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Application of multi-criteria decision making to sustainable energy planning-A review S. D. Pohekar , and M. Ramachandran Birla Institute of Technology and Science (BITS), Pilani 333 031, India Received 1 December 2003;  accepted 19 December 2003.  Available online 31 January 2004. Abstract Multi-Criteria Decision Making (MCDM) techniques are gaining popularity in sustainable energy management. The techniques provide solutions to the problems involving conflicting and multiple objectives. Several methods based on weighted averages, priority setting, outranking, fuzzy principles and their combinations are employed for energy planning decisions. A review of more than 90 published papers is presented here to analyze the applicability of various methods discussed. A classification on application areas and the year of application is presented to highlight the trends. It is observed that Analytical Hierarchy Process is the most popular technique followed by outranking techniques PROMETHEE and ELECTRE. Validation of results with multiple methods, development of interactive decision support systems and application of fuzzy methods to tackle uncertainties in the data is observed in the published literature. Author Keywords: Author Keywords: Multi-objective optimization; Multi-criteria decision making; Decision support systems; Sustainable energy planning Article Outline 1. Introduction 2. Overview of multi-criteria decision making (MCDM) methods 2.1. Weighted sum method (WSM) 2.2. Weighted product method (WPM) 2.3. Analytical hierarchy process (AHP) 2.4. Preference ranking organization method for enrichment evaluation (PROMETHEE) 2.5. The elimination and choice translating reality (ELECTRE) 2.6. The technique for order preference by similarity to ideal solutions (TOPSIS) 2.7. Compromise programming (CP) 2.8. Multi-attribute utility theory (MAUT) 3. Multi-criteria decision making applications in energy planning 3.1. Multi-objective optimization 3.2. Decision Suppor

Their study, the Global Limits of Biomass Energy, sought to utilize satellite imagery, reports, productivity models and other data to estimate the amounts of energy that could be produced from these derelict plots of earth.

Environmental organizations and sustainability advocates routinely assert that energy consumption for passenger rail is much "greener" than driving or flying. But Tables 2.13 and 2.14 (summarized in 2.12, above) in the Department of Energy's Transportation Energy Data Book #27 indicate that existing Amtrak intercity passenger rail is only 25% more efficient than the fleet average for cars; furthermore, Amtrak is only 19% more efficient than air travel!

The Massachusetts Renewable Energy Trust commissioned a study last year to review electricity output from 21 small wind turbines in the state and the results were surprising: the data showed that the estimated production was about three times higher than the turbines' actual production.

This afternoon a power outage in San Francisco affected the 365 Main St. data center. In the process of 6 cascading outages, one of the outages was not protected and reset systems in many of the colo facilities of that building. - DNS servers lost power and did not properly come back up. This has been resolved after about an hour of downtime and may have caused issues for many GNi customers that would appear as network issues

The process, Current says, lets a utility more efficiently manage the distribution of electricity by allowing two-way communication between consumers and energy suppliers via the broadband network on the power lines. Based on data they receive from hundreds of homes, utilities can monitor usage and adjust output and pricing in response to demand. Consumers can be rewarded with reduced rates by cutting back on consumption during peak periods. And computerized substations can talk to each other so overloaded circuits hand off electricity to underused ones, helping to prevent blackouts.

Milpitas, Calif.-based Adaptec (Nasdaq:ADPT) launches a new patent-pending product today that it says eliminates the need for lithium-ion batteries in data centers.

"The renewable energy map has been developed to fill what seems to be a gap in information about the major renewable energy schemes in the UK. Though there are a number of lists and project details available, these are often developed to indicate a point in time or a specific technology. The BWEA is an example of the latter, an excellent resource but specifically focused on wind. The data that has been gathered for the renewables map has invariably come from a wide range of web resources, in all cases these will be referenced, usually by a link to that information. Locations are either taken from existing data, usually from planning applications, or by painstakingly identifying the location on the ground using online maps. There are of course errors (such as landfill's at sea), though these are corrected as soon as they are identified."

**Extremely useful comparison + charts** Covers 11 technologies from 6 data sources. Source detail included in appendix. Costs: capital, fixed, operating, learning factor; Technical: size, heat rate, [potential] capacity factor, service life. Note on unit life: not all data sets include this, some run as long as plant is economic (no pre-determined retirement age), can represent max service life or is just used to compute economics (e.g. LCOE).

Hydrogen is a better source of energy than you think, according to Fujitsu. The Japanese electronics giant inaugurated a 200-kilowatt hydrogen fuel cell from UTC on Friday that will provide electricity as well as heat to the buildings on its campus here. The fuel cell--which sits in the parking lot and looks like a pair of giant green dumpsters--provides two types of energy to the facility. First, a unit heats methane with steam to create hydrogen. The hydrogen is passed through a proton exchange membrane (PEM). The electricity produced by the reaction with the PEM runs lights, computers and other equipment