Computationally Efficient Adjustment of FACTS Set Points in DC Optimal Power Flow With Shift Factor Structure

2017 ◽  
Vol 32 (3) ◽  
pp. 1733-1740 ◽  
Author(s):  
Mostafa Sahraei-Ardakani ◽  
Kory W. Hedman
Keyword(s):  
Factor Structure ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Shift Factor ◽  
Computationally Efficient ◽  
Optimal Power

scholarly journals Adaptive leader election for control of tactical microgrids

2020 ◽  
pp. 154851292090478
Author(s):  
Robert S Jane ◽  
Steven Y Goldsmith ◽  
Gordon G Parker ◽  
Wayne W Weaver ◽  
Denise M Rizzo
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Communication Complexity ◽  
Leader Election ◽  
Electrical Network ◽  
Computationally Efficient ◽  
Mobile Vehicle ◽  
Optimal Power ◽  
Asset Inventory ◽  
Desirability Index

An adaptive leader election protocol (LEP) was developed to control both stationary and mobile generation assets (generators and vehicles), achieved using an energy management system (EMS). The LEP algorithm adapts to changes in both topology and the asset inventory using the longevity criterion (available fuel, future availability), used to compute a desirability index, for election of a leader. The leader then implemented an optimal power flow EMS to ensure sufficient and optimal power flow within the electrical network was maintained in the presence of a complex electrical load, regardless of the asset mix. Both the LEP and EMS algorithms were distributed to the generation assets. This capability supports stationary grid-tied, vehicle-to-grid, and mobile vehicle-to-vehicle-based applications. Simulated case studies illustrate that the adaptive LEP was resistive to deterministic events (maintenance, available fuel), which could yield an inoperable asset, compromising grid stability. The use of the adaptive LEP resulted in a communication complexity of at most [Formula: see text]; in contrast, a fully connected communication system requires [Formula: see text] communications, limiting the scalability of the network. The EMS was optimized, resulting in a computationally efficient and scalable optimal power flow algorithm that can be extended for more general stationary or mobile energy networks.

Optimal Power Flow Using Newton’s Method

2012 ◽  
Vol 3 (2) ◽  
pp. 167-169
Author(s):  
F.M.PATEL F.M.PATEL ◽  
◽  
N. B. PANCHAL N. B. PANCHAL
Keyword(s):  
Newton’S Method ◽  
Newton's Method ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Power

Designing the Electricity Market with Energy Storage Devices

2020 ◽  
Vol 12 (12) ◽  
pp. 31-43
Author(s):  
Tatiana A. VASKOVSKAYA ◽  
◽  
Boris A. KLUS ◽  
Keyword(s):  
Energy Storage ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Storage Systems ◽  
Energy System ◽  
Energy Storage Systems ◽  
Storage Model ◽  
Optimal Power ◽  
Wide Range

The development of energy storage systems allows us to consider their usage for load profile leveling during operational planning on electricity markets. The paper proposes and analyses an application of an energy storage model to the electricity market in Russia with the focus on the day ahead market. We consider bidding, energy storage constraints for an optimal power flow problem, and locational marginal pricing. We show that the largest effect for the market and for the energy storage system would be gained by integration of the energy storage model into the market’s optimization models. The proposed theory has been tested on the optimal power flow model of the day ahead market in Russia of 10000-node Unified Energy System. It is shown that energy storage systems are in demand with a wide range of efficiencies and cycle costs.

A Comparison of Computing techniques for the Optimal Power Flow Problem

2011 ◽  
Vol 4 (4) ◽  
pp. 14-18
Author(s):  
A.V. Naresh Babu ◽  
◽  
S. Sivanagaraju ◽  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Problem ◽  
Optimal Power ◽  
Power Flow Problem
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