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We present experiments with combined reactive and resistive loads on a testbed based on the Controlled-Delivery power Grid (CDG) concept. The CDG is a novel data-based paradigm for distribution of energy in smart cities and smart buildings. This approach to the power grid distributes controlled amounts of power of loads following a request-grant protocol performed through a parallel data network. This network is used as a data plane that notifies the energy supplier about requests and inform loads of the amount of granted power. The energy supplier decides the load, amount, and the time power is granted. Each load is associated with a network address, which is used at the time when power is requested and granted. In this way, power is only delivered to selected loads. Knowing the amount of power being supplied in the CDG requires knowing the precise amount of power demand before this is requested. While the concept works well for an array of resistive loads, it is unclear how to apply it to reactive loads, such as motors, whose power consumption varies over time. Therefore, in this paper, we implement a testbed with multiple loads, two light bulbs as resistive loads and an electrical motor as a reactive load. We then propose to use power profiles for the adoption of the request-grant protocol in the CDG concept. We adopt the use of power profiles to leverage the generation of power requests and evaluate the efficiency of the request-grant protocol on the amount of supplied power. In addition, the deviation of delivered power in the data and power planes is evaluated and results show that the digitized power profile of the reactive loads enables the issuing of power requests for such loads with high accuracy.
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Multi-Objective Logarithmic Extremum Seeking for Wind Turbine Power Capture with Load Reduction
This paper describes a multi-objective ESC strategy that determines Pareto-optimal control parameters to jointly optimize wind turbine loads and power capture. The method uses two optimization objectives calculated in real time: (a) the logarithm of the average power and (b) the logarithm of the standard deviation of a measurable blade load, tower load or the combination of these loads. These two objectives are weighted in real-time to obtain a solution that is Pareto optimal with respect to the power average and the standard deviation of chosen load metric. The method is evaluated using NREL FAST simulations of the 5-MW reference turbine. The results are then evaluated using energy capture over the duration of the simulation and damage equivalent loads (DEL) calculated with MLife.
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- Award ID(s):
- 2040335
- PAR ID:
- 10285278
- Date Published:
- Journal Name:
- Multi-Objective Logarithmic Extremum Seeking for Wind Turbine Power Capture with Load Reduction
- Page Range / eLocation ID:
- 533 to 538
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.23919/ACC50511.2021.9483187
