Demonstration of INTElligent grid technologies for renewables INTEgration and INTEractive consumer participation enabling INTEroperable market solutions and INTErconnected stakeholders
Smarter Grid: Empowering SG Market Actors through Information and Communication Technologies
Digitalização da rede de distribuição - evolução da arquitetura de automação da rede de distribuição
Estudos destinados a dimensionar e definir requisitos técnicos para um sistema de armazenamento de energia para a ilha de Santa Maria e requisitos de ligação para sistemas de produção renovável eólica e solar fotovoltaica a ligar à rede
MARKET ENABLING INTERFACE TO UNLOCK FLEXIBILITY SOLUTIONS FOR COST-EFFECTIVE MANAGEMENT OF SMARTER DISTRIBUTION GRIDS
Bessa, R; Sampaio, G; Miranda, V; Pereira, J;
2018 Power Systems Computation Conference (PSCC)
Sampaio, GS; Saraiva, JT; Sousa, JC; Mendes, VT;
International Conference on the European Energy Market, EEM
This paper describes an approach to the short term operation planning of hydro stations in market environment. The developed approach is based on the solution of an optimization problem to maximize the profit of a generation agent along a planning period discretized in hourly steps using a Genetic Algorithm. This problem includes the possibility of pumping since this is an important resource in the scope of electricity markets. The scheduling problem was developed starting with an initial simplified version in which the head loss is neglected and the head is assumed constant. Then, it was implemented a second model in which the nonlinear relation between the head, the hydro power and the water discharge is retained and finally an approach in which the hydro schedule obtained in a given step is used to update the hourly electricity prices used to compute the profit of the generation agent. The short term hydro scheduling problem is illustrated using two Case Studies - the first one was designed to run a set of initial tests to the developed algorithm and the second one refers to a set of hydro stations that mirrors a cascade of 8 stations in Portugal. © 2013 IEEE.
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