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What is LCOE?

LCOE (levelized cost of energy) is one of the utility industry’s primary metrics for the cost of electricity produced by a generator. It is calculated by accounting for all of a system’s expected lifetime costs (including construction, financing, fuel, maintenance, taxes, insurance and incentives), which are then divided by the system’s lifetime expected power output (kWh). All cost and benefit estimates are adjusted for inflation and discounted to account for the time-value of money. As a financial tool, LCOE is very valuable for the comparison of various generation options. A relatively low LCOE means that electricity is being produced at a low cost, with higher likely returns for the investor. If the cost for a renewable technology is as low as current traditional costs, it is said to have reached “Grid Parity”. LCOE Estimates for Renewable Energy When an electric utility plans for a conventional plant, it must consider the effects of inflation on future plant maintenance, and it must estimate the price of fuel for the plant decades into the future. As those costs rise, they are passed on to the ratepayer. A renewable energy plant is initially more expensive to build, but has very low maintenance costs, and no fuel cost, over its 20-30 year life. As the following 2012 U.S. Govt. forecast illustrates, LCOE estimates for conventional sources of power depend on very uncertain fuel cost estimates. These uncertainties must be factored into LCOE comparisons between different technologies. LCOE estimates may or may not include the environmental costs associated with energy production. Governments around the world have begun to quantify these costs by developing various financial instruments that are granted to those who generate or purchase renewable energy. In the United States, these instruments are called Renewable Energy Certificates (RECs). To learn more about environmental costs, visit our Greenhouse Gas page. LCOE estimates do not normally include less tangible risks that may have very large effects on a power plant’s actual cost to ratepayers. Imagine, for example, the LCOE estimates used for nuclear power plants in Japan before the Fukushima incident, compared to the eventual costs for those plants. Location An important determination of photovoltaic LCOE is the system’s location. The LCOE of a system built in Southern Utah, for example, is likely to be lower than that of an identical system built in Northern Utah. Although the cost of building the two systems may be similar, the system with the most access to the sun will perform better, and deliver the most value to its owner. The National Renewable Energy Laboratory map below illustrates the differences in solar resources across the country. As you can see, Utah’s available solar energy is quite high, compared to most of the country. System technology and design also affect LCOE. Two apparently similar systems in the same location may produce very different financial results. Some panels, for example, perform better in low-light or high heat conditions than other systems, and some systems are built to deliver a higher percentage of the electricity produced to the user. Over the life of a system, these differences can be significant. Component prices for photovoltaic systems have fallen drastically over the last two years. With currently-available tax incentives, a well-priced, well-designed system can easily provide a very satisfactory return on one’s investment. The same rule applies to wind’s levelized cost. Wind turbines located on one side of a valley may be far more economical than turbines located on the other side of the same valley. An understanding of prevailing wind patterns is critical is a critical component of the planning process. The LCOE for wind power has fallen below the cost of traditional alternatives in many locations. Watch the short “Winds of Change” clip on our Videos page. If you would like to try out a simple LCOE calculator provided by the National Renewable Energy Labs, use this link: LCOE Calculator. The calculator is easy to use, and can help you understand how changes in assumptions affect LCOE results.
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