Virtual power plants: Stochastic techniques for effective costing and participation in a decentralized electricity network in Nigeria

As calls for increased government incentives for easy access to renewable energy technologies and favourable government policies mount, so also are there increased calls for a decentralized approach to electricity generation in the country. These calls are hinged upon the fact that conventional means of electricity generation coupled with their unsavoury effect on the climate and the environment pose serious threats to man´s livelihood. These calls opine and strongly support existing views that attention be turned to renewable energy sources (RES) in a bid to reducing our dependence on fossils in generating electricity. In making these proposals, schemes such as small scale energy zones (SSEZ) and virtual power plants (VPPs) have been proposed. Another reason for such calls on decentralizing electricity generation is the fact that it allows for private participation. Realizing the effect such free market economy could have on private owners of distributed generation (DG) units, we have come up with a model which seeks to optimize the contribution of each DG unit in a two tier system. In this paper therefore, we seek to incorporate the commercial virtual power plant (CVPP) and the technical virtual power plant (TVPP) in creating a template that seeks to encourage participation of each DG unit and also cater for network constraints using genetic algorithm (GA) as a stochastic tool.