Long Term Energy Pricing in the Competitive Market Era

May 12, 2011, VANCOUVER, B.C., Canada -

Developing a long term energy price forecast in the competitive market era is a major challenge facing all participants in the energy market. In the 80’s and then the 90’s gas and electric markets respectively migrated from regulated to competitive market paradigms. In the case of electricity, the transition to a competitive model applied uniformly across North America, is far from complete. The need for price forecasts to support trade and system planning remains paramount, despite the difficulty associated with limited price history, semi-liquid markets and a patchwork of competitive market environments.

The electricity market has undergone extensive, fundamental change over the past decade. Deregulation was introduced in hopes of allowing price signals to efficiently guide investment and the operational decisions of market participants. However, the regulatory shift in market paradigm brought with it some serious growing pains; not the least being the Western energy crisis of 2000-2001, a period characterized by obscene price spikes, scandal, market manipulation, and litigation. From these lessons new understanding, definition and expectation of competitive markets emerged. New market rules and structures are still being widely debated, tested and developed, but it now looks as though stable, competitive, and efficient markets may be possible, based on the new definitions of regulated deregulated markets.

Can the Developing Market Cope With the Credit Crunch?

In the immediate aftermath of the energy crisis, there was a concentration of trade in short-term bilateral contracts. As the market stabilized, emphasis on short-term trading was realized to be inefficient and risky, especially with the diminished potential for quick profits in comparison with the early days of deregulation. Now, with many channels in place to manage and trade risk, long-term trading is again seen as viable and necessary. As is typical of efficient markets, spot market activity will largely be relegated to balancing obligations and ancillary services provision related to physical delivery; as opposed to primarily speculative trading.

Challenges in Long-Term Planning

Despite the substantial changes the electricity markets have undergone in the past decade, many of the fundamental challenges that faced the industry before deregulation still prevail. What is radically different is the immense complexity that defines the supply and demand relationship through time. Despite this complexity, high price volatility makes the need for future planning acute; and effective planning still requires proper tools to manage data, analyze data, and internalize available market intelligence so as to develop reliable forward energy price forecasts for guiding corporate decisions. What is very different is the vastness of data that is now required, and the disposition of the more linear relationships that used to define many long-term forecasting activities. Important to defining long term pricing and trends, is the need to understand seasonality, fuel price correlations, historic and implied volatilities, spark spreads, basis differentials and other market indicators.

How Does ZE Deal with the Challenges

The bottom’s up generation modeling approach was suitable in a simpler market era without RTOs, ISOs, exchanges and a host of other mechanisms for price discovery and competitive trade in physical and financial energy markets. Complex market relationships that can not be modeled deterministically require a top-down probabilistic approach to modeling: top down, to clarify the big picture, simplify the analysis and allow for the overriding business economic factors that define generation development cycles; and probabilistic, to simulate the volatility of the numerous interconnected variables that define energy price behavior. However, a probabilistic approach is not viable without manageable access to the massive amounts of relevant data. In order to manage this data challenge, ZE has developed automated processes to gather and unify the data.

Identifying, Sourcing and Organizing Market Data

The first challenge in any type of forward view or forecasting activity is obtaining the right data, from reliable sources, in a timely, coordinated manner. Effective data collection requires an understanding of the fundamental and technical drivers underlying market indicators, as well as a knowledge of the ways in which these indicators are expressed and quantified, so that they can be organized in meaningful ways (e.g. uniform formats with aligned time scales). Market operators in competitive markets provide a lot of necessary electricity price and transmission data, although acquiring and interpreting the data can be tough. Data is also available from private exchange markets, bilateral markets and a host of basic physical and environmental trading platforms. The data sets required for proper analysis are unique to each region; come in various time granularities, down to the minute, and in various reporting formats. ZE’s development of the ZEMA application provided a way to automate collection and harmonize the data.

Looking at the Big Picture

Although the most obvious approach to price forecasting is utilization of econometric techniques, ZEPG does not believe in its usefulness without developing an understanding of the big picture. This “big picture” understanding includes analysis of regulatory environment and market structure, legislative and regulatory initiatives, major industry news, and changes in market participants’ strategy and behavior. Other components of the big picture that have to be analyzed are: transmission connections, inter-ties, and congestions; fuel supply infrastructure, e.g. pipelines for natural gas, railroads and drivers for coal. Furthermore, long-term projections require good understanding of technological trends in power generation. One of the most recent and the most important factors that will affect electricity prices in the future is the control of emissions: emission caps and trading, emission prices, renewable portfolio standards, etc. These are but a few of the many factors that should be clearly understood, have their relative importance, today and in the future, carefully weighted and their mutual influences should be comprehended before application of econometric, forecasting, and probabilistic techniques.

Analysis and Modeling

Performing analytics and market modeling are complex tasks that require constant adjustment as market and economic conditions evolve. Historic trends and patterns are easily skewed in the short-term by anomalies in weather, generation, or fuel supply, as well as other factors. In the long-term, regulatory developments, business cycle factors, and infrastructure projects will play larger roles in defining the market outlook. Additionally, as electricity pricing is often tied to underlying fuel markets which have their own volatility and drivers, the relative pricing relationships between energy commodities will be in a constant state of flux. ZE uses probabilistic approaches to model such volatilities and understands that it is often more critical to establish the price trend, as opposed to the absolute price at any particular point in time. The top down approach developed by ZE over the past twelve years, has allowed the consistent prediction of trend reversals. Effective physical portfolio and financial risk management can be achieved on the basis of iterative price trend analysis.

Expert Judgment

Even with the automated processes, and probabilistic approaches, long-term forecasting is more than a simple number crunching, modeling exercise. Only after technical rigor and expert judgment have been applied can results be considered indicative of reasonable expectations for the future. The successful top down approach depends on market expertise to simplify market relationships and interpret trends / behavior. Application of even well developed and understood mathematical methods and models requires at some points selection of various approaches, options, and parameters, requiring real market insight. Knowledge of regulatory processes and expertise in utility operations, are key to understanding how and why industry participants will respond to market events. Companies need to rely on people who have “been there” and “done that”.

Resulting ZEPG Long-term Price Forecast

The top-down integrated approach utilized by ZEPG is more reliable than complicated mathematical methods, econometric techniques, or probabilistic simulations by themselves. Expert judgment guarantees application of the most appropriate methods and techniques, selection of which may change several times over time span of the forecast as various “big picture” factors become more or less important. Expert judgment and analysts’ industry experience also guarantees quality control of intermediate and final results, raising alarm flags any time when complex calculations provide counter-intuitive values. ZEPG’s view is that the most important results of long-term forecasts are identification of price trend reversals and measurement of price uncertainty. ZEPG forecasting approach is developed and implemented accordingly to deal with this new paradigm.

How We Can Help

ZE PowerGroup develops Long Term Price Views for markets Across North America. ZEPG’s Long-Term Energy Market Price View Report is a comprehensive document that discusses methodology, research, analysis, and forecast results.

Primary Deliverables

The examples above do not require minute-to-minute real-time estimations of volatility; nor do they require detailed understanding of complex theories and manipulations with strange-looking mathematics. Still, one really does need to have a good feeling for the current market volatility levels, volatility trends, the mean-reversion and resistance levels and the seasonal pattern of volatility. Volatility needs to be observed over time to develop a good understanding of its behavior; the principal issues are:

Supplementary Deliverables

Analysis of:

Format of Deliverables

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