Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
Hierarchical hybrid power supply networks
Proceedings of the 47th Design Automation Conference
Hybrid electrical energy storage systems
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Charge migration efficiency optimization in hybrid electrical energy storage (HEES) systems
Proceedings of the 17th IEEE/ACM international symposium on Low-power electronics and design
Charge allocation for hybrid electrical energy storage systems
CODES+ISSS '11 Proceedings of the seventh IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Battery management for grid-connected PV systems with a battery
Proceedings of the 2012 ACM/IEEE international symposium on Low power electronics and design
Hi-index | 0.00 |
Integrating residential photovoltaic (PV) power generation and electrical energy storage (EES) systems into the Smart Grid is an effective way of utilizing renewable power and reducing the consumption of fossil fuels. This has become a particularly interesting problem with the introduction of dynamic electricity energy pricing models since electricity consumers can use their PV-based energy generation and EES systems for peak shaving on their power demand profile from the grid, and thereby, minimize their electricity bill. Due to the characteristics of a realistic electricity price function and the energy storage capacity limitation, the control algorithm for a residential EES system should accurately account for various energy loss components during operation. Hybrid electrical energy storage (HEES) systems are proposed to exploit the strengths of each type of EES element and hide its weaknesses so as to achieve a combination of performance metrics that is superior to those of any of its individual EES components. This paper introduces the problem of how best to utilize a HEES system for a residential Smart Grid user equipped with PV power generation facilities. The optimal control algorithm for the HEES system is developed, which aims at minimization of the total electricity cost over a billing period under a general electricity energy price function. The proposed algorithm is based on dynamic programming and has polynomial time complexity. Experimental results demonstrate that the proposed HEES system and optimal control algorithm achieves 73.9% average profit enhancement over baseline homogeneous EES systems.