Optimal control of a grid-connected hybrid electrical energy storage system for homes

  • Authors:
  • Yanzhi Wang;Xue Lin;Massoud Pedram;Sangyoung Park;Naehyuck Chang

  • Affiliations:
  • University of Southern California, Los Angeles, CA;University of Southern California, Los Angeles, CA;University of Southern California, Los Angeles, CA;Seoul National University, Seoul, Korea;Seoul National University, Seoul, Korea

  • Venue:
  • Proceedings of the Conference on Design, Automation and Test in Europe
  • Year:
  • 2013

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Abstract

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.