[BETA] Fortnightly

Customers in some markets are demanding the right to opt out of smart meter deployments. Their concerns involve radio frequency (RF) emissions and potential privacy breaches. Whether these concerns are valid or not, some regulators are requiring options for customers who don’t want smart meters. The right approach can satisfy concerns without undue costs and complexities.

When customers sell demand response into a regional capacity market (such as PJM’s Reliability Pricing Model, known as the RPM), how much credit should they earn for agreeing to curtail demand and alleviating stress on the grid — that is, for reducing the market’s need for generating capability and capacity reserve margin? And further, should the amount of credit depend on whether the customer works with market aggregators, known both as CSPs (“Curtailment Service Providers”) or ARCs (“Aggregators of Retail Customers”)? One view would pay customers for the full extent of their curtailment of demand — known as its “Guaranteed Load Drop” (GLD). The other would limit capacity credit to the customer’s prior load history — “Peak Load Contribution,” or PLC. The answer may well dictate whether regulators continue to treat “energy” and “capacity” as two distinct concepts.

(April 2011) GE Hitachi and Lockheed Martin team up on nuclear reactor controls; Elster wins metering contract in New Hampshire; Xcel hires Bechtel for nuclear services in Minnesota; Mitsubishi builds transformer HQ in Memphis; Northeast Utilities taps Siemens for transmission projects; Iberdrola sells wind output to FirstEnergy; Consumers and DTE invest $400 million to upgrade pumped storage facility; plus contracts and announcements from Alstom, URS, Areva, groSolar, Pattern Energy, S&C Electric and others.

Former Pres. Bill Clinton and other dignitaries help Duke, Cisco and Charlotte, N.C., launch commercial efficiency initiative; AEP signs 20-year MOU to buy solar output from New Harvest plant; Wartsila expands gas-fired generator in Turkey; U.S. DOE awards geothermal RD&D grants; GE acquires Dresser for $3 billion, and also acquires Calnetix industrial cogen technology; SunEdison sells 70 MW Rovigo PV plant; Ford Motor Co.

A fierce debate has erupted in the utility policy community, with battle lines drawn within FERC itself. In the effort to improve system efficiency, two competing alternatives stand out: to build the smart grid on large-scale demand response (DR) programs, or to build it around consumer behavior in retail markets.

Demand response isn’t energy: It’s a separate product, traded in a separate market. Policy trends, however, are moving toward equal treatment for demand and supply resources in electricity markets. Does treating DR as energy inflate its value and create perverse incentives?

Generation

FEI Company, a diversified scientific instruments company providing electron and ion-beam microscopes and tools for nanoscale applications, completed a multiple system installation at the Materials Ageing Institute (MAI) in France, a utility-oriented research center financed by Electricite de France, the Tokyo Electric Power Co., the Kansai Electric Power Co. and the U.S. Electric Power Research Institute.

Six months back, when ISO New England was mulling over various reforms that FERC had mandated last fall in Order 719 for the nation’s six regional transmission organizations and independent system operators (RTOs and ISOs are interchangeable terms in this column), the ISO refused point blank to include in its mission statement a proposal by stakeholders that it should operate the bulk power system at the “lowest reasonable cost.”

About four months ago, at a conference at Stanford University’s Center for International Development, the economist and utility industry expert Frank Wolak turned heads with a not-so-new but very outrageous idea.

Price forecasting is a significant business process within any energy merchant that trades electricity and natural gas. Business planning, trading, mergers and acquisitions (M&A), even rate-case activities rely upon some type of a price forecast as the foundation to analysis.

The problem with a single forecast is that it never is correct. As soon as the forecast is complete, the world changes and the information becomes dated and often even irrelevant.