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The evolution of conventional electric grid into Smart Grid (SG) has enabled utilities as well as consumers to reap fruits due to its time varying price mechanisms. The utilities can acquire benefits by improving stability of grid, lessening blackouts and brownouts, knowing better their consumers power needs and not investing into new infrastructures. On the other hand consumer can also reduce electric bills, gain incentives by installing renewable energy sources and exporting energy to the main grid and attain improved services from utility. Demand Response (DR) is one of the most cost effective and reliable techniques used by utilities for consumers load shifting. In this paper, we are presenting a review of several DR techniques with a specific view on pricing signals, optimization, appliance scheduling used and their benefits. A comprehensive performance comparison is also prepared with the help of multiple criteria of SG paradigm.

This paper presents, with a live field experiment, the potential of increasing wind farm power generation by optimally yawing upstream wind turbine for reducing wake effects as a part of the SmartEOLE project. Two 2MW turbines from the Le Sole de Moulin Vieux (SMV) wind farm are used for this purpose. The upstream turbine (SMV6) is operated with a yaw offset ( α ) in a range of − 12 ° to 8° for analysing the impact on the downstream turbine (SMV5). Simulations are performed with intelligent control strategies for estimating optimum α settings. Simulations show that optimal α can increase net production of the two turbines by more than 5%. The impact of α on SMV6 is quantified using the data obtained during the experiment. A comparison of the data obtained during the experiment is carried out with data obtained during normal operations in similar wind conditions. This comparison show that an optimum or near-optimum α increases net production by more than 5% in wake affected wind conditions, which is in confirmation with the simulated results.

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