Available waste heat could offset about 1,600 Mbtu of a typical customer's purchased natural gas previously used for space and water heating. Recalculating the net microturbine generating cost in this case results in 8.62 cents/kWh, which brings the microturbine generation costs lower than purchased electricity, but still not enough to offset the initial cost of the microturbine within the life of the equipment.
An even more dramatic change in the economic picture occurs if waste heat is used to fuel an absorption air conditioner. A 30 ton absorption unit could save about $14,500 in electricity costs in a commercial building with significant internal loads (offset partly by an additional $1,500 in O&M costs) reducing the total net cost of generating electricity to $62,500. In this final configuration, the net cost of onsite generated power is 7.13 cents/kWh, low enough to pay for the DG equipment in 6-8 years depending on installation costs and configurations. Since the $7.5 per Mbtu price used to compute gas costs in the example is greater than the likely average gas price in future years, especially in light of planned expansions in Long Island natural gas delivery capability, the payback for this particular application could be as low as 4 to 6 years.
Table 1 results suggest one of the difficulties in assessing costs and benefits of DG in an actual market or service area. Customer differences in hourly electric loads and differences in potential waste heat uses can easily result in payback periods that range from one-fourth to four times that shown in this particular example. Consequently, evaluating DG potential cannot be accomplished with "average" or "prototype" customer load data; instead, one must evaluate a sample of customers whose energy use diversity reflects that of the population of customers in the service area.
In summary, the economic potential for LIPA DG applications can be significantly greater than indicated by simple spark-spread analysis and varies considerably from customer to customer.
V. Efficiency, Natural Gas Conservation and Emissions
An active DG supply strategy has important implications for system efficiency, transportation and distribution investments, conservation of the limited Long Island natural gas supplies and air quality.
Table 2 compares a simple cycle combustion turbine (CT) natural gas unit and onsite microturbine systems. As indicated in row 1 of the table, CT units provide much greater electric generation efficiency than can be obtained with the smaller onsite technology (35% versus 27% , respectively). Line 2 of the table shows an estimate of transmission losses incurred in moving electricity from the CT power plant to the customer. This adjustment results in a line 5 total CT system efficiency of 32.6% (i.e., 32.6% of the energy content in the natural gas used to drive the Combustion turbine is delivered to the customer in the form of electric energy)
Table 2. Comparison of Simple Cycle Combustion Turbine and Microturbine Characteristics
Legend: MT(CHP) - Microturbine with waste heat applications
Table 3. Cost Comparison
Even with transmission losses, the Microturbine is less efficient in converting natural gas energy to electricity delivered to the customer. However, the picture changes when waste heat produced as a byproduct of the microturbine generation process is captured and used to supplement space and water heating. While the waste heat contribution to space and water heat varies by customer in the LIPA service area, the 15% utilization of total waste heat is reasonable for an appropriately sized DG unit. Capturing this waste heat, which is relatively inexpensive , pushes the microturbine system efficiency to 42% , which is 29% more than the CT delivered electricity efficiency. Even greater gains in the microturbine system efficiency are achieved with the addition of an absorption AC which uses waste heat as part of the AC process. Adding these waste heat uses improves system efficiency to 62%, almost double that of the CT unit.
Row 6 in the table shows "best case" system characteristics for both a CT/distribution system (60% efficiency for a combined cycle unit with 7% T&D losses) and a microturbine with optimally balanced heat, water heat and air conditioning loads.
As indicated in the emissions portion of the table, the microturbine system is almost as "clean" as the CT. However, row 11 - 14 show that when emissions avoided by using waste heat for air conditioning and avoided boiler emissions used to fire space and water heating are taken into account, total emissions are reduced by almost 40 percent. This avoided emissions benefit provides environmental benefits even when less clean gas-fired engines are used to drive onsite generation.
CT units are typically less costly to install than onsite DG systems, however, this differential can be offset by increased transmission and distribution costs especially if the existing system must be upgraded to facilitate the new capacity. Absorption AC costs typically range from $300/ton to $750/ton; however, in new or replacement systems, total HVAC costs can actually be less than that of a conventional system.
The greater system efficiencies achieved with DG means:
VI. Fuel Cell Systems
Fuel cells use an electrochemical process, similar to a battery, to convert fuel to heat and electricity. Fuel cells generate power with hydrogen (which can be extracted from natural gas) and oxygen from the air. Fuel cell technologies differ in the materials used to support the electrochemical process and include phosphoric acid (PAFC) molten carbonate (MCFC), solid oxide (SOFC) and proton exchange membrane (PEM). Electric generation efficiencies range from 35 to 60 percent and generate minimal emissions. In terms of total system efficiencies, fuel cells can deliver electricity and heat-driven applications with up to 80 - 90% efficiency, similar to that of an IES system using a microturbine; however, the electric generation part of a fuel cell system operates at significantly higher efficiency than other DG prime drivers. Thus the potential market for fuel cells is less dependent on harnessing waste heat than systems based on engines or microturbines.
Unfortunately, the current cost of these systems is about three times that of the microturbine and engine systems. Costs of fuel cells will fall significantly, however, as the commercialization process continues. Some industry estimates indicate that the installed cost of fuel cells will drop as low as 25 to 50 percent more than microturbines within three years. The extent of the price drop will depend on economies of scale, manufacturing experience and other factors which organizations like LIPA can accelerate with early adoption.
While significant commercialization of fuel cells will not occur until 2003 - 2004, fuel cell options must be considered now because current LIPA capacity expansion activities can have an impact on costs and benefits of adopting fuel cell systems in the future. For example, upgrading a portion of the transmission/distribution system to facilitate a central plant in 2004 will reduce the benefits that might have been achieved with the installation of fuel cells in 2005 because part of the benefit of a DG system is avoiding T&D upgrading costs.
Fuel cells are included in this analysis beginning in the year 2005 with costs that are compatible with industry target estimates, $1500 - $1900 /kW depending on the size of the unit. Even thought fuel cells are the most expensive DG main driver technology, their greater electric generation efficiency make them a competitive technology for some buildings, especially where waste heat applications are less important in defining system benefits.
VII. Avoided Electric Costs
LIPA operates in a competitive market where it can elicit new capacity by offering economic incentives, either to merchant power plants in the way of supply contracts or to customers by way of conservation, demand response and other incentive programs. To determine the efficacy of DG incentive programs versus other supply alternatives, one would ideally use detailed LIPA data on operating costs, transmission and distribution costs and market responses to LIPA power requests for proposals to determine the value to the LIPA system of adding 1 kW in DG capacity to 1 kW of central plant capacity.
Since this information is not available for this study, we apply LIPA rate structures to estimate the value of added capacity provided by DG. Current rate structures are a reasonable first approximation to marginal resource costs. Rate structures have been developed from cost of service analysis to equitably assess customers for their share of generation, transmission and distribution costs as a function of customer energy and peak demand during peak and off-peak periods. Since these rate structures are designed to cover average cost, they undoubtedly reflect lower costs than the true marginal costs of adding capacity to the system; consequently, results developed here will be conservative. That is, estimated DG potentials determined in this study reflect a lower bound on DG contributions which can economically be achieved if LIPA pursues a DG supply strategy.
The MAISY Utility Service Area DG Policy Model applies the appropriate rate structure to each customer in the sample of LIPA customers to determine avoided electricity costs.
Using rate structures to determine the value of DG capacity additions to LIPA makes customer and LIPA system analysis equivalent. That is, if DG installation is economically prudent for the customer, it is also prudent for LIPA to encourage the customer's installation. Consequently, while study results were developed to quantify the economic benefits of DG to LIPA, the results also provide an assessment of the market for DG systems from customer, DG equipment manufacturer and retailer perspectives.
VIII. Customer Information and MAISY DG Modeling
The pie chart below shows LIPA nonresidential electricity sales by customer type. Relatively little industrial activity takes place on Long Island compared to a "typical" utility; consequently this study focuses on DG potential in the commercial sector which is comprised of office, retail, hospitals, schools, government and other business and service activities.
Figure 3. LIPA Nonresidential Electricity Sales
As indicated in Table 1 above, space heating, water heating and air condition energy use characteristics of individual customers dramatically affects DG economics. Other factors such as hourly variations in electric and non-electric uses also impact the costs and benefits of a DG system and vary substantially even within similar business type categories.
Accounting for this customer diversity is critical in developing a reliable DG potential evaluation. Detailed customer information in this study is provided with the LIPA MAISY Utility Customer Service Area Database. In addition to providing information on individual customer buildings, occupancy, equipment and energy use for a sample of customers in each service area, these databases provide building and end-use hourly loads for each hour of the year for each customer record. These 8760 hourly loads, which reflect the unique operating characteristics of each customer, are essential for determining detailed DG system costs and benefits.
The MAISY Utility Service Area DG Policy Model, simulates the economic evaluation of each of thirty individual DG generation technologies including natural gas driven engines, microturbines and fuel cells. Information on twenty different reciprocating, centrifugal and absorption air conditioning systems is also used to evaluate waste heat applications for air conditioning. Costs and benefits of each DG technology option are evaluated and the most economically attractive technology is installed at the customer's site. Avoided electricity costs, operating and maintenance costs, avoided natural gas costs, additional costs of natural gas for generation and equipment and installation costs are all considered. More than one technology can be applied at each site; for instance, a customer might install a baseload DG system with an absorption air conditioner along with a peaking DG unit. Only customers who already use natural gas are considered prospects for DG.2 Furthermore, characteristics of the current HVAC system are also considered in determining the cost and potential for retrofitting buildings with waste-heat driven systems. Only projects which provided a payback of less than ten years were considered; the average payback for the existing stock of buildings is 5.1 year and the average for new construction is 4.5 years.
The microsimulation modeling process applied in the MAISY DG models has been used to assess the economic potential and market penetration for a variety of new technologies in previous applications. More information is available on the MAISY DG Energy Policy Models at : http://www.maisy.com/udganal.htm.
IX. LIPA DG Potentials
Figure 4 shows the projected LIPA shortfall in capacity along with central plant electricity savings which can be achieved with DG systems. The 1,000 MW capacity deficiency for 2003 - 2011 is taken from the LIPA Draft Energy Plan. The second bar in the chart shows that 465 MW are available from the current stock of commercial buildings in the LIPA service area with the application of DG systems to existing commercial sector buildings. Considering new construction in the 2003-2011 period and opportunities created when air conditioning equipment is replaced in existing buildings increase the DG MW savings potential to 545 MW. Incorporating fuel cells in the analysis beginning in 2005 extends the DG potential to 631 MW, or almost two-thirds of the currently anticipated capacity shortfall in the LIPA service area.
Figure 4. LIPA MW Shortfall and Potential Commercial Sector DG MW Contributions
Figure 5 shows 2002 DG MW potentials by commercial building category. Office buildings reflects by far the largest opportunity for DG applications in the LIPA service area.
Figure 5. Potential DG MW Contributions by Business Activity, 2002
Figure 6 shows the number of individual buildings within each business sector for whom a DG system is economically attractive.
Figure 6. Number of Potential LIPA Economic DG Installations, 2002
X. Other Policy Considerations
Distributed Generation installations are hindered by the emissions and construction permitting processes. LIPA is working with local agencies on Long Island to streamline permitting activities related to its residential solar program; similar efforts can be undertaken for DG applications in commercial buildings. The state of New York is currently developing emissions requirements for DG which will presumably reflect output efficiency advantages of DG providing credit for avoided power plant and boiler emissions associated with DG systems. One can reasonably expect that many of the permitting difficulties that have slowed the adoption of DG will soon begin to diminish, especially for smaller systems.
Keyspan provides support for LIPA customer DG installations on Long Island; however, the general lack of customer knowledge on customer benefits of DG still reflects a substantial impediment to customer-initiated DG installation. Both Keyspan and LIPA can substantially improve information flow if DG were to become a planning priority. LIPA can also provide incentives to encourage installation of DG systems.
The gas-driven DG systems evaluated in this study will make demands on the limited supply of natural gas available on Long Island; however, as indicated in Table 2 above, DG applications can make more efficient use of gas resources, essentially, stretching available gas further. In addition, much of the natural gas-driven central capacity on Long Island can be fueled with low-sulfur oil during times of natural gas shortages.
LIPA is required to perform a difficult resource balancing act, trading off customer incentive programs and contracted generation and transmission resources. Incorporating a quantitative assessment of potential DG resources in this planning will provide an even more robust strategic evaluation.
1Spark spread statistics do not usually include operating and maintenance costs; however, the economic evaluation of operating costs is more meaningful when these costs are included
2Natural gas is the only fuel considered here to fuel DG systems because gasoline and fuel oil systems would not meet emissions requirements on Long Island. These fuel sources are viable, especially in smaller systems, in geographic areas where emissions requirements are less strict.
(c) 2005 Jerry Jackson. All rights reserved.