Listed below are all documents and RMI.org site pages related to this topic.
Energy and Resources 234 Items
The session explored how platforms can enable value exchange of DER, both vertically to the distribution and bulk power system, as well as horizontally through bilateral transactions from distributed resources.
Caroline Hillegeer from GdF Suez shared her perspective on the European distributed energy landscape (see attached slides), along with insightful contributions from others familiar with the European situation.
This session reviewed the work that Fort Collins Utilities did to develop a new business model titled, “Integrated Utility Services” (IUS). In the IUS model, the utility would deliver integrated packages of solar and efficiency to customers using on-bill repayment and delivering savings from day 1. This business model would diversify the utility’s business model by providing new revenue from service charges for the solar and efficiency, while at the same time delivering savings to customers.
Fort Collins Utilities has been working on this e-Lab project for over a year, and shared a draft of their final report. In attendance were representatives from SMUD, Avista, Duke, ConEd, and others. The goal was to have a practical discussion about how these and other utilities could deliver new services to their customers in this or similar ways, and to provide structured feedback to FCU and RMI on the proposed
IUS business model for Fort Collins.
The purpose of this session was to further scope a potential project to launch an e-Lab “X-Prize” (name likely to be changed) that would offer a cash reward for solving a tough problem faced by the electricity sector related to eLab’s core issues. The group was very enthusiastic about the idea as a means of driving interest and excitement in these issues, but has agreed to further scoping and due diligence are needed before a go/no-go decision can be made.
Report or White Paper, 2014
This report examines the opportunity for accelerating Fort Collins’ energy and climate goals to reflect the community’s values while capturing economic, social, and environmental benefits. In the five years since Fort Collins initially established its current greenhouse gas emissions goals, rapid changes in the cost and availability of clean, energy efficient technologies, together with the emergence of new business models and financing methods for implementing these measures, have dramatically shifted the solutions space for addressing the community’s energy needs. The cost of solar panels, for example, has fallen nearly 75% since 2008, with further dramatic declines yet to come; the retail price for energy- efficient LED lightbulbs has fallen by 50% in the past year. These and other changes have opened the door for the City to implement new solutions to reduce emissions and waste, stimulate local economic development, improve security, and reduce risk.
This analysis indicates that, in the accelerated scenario, Fort Collins can achieve an approximate 80% reduction in CO2 emissions by 2030, two decades ahead of its existing 2050 greenhouse gas reduction target. In doing so, the community could:
• reduce building energy use by 31% through efficiency,
• achieve a carbon neutral electricity system by 2030, and
• reduce transportation energy use by 48%.
Fact-sheet or One-pager, 2014
4 Page fact sheet detailing the spiral of falling sales and rising electricity prices that make defection via solar-plus systems even more attractive and undermine utilities' traditional business models
Report or White Paper, 2014
Though many utilities rightly see the impending
arrival of solar-plus-battery grid parity as a threat,
they could also see such systems as an opportunity to
add value to the grid and their business models. The
important next question is how utilities might adjust
their existing business models or adopt new business
models—either within existing regulatory frameworks
or under an evolved regulatory landscape—to tap into
and maximize new sources of value that build the best
electricity system of the future at lowest cost to serve
customers and society. These questions will be the
subject of a forthcoming companion piece.
Report or White Paper, 2014
The development of Australia’s solar market, and
the drastic cost reductions it saw over a short period of time, emphasize that high market demand and transparency in costs is a key towards reducing
soft costs. When the market is large enough, solar installers and retailers can rely more upon volume for profitability and can create reductions in soft costs in order to compete in the marketplace.
2014 (July) Edition: The purpose of the micropower database is to present a clear, rigorous, and independent assessment of the global capacity and electrical output of micropower (all renewables, except large hydro, and cogeneration), showing its development over time and documenting all data and assumptions. With minor exceptions, this information is based on bottom-up, transaction-by-transaction equipment counts reported by the relevant suppliers and operators, cross-checked against assessments by reputable governmental and intergovernmental technical agencies. For most technologies, historic data runs from 1990 through 2013. Available information includes installed capacity (GW) and electricity generation (TWh/y) per generating technology. The Micropower Database Methodology is also included in this ZIP-file. For previous versions, please see the 2008 Micropower Database (RMI ID E05-04) and the 2010 (May) Edition (RMI ID 2010-06).
Journal or Magazine Article, Letter, 2014
A May 2014 working paper by nonresident Brookings Institute fellow Dr. Charles Frank, highlighted in The Economist, claims that wind and solar power are the least, while nuclear power and combined-cycle gas generation are the most, cost-effective ways to displace coal-fired power. (He didn't assess efficiency.) This detailed twelve-page critique by RMI's Amory Lovins shows that those priorities are artifacts of Dr. Frank's obsolete data. Replacing nine of his wrong numbers with up-to-date empirical ones, even without correcting his methodology, reverses his priorities to the ones most energy experts would expect: after efficiency, the best buys are hydropower (on his purely economic assumptions), then windpower, photovoltaics, gas combined-cycle (assuming 1.5% methane leakage and medium price volatility—assuming zero price volatility would put gas ahead of solar), and last of all nuclear power. Dr. Frank argued that the way most investors pick power-sector investments—lowest long-run economic cost—is wrong, or at least incomplete, because different technologies generate power at different times, creating different amounts of value. He's right that value as well as cost should be considered. But interestingly, using correct data, the cost- and value-based calculations yield the same priorities, so adjusting for time of generation doesn't matter. Those priorities would probably be further reinforced (other than big and some small hydropower) if other kinds of hidden costs, risks, and benefits were also considered. The more obvious of Dr. Frank's data problems were assuming wind and solar power half as productive and twice as costly as they actually are, gas power twice as productive as it actually is but with no methane leakage or price volatility (let alone extractive side-effects of fracking), nuclear power at about half its actual cost and construction time and one-fifth its actual operating cost, a supposed need for new generating capacity and for bulk electricity storage, and no efficiency opportunities worth mentioning. His method of analyzing grid reliability was also unique and strange. These assumptions drove his unwarranted but, thanks to the Economist, widely publicized conclusions.
Dr. Frank argued that the way most investors pick power-sector investments—lowest long-run economic cost—is wrong, or at least incomplete, because different technologies generate power at different times, creating different amounts of value. He's right that value as well as cost should be considered. But interestingly, using correct data, the cost- and value-based calculations yield the same priorities, so adjusting for time of generation doesn't matter. Those priorities would probably be further reinforced (other than big and some small hydropower) if other kinds of hidden costs, risks, and benefits were also considered.