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Optimal Allocation of Wind Turbines in Active Distribution Networks by Using Multi-Period Optimal Power Flow and Genetic Algorithms

Pierluigi Siano ; Peiyuan Chen (Institutionen för energi och miljö, Elteknik) ; Zhe Chen ; A. Piccolo
Modeling and Control of Sstainable Power Systems : Towards Smarter and Greener Electric Grids p. 20. (2012)

In order to achieve an effective reduction of green house gas emissions, the future electrical distribution networks will need to accommodate higher amount of renewable energy based on distributed generation such as Wind Turbines. This will require a re-evaluation and most likely a revision of traditional methodologies, so that they can be used for the planning and management of future electrical distribution networks. Such networks evolve from the current passive systems to active networks and smart grids, managed through systems based on Information Communication Technology. This chapter proposes a hybrid optimization method that aims of maximizing the Net Present Value related to the Investment made by Wind Turbines developers in an active distribution network. The proposed network combines a Genetic Algorithm with a multi-period optimal power flow. The method, integrating active management schemes such as coordinted voltage control, energy curtailment and power factor control is demonstrated on a 69-bus 11kV radial distribution network.

Nyckelord: active distribution system, genetic algorithms, optimal power flow, optimization

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Denna post skapades 2012-01-26.
CPL Pubid: 154442


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Institutioner (Chalmers)

Institutionen för energi och miljö, Elteknik



Chalmers infrastruktur