Solution to uncertainty of renewable energy sources and peak hour demand in smart grid system

Abstract

Today's need for environmental sustainability prompted the smart grid to incorporate more renewable energy sources. Reducing the operational costs of power generation and emission dispatch can both be accomplished with the integration of renewable energy sources. A power system is made to manage the fluctuating nature of loads for a brief time, nevertheless. However, new difficulties arise for utilities as a result of the fluctuation and uncertainty associated with renewable sources. Another problem faced by generating plants is network reliability issues arising from the peak hour's power demand in the power system. Application of demand response technology with the help of smart meters connected at consumers' end in smart cities can help to ease the enormous peak-hour pressure on power generating units. But a hybrid power system integrated with a storage system faces the challenge of optimal utilization of the battery under uncertainties caused by intermittent generation of power and dynamic demand. This research work proposes a real-time price based hidden Markov model and an enhanced demand response technique to solve these issues in a hybrid power system. Proposed model is tested on IEEE 30-bus system with/without renewable energy sources and implemented grasshopper optimization algorithm for optimal scheduling of generating units.

Keywords

• Demand response
• Dynamic programming
• Energy management
• Renewable energy generation
• Storage system