“DG hurts utilities,” say many electric company engineers, who believe that haphazardly sited engines threaten grid safety; hence, prohibitively high connection charges are imposed. “Distributed generation really helps utilities,” say other, perhaps better-informed voices, including rate-setting commissioners in California and New York in 2004; the DOE; assorted consumer advocacy groups; and, of course, the DG industry.

Whose view is right?

Perhaps a better question is, Which side can back up its claim with compelling, reliable facts? All this time, both have struggled with the complexities of how to quantify potential benefits or harm, yielding solid, credible data. Both sides offer sweeping but “basically unsubstantiated” claims, as Peter Evans, CEO of New Power Technologies (NPT) in Los Altos Hills, CA, observes. NPT develops management solutions for the power industry. Absent from the good-for-grids/bad-for-grids debate were methodologies for serious DG impact studies, resource optimization analysis, and comparative technology assessments. Up until recently, Evans points out, no one had been able to solve puzzles like right-sizing DG resources (from the grid’s standpoint), where resources should go, or what actual dollar value they would bring to the utility company.

All of this has now radically changed. During 2003–2004, NPT led a research team that produced a landmark study in nearby Silicon Valley, showing these critical issues can indeed be addressed reliably—probably for the first time ever. Along with Evans and NPT, 10 other co-participants included Optimal Technologies (USA) Inc. of Benicia, CA, which provided principal optimization technology and services for the study; Cupertino Electric, which assisted in developing the system model; the Silicon Valley Manufacturing Group (SVMG); and consultancies Rita Norton & Associates, William M. Stephenson, and Roy Skinner. Funding for the study, and strong state-level encouragement, came from the Public Interest Energy Research (PIER) program within the California Energy Commission (CEC), which has long been a major sponsor and benefactor of DG-related R&D.

Finally—and perhaps above all—to serve as a test-case system for undertaking this DG-on-grid analysis, Evans and SVMG solicited the participation of Silicon Valley Power (SVP), a modest-sized municipal network of 850 buses serving the city of Santa Clara. SVP’s transmission backbone includes two 115-kV main feeds, a 60-kV transmission system, and 48 or more distribution feeders of 12 kV, lightly loaded off of about 422 customer locations—in sum, notes Evans, nearly 1,000 line segments with 106 switchable branches connecting them; 101 switchable capacitors; and six onsite generators with megawatt and megavar capability already in the mix.

What the Study Found
After several months of studying grid optimization with DG sets, Evans issued his report to the CEC, from which the following summary and discussion is adapted. In essence, researchers learned that, indeed, small generators sited strategically on the distribution system would yield potentially tremendous improvements to system efficiency. Moreover, further gains and benefits would accrue to the interconnected transmission system. DG’s value to both would be realized not only by the additional reserve power provided but, even more so, from DG’s ability to ease power delivery across hundreds of strained, occasionally redundant, energy-sapping distribution lines.

In any grid system, perhaps hundreds and even thousands of kilowatts typically are squandered in the task of moving amps across needlessly long distances. Often, too, this surfeit of travel must squeeze itself through congested local transmission bottlenecks and loop flows; the resulting problems here include weaker voltage profiles, voltage instability, and poor power quality. Properly positioned DG can greatly reduce system congestion and curtail waste of this sort. Potential savings might amount to thousands of dollars daily—a scale of economizing that should readily cost-justify, and subsidize, many cogen investments.

For example, as the report notes: Unstable voltage must often be boosted higher in order to maintain a sufficient minimum; but, if more stable distribution system voltages could be achieved—a potential byproduct of many DG projects—this would reduce the need for this wasteful over-amping.

Moreover, researchers found that system voltage stability is closely linked to optimal distribution of the system’s volt-ampere reactive (VAR) power resources .What impact does DG have here? The question can now be answered using breakthrough software from Optimal Technologies, called AEMPFAST (pronounced aim-fast). Using this tool, Evans’s team evaluated and quantified both active (kilowatt and megawatt) and VAR and megavolt-ampere reactive (MVAR) power flows, and events that could lead to cost-justifiable DG sites. Evans’s conclusion: “There’s a lot more you can do with reactive power, from a distributed generator, toward providing system benefits.”

Sharing the Benefits With Adopters
What this insight also suggests is that a prospective DG adopter whose generator might provide such benefits should probably receive some kind of compensation or inducement. Optimal’s CEO Roland Schoettle suggests that these might come, for example, “through appropriately structured ancillary power markets, where these benefits are quantified and ranked as alternatives.” DG resource optimization on a grid, he adds, “would make certain that all the lowest cost/benefit alternatives would be known and ranked” in utility management decisions—“not just the traditionally obvious ones using standard utility methods.”

Schoettle’s AEMPFAST tool also assessed SVP customer demand-response measures designed for reducing system peak demand. Using detailed AEMPFAST ranking, the study established that demand-response, wherever onsite power is applied, has greater system benefits in certain locations within a distribution system than in others. Hence, the widely asserted “safety risk” to grid security, so often leveled at DG projects, is just the opposite of the truth. Risks are actually lowered by the presence of DG, AEMPFAST revealed. Again, says Evans, utilities “would be acting in their self-interest” by giving out carefully targeted incentives to DG adopters, especially where the result is peak demand reduction.

Other kinds of grid benefits accrue, including, says Evans, “all network-related, -avoided, or -deferred additions,” along with improved supply/demand margins, reduced dependence on electricity spot markets, deferred costs, reduced fuel costs, lowered emissions and related costs, and easier integration of future customer-driven onsite power projects into the grid. Lastly, with customer-owned DG in the right places, low-voltage buses can sometimes be eliminated outright.

All in all, then, grids can be “tuned up” with DG networks and made more efficient, says Evans, “by minimizing real power losses and reactive power consumption.”

To illustrate: On a 60-kV main feeder (such as at SVP), at a transmission-to-distribution step-down point where the feeder connects to a 12-kV line (and that, in turn, to low-voltage buses), a system, Evans notes, will typically show voltage variability. Although this isn’t a problem from an engineering standpoint, he says, “It’s waste—and it presents an opportunity for optimization.” By carefully measuring these and assorted other losses, and then determining and ranking how they’d be reduced by a customer-installed generator nearby, a grid-improvement value results. And again, in incentive terms, a portion should be rebated to the adopter.

Another example: A customer installing a 150-kW combined-heating-and-power (CHP) system might allow for eliminating a nearby low voltage bus, or might flatten the overall voltage profile on that 12-kV line. The current would become more consistent. This would reduce wastage, thereby saving the utility, say, something in the low four figures each year. Obviously, a kickback might spur this win-win project considerably.

DG is but one of several solutions to be applied systematically in a well-optimized grid. Others include “more automated remote switching, changeable topology, controllable capacitors, distribution automation, and sophisticated demand response programs,” Evans says. “That’s the direction this will head. Distributed generation is maybe the most important piece of that, but it is not the only piece,” in a budding trend he sees toward radical grid renovation.

Siting Power for Maximum Grid Benefit
Back now to the question of precisely where generators should go and what their potential dollar value would be. Here, AEMPFAST’s tools for DG-on-grid analysis are able to integrate complex interrelated functions: System security, voltage profiles, reliability, congestion, minimum loss, minimum generation cost, minimum emission, minimum maintenance, locational marginal costs, congestion mitigation, and sophisticated asset optimization are all doable. Schoettle adds here that his product “is not based on the mathematical engines now prevalent,” and so therefore it “does not suffer from their limitations.” AEMPFAST analyzes a grid’s physical condition, virtually in real time (or with only a few seconds’ lag) and purports to give system engineers best-possible resource deployment choices. In so doing, it also ranks every component as to its net benefit, and to meeting the optimization objectives. These, says Schoettle, “can be multiple and varied, and can include both engineering and business objectives.” Even very fine detail and micro-analysis is possible. Evans notes that in the SVP study, “We could actually go down to line-segment by line-segment” to detect waste and to quantify savings opportunities, as well as doing the assessment device-by-device. Schoettle notes too that customer onsite power projects can often accomplish distribution savings and efficiencies “if located and sized optimally” to solve problems, “as well as serving the customer cost-effectively.”

With these win-win criteria in mind, then, Evans’s team launched the DG siting analysis. He assumed non-exporting generators that were switchable and dispatchable.

In their first what-if scenario, the DGs were limited to the light load on the feeder, meaning they could add only a maximum of 15% of the feeder power (meeting the cap under California’s Rule 21 limit for expedited interconnections).

Given this input, AEMPFAST identified hundreds of customer sites where DG would help the grid significantly—382 of them, to be exact. The aggregated total in new generation would be optimized at 13.6 MW; that’s about 36 kW per generator—totaling 3.4% of peak load.

A second what-if scenario optimized Silicon Valley Power’s light feeders. California grid connection rules are more liberal here, permitting up to 60% of the adjacent load to come from non-exporting DGs. On these, Evans’s group found 346 prime customer sites for onsite power, totaling 38 MW (9.7% of total peak load and about 110 kW per generator).

In the AEMPFAST number-crunching output came one surprising twist: The data showed that relatively small DGs—averaging much less than 150 kW—can carry almost disproportionate impact. In fact, one of the highest-prioritized potential DG sites that AEMPFAST flagged called for a mere 7 kW to support one customer’s 14-kW load. Nevertheless, this particular locale was so critical to the grid, Evans explains, that “adding capacity there would benefit the entire system.”

For multiple reasons, small-footprint power projects are just generally easier to position near the feeder loads than are megawatt-sized ones. Likewise, smaller generators can more readily be optimally sized to match loads. “The sweet spot here,” says Evans, “tends to fall somewhere between 100 and 300 kilowatts.” In this size range, scores of cogen installations turned out to be very cost-effective for customers, especially when the analysis could assume low or subsidized up-front costs.

Next, regarding the very best win-win deals carrying the highest value, these were generally found to exist near the ends of main feeders—an interesting finding in itself. By adding generation capacity here, Evans points out, “not only does it benefit the feeder, but the entire system.” Generally speaking, the more remote the DG positioning, the greater the grid benefit. Less impressive but still cost-justifiable results emerge from proposed installations near existing DG plants.

In any event, location-specific analyses like these should be performed in ideal DG installations in the future, Evans and Schoettle believe. AEMPFAST does this, as part of its site ranking. With the help of such tools, says Evans, “A utility can look at multiple permutations and load scenarios, multiple ways of controlling the units, identifying optimal locations, and then figuring out how far away from the optimal performance you get by using different locations.”

Quantifying the Savings Magnitude
Bottom line? All in all, the Silicon Valley grid—if fully DG optimized—could achieve an impressive 31% reduction in real power losses. Along with this would come another 30% reduction in reactive power consumption, equal to 15.203 MVAR. If recommendations churned out by AEMPFAST were actually applied, the resulting reduction in losses would come in, as Evans notes, “at three times the system’s average loss rate.” These numbers are particularly impressive, he adds, because SVP was already relatively well designed, maintained, and operated. In more stressed-out utility environments (found in many locales), potential savings would be much greater.

Better still, because SVP’s grid interconnects with Pacific Gas & Electric’s transmission system, the latter also benefits, to the tune of about 5 MW gained. In economic terms, that could easily translate into thousands of dollars a day during peak loads.

Evans sums up, “These values are significant. They can be quantified. And they are real benefits to this network.” Even so, he points out, most of that value still remains with the onsite DG customer—who, after all, has hypothetically paid for it. Customer outlays yield a windfall to utilities; hence, customers should arguably get some of it back.

What’s It All Going to Mean to DG’s Future?
In 2005, a second NPT technology study, conducted at the much larger and more complex Southern California Edison (SCE) network, will explore small-generator impact even more extensively. In scope and scale, the SCE study will be almost 20 times larger than the SVP demonstration, Evans notes. Added to the SCE analysis will be a look at DG’s impact, for example, on winter-peak, light-load, and load-growth conditions. Research funding will come from a $5.4 million grant to Evans’s firm from the CEC.

Beyond such public-private partnerships as these, various paths to a DG-optimized reality of tomorrow are imaginable.

One seemingly likely route would be through regulatory commissions and utility rate-setting bodies. For example, Evans suggests, if a utility company sought major funding for transmission and distribution (T&D) upgrades, a panel of commissioners might require that a DG-friendly assessment first be done, at least to present an alternative. If the resulting choice then came down to either approving $100 million in rate hikes to pay for more wires or endorsing scores of customer-owned onsite power, then naturally most regulators would welcome the latter.

Or—positing a more collaborative approach—utility companies might offer financing to selected cogen adopters on a dollars-per-kilowatt-installed basis. Adopters would earn rebates by siting generators near particular buses. Deals would be subject to further terms such as kilowatt output levels; a non-exporting connection; networkability; lead lag VAR capability; and perhaps real-time, variable, controllable reactive-power production. Cogen plant owners might agree to run their engines “at least 80% of the time during peak hours,” Evans suggests, while also agreeing to curtail off-peak operation, or to comply with other terms that might be required. Giving these grid-driven parameters, onsite power would then become a win-win-win for utilities, adopters, and developers.

At the state agency level, key players working to make DG-optimized grids and “ultra-networking” happen include the CEC as well as the California Independent System Operators (CAISO). The latter oversees most of the state’s power transmission system, and this organization, says its manager of special project engineering, David Hawkins, “is strongly supportive of adding more distributed generation” to relieve transmission loads. DG resources, he believes, “can provide some real benefits both for customers and for transmission-load relief during times of peak loading.” Widespread implementation of DG, he adds, could become “a wonderful additional tool to help us avoid having to do major customer load-shedding.” Hawkins served on Evans’s technical advisory committee and is also working with Optimal on critical new tools for CAISO.

First, before any large-scale deployment of grid-optimized DG becomes a reality, new technology for dispatching, remote monitoring, and control systems—currently under development—must mature. Potentially hundreds of DG assets might be networked and, in order to coordinate them all, engineers will need ways to activate specific ones quickly and efficiently “to manage loads and avert trouble,” notes Hawkins. CAISO, he adds, is now teaming up with SCE and others to implement networked, inter-communicating distributed resources on a large scale. A demonstration project currently in the offing will probably turn out to be the largest coordinated DG application ever implemented.

Money to pay for such R&D will continue to flow to worthy undertakings like these, adds Mark Rawson, CEC’s policy coordinator for DG and the commission’s DG integration research program manager. CEC has already contributed $100 million (mainly through PIER) to develop and advance distributed power. PIER’s past investments have supported the development of cleaner-burning and lower-cost generators, among other causes. Rawson anticipates that, as interconnectivity matures, CEC will appropriately revise California’s energy policy in order to expand the role of DG. In turn, CEC’s sister agency, the California Public Utilities Commission (CPUC), will alter utility rates and policies. Rawson points out that, beginning in early 2004, the CPUC was already directing state utilities “to include the implementation of DG resources in determining distribution planning,” and, he adds, “to the extent that utilities can determine that DG would be a more cost-effective solution than a traditional utility wires solution, the utilities were directed to pursue that as well.”

As for future intentions at Optimal, Schoettle is promoting AEMPFAST to utilities and distribution system operators to “solve previously unsolvable problems” in grid management. Various current and pending tools that Optimal is offering will make it easier, faster, and more attractive for engineers to evaluate and implement DG projects. For example, grid operators can select DG-supported remedial actions; automate their network planning and emergency control; and carry out system restoration, etc., Schoettle says, “taking T&D grids to the next generation in optimized planning and operation.”

Also under development at Optimal is a DG controller tool that “integrates DG-device operating goals with system price and other performance signals, end use, and networked appliance-level monitoring and control devices,” Schoettle says, with bi-directional communication and controls, for dramatically enhanced demand-response management.

In short, by various means and avenues, DG dispatchability, remote monitoring, and controllability needs are rapidly being realized.

Summing up, Evans points out that the iconic images of our electrical system—i.e., big-smokestack power plants and miles of high-tension lines—are more antiquated than ever “and really quaint, when you think about it.” More of us are beginning to realize the obsolescence and inadequacy here. Grids are poised for being phased out and replaced with a perhaps overdue “intelligent energy infrastructure,” he says, “with transmission and distribution actively managed as an integrated network.” In a modernized electrical future, he says, “self-healing grids” will be capable of seamlessly adjusting to demand loads, emergencies, and outages. Loads will be made more responsive to network conditions. DG resources will be embedded into grids extensively—together with remote generation.

Energy services will be better tailored to meet widely disparate customer needs. And, when it’s all finished, our new infrastructure will be far less brittle and prone to outages, and much more flexible, customizable, and adaptable, than what we have now. “Today,” he says, “we’re demonstrating that these things are feasible and doable—and really not even that tough.” As for immediate needs, though, it’s now widely accepted that several of our urban centers face serious transmission crunches. Space for expansion to meet load growth no longer exists. Adding T&D isn’t viable “either because costs are too high” or local communities raise barriers, he adds. Urban markets especially will increasingly need their power generation and grid improvement solutions to be “located much closer to the loads.” DG networks “are the way to go.” And, because utilities stand to gain significantly from DG optimization, “let them share the benefit,” Evans suggests. “And everyone is better off.”

La Mesa, CA–based writer DAVID ENGLE specializes in construction-related topics.

DE - January/February 2006