mean value of the outcome and better quantify the risk associated with the forecast result. This contrasts with a deterministic model, where no probability can practically be assigned to different outcomes. This is not to say that deterministic modeling is outdated or incorrect, but simply that stochastic modeling through the use of Monte-Carlo techniques describes the inherent risks more fully. Risk Analysis Methodology The EDC models are now designed to allow rapid and complex sensitivity testing of single or multiple scenarios, in either a deterministic or probabilistic mode. This year s report reflects a progression from previous editions, which had presented two discrete deterministic cases, a High Case and a Low Case. This Chapter 1 11

4 year s report instead presents a probability distribution of forecast pool prices. The pool price distribution is intended to represent the range of future possible outcomes resulting from a range in future electricity supply and demand input assumptions. Typical P10 and P90 bands (a 10% or 90% probability (or confidence interval) that the price will be lower than that value) are shown in the report, but the distribution allows the reader to choose a custom confidence level appropriate to their own application. This stochastic forecast concept is illustrated in Figure 1. Figure 1 Stochastic Forecast Distribution Concept $160 Stochastic Modeling Concept Forecast Distribution $140 Most Likely Price n $120 Pool Price $/MWh $100 $80 $60 $40 History P90 Mean P10 Distribution of Future Possible Outcome $20 $ YEAR In order to quantify the potential range and magnitude of the deviation in the price profile that could result, EDC incorporates several key risk elements into its generation dispatch and energy price forecast model, using typical Monte-Carlo techniques. The model convolutes the various stochastic risk elements collectively, to arrive at a composite price profile. Alternatively, each input can be varied in isolation to assess its importance, or sensitivity, to the overall variability. Variables are categorized as either short-run or long-run. EDC Short-run Risk Variables The short-term risk variables reflect the typical range of demand and supply variance resulting from short-run influences such as weather, intra-month natural gas price volatility and forced outages of generation units and tie-lines. These variables are varied about historical mean values and typically produce a small dispersion of the total price distribution. Chapter 1 12

5 Expanded Long-run Risk Variables As noted above, the EDC models are now designed to assess the impact of significant changes to longer term assumptions which can potentially produce a much more dramatic impact in the future electricity price forecast. EDC has identified five key assumptions that typically represent the most significant amount of risk in any future electricity price forecast: AIES energy and demand growth, generation timing and probability, potential environmental costs, natural gas and other fuel prices, and Mid-C market prices. EDC also makes specific assumptions such as strategic bidding behaviors and planned maintenance scheduling on the supply-side, and demand responsiveness on the load side. Typically, each of these inputs are varied on a mutually exclusive basis, relative to one another and from year to year, but any unique correlation or relationship can also be modeled. Each variable can either be varied from its mean value using a uniform selection criteria applied to a symmetric range of input values or using a non-uniform selection criterion applied to an asymmetrical range of input values. Typically, the variations in the input assumptions are designed to be mean reverting so as not to induce a bias in the forecast directly from a bias in the input assumption. The Monte-Carlo process can be executed for each sensitivity, from a typical minimum of 30 iterations up to 1,000 iterations, largely dependant on the number of years included in the forecast. The following chart illustrates the Monte-Carlo process within the generation dispatch and energy pricing model that produces the final pool price result of the overall forecast process. Figure 2 Typical Risk Analysis Process Flow Diagram Long-term Monte-Carlo Risk Variables Energy Demand (MWh) Supply Additions (MW, Timing) Nat Gas Volatility Unit Availability Weather +/-1% to +/-5% +/-25%, +/-1 Yr Short-term Monte- Carlo Inputs Generation Supply Additions & Other Base Case Assumptions Unit Bidding Behaviors Environmental Costs (On/Off) Generation Dispatch & Energy Pricing Model HELP Natural Gas Price ($/GJ) -$2/ to $6/GJ Outputs Mid-C Import Pricing (Heat Rate GJ/MWh) +/-1.25GJ/MWh Unit MWh s Pool Price Distribution Each key input assumption has its own distribution of values that, when allowed to randomly vary from one iteration (or seed) to the next, produces a unique price Chapter 1 13

6 forecast distribution. Each variable can be varied independently to produce a tornado chart which graphically demonstrates the sensitivity of the price profile to specific changes in each variable. The P10 Case reflects a combination of events from the pessimistic end of each of the each key assumption similar to the old P 10 deterministic forecast. For example, it might reflect a sustained future period of lower economic growth in the US and around the world, and ultimately low economic growth in Alberta, brought on by downward pressure on all commodity prices, particularly the energy commodities, crude oil and natural gas. The Alberta electric energy market might also find itself with a surplus of generation that might be due to an overly aggressive cadre of generation developers who persistently over-build base load generation capacity. The P90 Case reflects the opposite situation, where sustained high electricity prices might result from generation development lagging behind load growth that has been bolstered by strong economic growth in the US and around the world similar to last year s High Case deterministic forecast. The Alberta economy might simultaneously be supported by very robust crude oil and natural gas prices, where the latter has a direct impact on the cost structure of electric energy production particularly at the margin, where the price is influenced by natural gas based generation. The probability distribution presented herein represents a plausible range of future values with an indication of the likelihood of any particular price actually occurring. This gives the reader more information about the riskiness of the forecast than a single, most-likely value. As such, the P10 to P90 range presented in this report reflects the outward bounds of future supply, demand and pricing in the Alberta electricity market at an approximate eighty percent confidence interval. 1 It is expected that any future outcome from one year to the next would not likely be sustainable along either extreme but rather, would tend to oscillate between the extremes, creating typical market cycles. The quantitative results reported in this study are the output of EDC s proprietary long-term integrated electricity models. The integrated model set includes several sub-models that assess Alberta s demographic and economic outlook, oil and gas production and export potential, electricity demand (by sector, utility and transmission point-of-delivery), generation supply, transmission cost and pool price as well as costs for air borne emissions such as Hg, NOx, SOx, Particulate Matter (PM) and CO 2 equivalent albeit no POD forecasts or emissions values are presented in this report. Also new this year, the EDC model has been significantly enhanced to more discretely model the interaction of the Alberta market with its adjacent markets, especially if additional tie capacity is deployed. The Mid-C and BC market models have also been enhanced to more discretely model the supply demand fundamentals for each market that now interact to produce real-time import and export volumes based on specific market participant strategic behaviors or market price differentials. 1 The P10-P90 range of possible outcomes is characterized statistically as being approximately equal to plus or minus 1.3 standard deviations about the mean assuming a normal distribution. Chapter 1 14

7 Feature Chapter: Getting Load to Say No This years report contains 8 chapters: Chapter Two presents an executive summary of the key findings of the analysis and the quantitative results presented in this report. A summary of each chapter s key results is presented. Chapter Three presents an overview of the underlying macro economics and demography in Alberta, including an outlook for the key industry segments including a review of oil and natural gas prices. The development of the probabilistic inputs to the demand forecast starts in this section. These results drive the demand forecast in the next chapter. Chapter Four examines the output of the quantitative electric load growth model with some discussion of the key forces driving the results. Domestic load growth across the key consumer groups residential, commercial and industrial is presented and discussed. A commentary on export opportunities and transmission and distribution losses rounds out the total Alberta electricity requirements for domestic generation and import supply. Chapter Five, this year s feature chapter, examines an emerging technology for encouraging a substantial increase in the demand responsiveness of small and intermediate sized load. This so-called Direct Load Control removes some of the current impediments to a vibrant Demand Response, especially, instantaneous price surveillance, automatic or external curtailing in response to a threshold price signal, and settling bills based on the amount of electricity that is cut back precisely when prices are highest and reliability is in the most jeopardy. The study examines competing technologies, experience in other jurisdictions, expected efficacy for an Alberta system and approval and implementation issues. The range of possible increased demand response is then incorporated probabilistically into the load forecast. Chapter Six discusses the electric energy supply fundamentals. The examination of the future electricity supply starts with an overview of existing generation capacity, cost structure and the expected timing of unit retirements. Future supply options and availability, generation technologies, supply demand balance and reserve margin are then discussed. The chapter also presents a discussion on the key elements that will define the range of future supply additions. The discussion will also address the key drivers that affect the range of generation future costs. Chapter Seven brings together the discussion of supply and demand for the purpose of forecasting the wholesale price of electricity. All of the probabilistic parameters of supply and demand are used in this chapter s analysis to define the distribution of future price forecasts. The quantitative results are presented and discussed noting key assumptions and conclusions. Finally, Chapter Eight contains the appendices of the report, including supplementary charts and tables. Subscribers can obtain this information electronically by contacting EDC. It should also be noted that all financial forecast data is presented throughout this report in nominal terms or Money of the Day, unless otherwise noted. Chapter 1 15

8 Preliminary Table of Contents Introduction Risk Analysis Methodology EDC Short-run Risk Variables Expanded Long-run Risk Variables Executive Summary Macro Economics Electric Load Forecasts Direct Load Control Supply Resource Development Electricity Price Forecasts Forecast Distributions Macro Economics Macroeconomic Input Assumptions US Economy Canadian Economic Outlook Alberta Macroeconomic Outlook Oil and Natural Gas Market Outlook Oil Price Forecasts World Oil Supply and Demand Outlook Alberta Oil Production Natural Gas Price Forecasts US Natural Gas Market Outlook Alberta Natural Gas Outlook Other Natural Gas Market Developments Oil and Natural Gas Price Distributions Large Industrial Project Profile Macro Economic Summary Alberta Electric Load Forecasts Electric Energy & Demand Forecast Alberta Internal Load vs. AIES Demand Energy and Demand Growth Residential Energy Sales Commercial Energy Sales Farm & Irrigation Energy Sales Industrial Load Growth Transmission and Distribution Losses Export Sales Behind the Fence Load Forecast iv

9 Energy and Demand Forecast Summary Direct Load Control- Getting Load to say No What is Direct Load Control? Impediments Removed by Direct Load Control Experience in Other Jurisdictions Potential for DLC in Alberta Complement to Price Cap Incease Implementation Issues Supply Resource Development Current Generation Supply Installed Capacity Forecast Unit Retirements Fuel Supply & Generation Technology Natural Gas-Fired Generation Coal-Fired Generation Hydro Generation Wind Generation Nuclear Generation Biomass Generation Generation Supply Forecasts Project Probabilities Project Timing Future Supply Resources P10 Supply Resource Forecast P90 Supply Resource Forecast Supply Resource Forecast Summary Electricity Price Forecasts Historical Alberta Pool Prices Forecast Assumptions Ancillary Services Assumptions Supply Offer Strategies Scheduled Supply Outages P 90 Forecast Results Energy Production Simulation Results Electricity Price Forecast Results P 10 Forecast Results Energy Production Simulation Results Electricity Price Forecast Results Pool Price Forecast Summary P 90 Forecast Results P 10 Forecast Results Forecast Comparison v

10 Appendices Data Tables Appendix A - Generating Unit Statistics Appendix B - P Appendix C - P vi