09.07.10Peter Noland, Consulting Partner, Artois-Bell

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There appears now to be almost universal concurrence on a future where distributed generation (DG) assets including solar PV, solar thermal, fuel cells and other forms of on-site power generation produce clean, reliable & economic energy for thousands of commercial, industrial and residential end-users.

However, while this future "Microgrid" evolves, there is an existing distributed energy marketplace that is alive and well today, which primarily uses clean natural gas as the fuel source. A great opportunity exists to realize more effective asset utilization and more economic operation of the existing generators already installed in the market. This can be done via improved integration of operational, market and price data into the decision making process on operating these assets.

The Economic model of DG operates under the simple principle that in order to be profitable the cost of input materials (natural gas), plus the cost of operation, must be lower than the sale price of the final power product ("the spark spread"). Many operators aren't now making informed spark spread decisions because they have no insight or transparency into the most critical cost component of operating these assets, that being the fuel source (highly volatile natural gas pricing). Similarly, in Time of Use (TOU) pricing environments that are now proliferating with the deployment of smart metering, many operators are equally challenged in accessing the corresponding power market or tariff information needed at different points in the day to thoroughly evaluate the spark spread decision.

The result is that many operators of small-scale power systems are "flying blind" when making decisions on when to run the units. Natural gas prices have gyrated wildly over the last few years ($4-13 MMBtu) with changes in market prices of 25-40% over a period of a couple weeks happening numerous times in that period. Generators with no transparency to the market are frequently unaware of, and often miss the magnitude of, weekly or monthly changes in gas market prices. Thus they make un-informed decisions on utilization of the assets.

Conversely, operators often must consider the impact on generator economics when electric tariff pricing (on-peak, off-peak, part-peak, etc) changes throughout the day. Utilities often adjust these tariffs more frequently than customers realize, and the inclusion of new Critical Peak Pricing and Demand Response incentive programs, only heightens the complexity (and the opportunity) of the spark spread decision.

The net result is that the existing market for small-scale natural gas fired DG is not realizing its fullest potential.

• Many customers are reluctant to make long term commitments to Power Purchase Agreements (PPA's) by cogeneration/CHP vendors with PPA rates tied to movements in NG prices.
• Many existing customers and operators are not realizing the full economic benefit, and in many cases are probably losing money, because they are letting generator assets run when its' not economical , or are turn them off at the wrong points in time.
• Executives at many companies which have installed cogeneration/CHP systems are frustrated because they are unsure of the economic impact of wild swings in natural gas prices. Therefore many units have been idled, with the result being that a good number of existing installed assets are not realizing full value.
• Finally, a number of project financing deals that should be done aren't happening because the accurate forecasting, and on-going verification, of the spark spread economics that is required can't be done clearly enough to meet the financier's satisfaction.

There is a lot of opportunity to make this installed base of Natural Gas fired generation assets "smarter", by giving operators more transparent access to market data along while simultaneously providing visibility to electric tariffs and real-time pricing when operating these units. By doing so, these customers will be able to:

• Make more informed decisions on when to run and when to not-run these units.
• Make more informed decisions on natural gas forecasting, purchasing and hedging strategies.
• Improve forecasting on other DG operating costs such as O&M charges, where the service providers' O&M contract is typically tied to number of hours these units are run.
• Generate a host of information that management is desiring for other reasons; such as providing more accurate reporting on asset utilization and providing a clearer picture of the economics and ROI of an expensive asset already invested in.
• Provide more timely and accurate emissions & carbon forecasting and reporting data for import into GHG and carbon accounting systems.

Additionally, as the market price for carbon becomes clearer, future carbon market pricing data will also be fed into the data management equation here; for simultaneous consideration with existing gas market pricing, electricity tariffs and all other generator operating costs. This will thus provide a more comprehensive and truly holistic view of generator economics.

It's important to note here too that essentially all other types of distributed generation and on-site power systems (solar PV, fuel cells, waste to energy) , will benefit from data solutions that provide clear and immediate access to generator input costs along with simultaneous access to market, tariff and operational data sources.

In the meantime, there are a lot of natural gas fired generating assets that we can today reap much more efficiency from, simply by taking advantage of data and information technologies that are available to us now.

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Reader's Comments

Date

Comment

Len Gould 9.15.10

Excellent. And we are only a short time from the point where residential micro-CHP will need these data as well. I would also argue that the public data systems which make available in useful format to everyone a transparent a) electricity wholesale (selling) and b) electricity retail (purchasing) price and c) natural gas wholesale price, should also make avaialble d) potable water price (how soon until options become available and a market develops?) and e) gasoline and diesel prices (eg. the prices from all retail fuel pumps within a set radius of the location (eg. for intelligent decisions regarding charging PHEV's and perhaps on re-selling to the electric peak market from grid-wise PHEV's) and f) decently reliable weather forcast data. Clearly no single supplier should be doing this (not the electric or gas utilities) but a single "market manager" public entity whose assignment is simply to gather and make publicly available the bids and asks from all participants, from the large natural gas storage and distribution companies to the multitude of competing home micro-CHP units and grid-wise PHEV's. This is what IMEUC is all about. With an adequate regional "market manager" managing provision of the data items a) to f) and capturing and storing accurately the required transaction data for final settlement, we'd have a revolutionary system.

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