July – SG & Applications
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Written by Adel El-Shahat
Electrified aircraft and flying vehicles are the future of aviation and society’s transportation for future smart grids. These technologies have emerged as a key enabling technology for concepts ranging from hybrid-electric propulsion systems to all-electric aircraft. The global electrification market is promptly expanding, and it is estimated to reach $8.6 billion USD by 2030. Moreover, flying vehicles and electrified airplanes are coming into play by addressing various aspects such as the reduction of emissions, running costs, and decarbonization, along with the concourse of technologies’ evolutions, and growth in ride-sharing needs. Modern advances in electric motors, power converters, batteries, and related auxiliary systems have energized the industry, leading to the development and demonstration of a range of a range of air transport systems on the ground and in flight.
Written by Soheil Mohseni and Alan Brent
Demand response is increasingly recognized as a valuable system resource to cost-effectively manage peak loads. Particularly in off-grid microgrid applications, it can play a pivotal role in reducing the total discounted cost of the project by minimizing the risk of overbuilt equipment capacity, which either remains under-utilized (for storage devices) or necessitates excessive curtailments (for renewable generators) over the project life-cycle. In this light, this article discusses the potential opportunities of implementing integrated demand response programs using relevant state-of-the-art technologies to reduce the need for cost-prohibitive energy infrastructure, with a particular focus on non-grid-connected scenarios.
Written by Linda M. Zeger
As Distributed Energy Resources (DER) behind the meter (BTM) increase, the need to carefully manage both the demand-supply balance and increased utilization of local feeders and transformers is highlighted; this management requires accurate and timely information. Reliability issues in grid data could degrade this information and result in the propagation of inaccuracies, including into smart grid control. Poor data quality or inaccurate forecasts could potentially contribute to unnecessary green-house gas (GHG) emissions and financial expenditures, as well as adverse grid events.