Vasiliki Vita

Estimation of wind turbines optimal number and produced power in a wind farm using an artificial neural network model

One of the most significant issues in the design of a new wind farm is the estimation of optimal number of wind turbines that has to be installed in it. The goal of every wind farm designer is the production of the maximum possible power, minimizing the installation cost. The cost can be significantly reduced using the minimum required number of wind turbines for specific power production, occupying at the same time the least possible acreage of land. In this work an artificial neural network (ANN) model is developed which has the ability to estimate the optimal number of wind turbines and the total produced power in a wind farm. The ANN model’s results are compared with those of earlier studies that have followed other approaches, proving that the ANN model is well working and has an acceptable accuracy. The proposed model can be useful in the studies of wind farm designers as a supportive tool for the estimation of the optimal number of wind turbines in a wind farm.

An open data repository for steady state analysis of a 100-node electricity distribution network with moderate connection of renewable energy sources

The data of this article represent a real electricity distribution network on twenty kilovolts (20 kV) at medium voltage level of the Hellenic electricity distribution system [1]. This network has been chosen as suitable for smart grid analysis. It demonstrates moderate penetration of renewable sources and it has capability in part of time for reverse power flows. It is suitable for studies of load aggregation, storage, demand response. It represents a rural line of fifty-five kilometres (55 km) total length, a typical length for this type. It serves forty-five (45) medium to low voltage transformers and twenty-four (24) connections to photovoltaic plants. The total installed load capacity is twelve mega-volt-ampere (12 MVA), however the maximum observed load is lower. The data are ready to perform load flow simulation on Matpower [2] for the maximum observed load power on the half production for renewables. The simulation results and processed data for creating the source code are also provided on the database available at http://dx.doi.org/10.7910/DVN/1I6MKU.