A renewable energy grid daily pricing model for consumer

A Renewable Smart Energy Grid is a global challenge which has to address varied complex issues. In response to this challenge, we present an algorithm for Real-Time Price Suggestion (RTPS) that allows for utilisation within the Smart Grid (SG). Our model achieves a complex optimization of the personal (individual) energy needs of a consumer and minimization of their energy costs. As the SG represents a bidirectional grid the RTPS manages the balance between energy consumer need and a provider to optimize cost savings via a Demand Response (DR) model. The RTPS was designed and validated using real energy network data and has demonstrated that energy consumers can reduce their energy expenditure. Our model integrates the following metrics; Price Suggestion Unit (PSU), Price Control Unit (PCU), Smart Meter (SM) data and along with user appliances, the proposed Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm which varies prices on the basis of a users’ consumption. Thus, we believe that the RTPS algorithm accommodates users’ preferences and non-responsiveness in order to save their energy cost, thereby, safeguarding individual consumer rights and users’ social welfare.