A comprehensive strategy for optimizing demand side management in smart grid systems, using both forecasting techniques and advanced metering infrastructure frameworks

The use of Advanced Metering Infrastructures (AMI) in Smart Grid (SG) has allowed customers to engage in Demand-Side Monitoring (DSM) via the utilization of price-based Demand Response (DR) schemes provided by Distribution Companies (DC). By adopting this approach, both customers lower their energy costs and comfort, while DCs can effectively manage high electricity demand and mitigate carbon (CO2) emissions in a regulated manner. Developing an optimization framework to optimize cost, demand during peak hours, waiting time, and CO2 emission is a challenging endeavor and a priority for DSM. Most evaluations focus on minimizing costs and the Peak-to-Average Ratios (PAR). However, the efficacy of the DSM system is also influenced by customer satisfaction and the reduction of CO2 emissions. This study effectively develops a unique DSM Framework (DSMF) including four devices: (i) DC, (ii) Multi-Layer Perceptron (MLP) based prediction engine, (iii) AMI, and (iv) demand-side energy management components. The simulation outcomes clearly illustrate the efficacy of our suggested approach in surpassing all benchmark models and achieving both consumer and DC goals.

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