Enhancement of loadability and voltage stability in grid-connected microgrid network

- The implementation of demand response programs in microgrid network applications enables end-consumers to participate in active load shaping, peak shaving, and supply-demand balancing activities. However, the impact of demand response programs on microgrid performance subjected to renewable energy intermittency, network flow constraints, loadability, and voltage stability is not acknowledged to the full extent. To cover this research gap, a tri-level stochastic framework is proposed to enhance the grid-connected microgrid performance in terms of loadability, voltage stability, and optimal scheduling. At the first level, a stochastic scenario-based approach deals with the intermittency of renewable sources. The interdependency of loading level on voltage profile is investigated in level two, implementing utility-oriented and customer-oriented demand-side management schemes. Unlike most previous research, flexible price elasticity-based incentive-driven and price-driven demand response programs are implemented to shape the load demand. Moreover, four distinct seasonal load profiles were considered: summer, winter, spring, and fall. Finally, the recently reported nature-inspired Harris Hawk Optimizer is incorporated in level three to optimize the costs and enhancement of microgrid loadability. The enhanced version of the IEEE 69 bus radial distribution network has been implemented and analyzed to demonstrate the effectiveness of the proposed tri-level framework. The obtained simulation results show that the voltage profile is enhanced by 6.58%, and microgrid loadability is improved by 34.64%. The significance of the proposed work to attain sustainable development goals and various practical insights for the benefit of multistakeholder is also discussed.

Automated summary

A tri-level stochastic framework is proposed to enhance the performance of grid-connected microgrids. The framework addresses the intermittency of renewable sources, investigates the impact of loading level on voltage profile, and optimizes costs and loadability using the Harris Hawk Optimizer.