TY - GEN

T1 - A novel mathematical modeling approach to the electric dispatch problem

T2 - 2013 IEEE Congress on Evolutionary Computation, CEC 2013

AU - Marcelino, Carolina G.

AU - Wanner, Elizabeth F.

AU - Almeida, Paulo E.M.

PY - 2013/7/15

Y1 - 2013/7/15

N2 - Nowadays, the population growth and economic development causes the need for electricity power to increase every year. An unit dispatch problem is defined as the attribution of operational values to each generation unit inside a power plant, given some criteria to be obeyed like the total power to be generated, operational bounds of these units etc. In this context, an optimal dispatch programming for hydroelectric units in energy plants provides a bigger production of electricity to be generated with a minimal water amount. This paper presents an optimization solution for hydroelectric generating system of a plant, using Differential Evolution algorithms. The novel mathematical model proposed and validation of the obtained algorithms will be performed with practical simulation experiments. Throughout the text, the equations and models for the system simulation will be fully described, and the experiments and results will be objectively analysed through statistical inference. Simulation results indicate savings of 6.5 million litres of water for each month of operation using the proposed solution.

AB - Nowadays, the population growth and economic development causes the need for electricity power to increase every year. An unit dispatch problem is defined as the attribution of operational values to each generation unit inside a power plant, given some criteria to be obeyed like the total power to be generated, operational bounds of these units etc. In this context, an optimal dispatch programming for hydroelectric units in energy plants provides a bigger production of electricity to be generated with a minimal water amount. This paper presents an optimization solution for hydroelectric generating system of a plant, using Differential Evolution algorithms. The novel mathematical model proposed and validation of the obtained algorithms will be performed with practical simulation experiments. Throughout the text, the equations and models for the system simulation will be fully described, and the experiments and results will be objectively analysed through statistical inference. Simulation results indicate savings of 6.5 million litres of water for each month of operation using the proposed solution.

KW - Differential Evolution Algorithms

KW - Optimization

KW - Simulation

UR - http://www.scopus.com/inward/record.url?scp=84881574627&partnerID=8YFLogxK

UR - https://ieeexplore.ieee.org/document/6557597

U2 - 10.1109/CEC.2013.6557597

DO - 10.1109/CEC.2013.6557597

M3 - Conference publication

AN - SCOPUS:84881574627

SN - 9781479904549

T3 - 2013 IEEE Congress on Evolutionary Computation, CEC 2013

SP - 400

EP - 407

BT - 2013 IEEE Congress on Evolutionary Computation, CEC 2013

PB - IEEE

Y2 - 20 June 2013 through 23 June 2013

ER -