DC microgrid power flow optimization by multi-layer supervision control. Design and experimental validation - Archive ouverte HAL Access content directly
Journal Articles Energy Conversion and Management Year : 2014

DC microgrid power flow optimization by multi-layer supervision control. Design and experimental validation

, , , (1, 2)
1
2

Abstract

Urban areas have great potential for photovoltaic (PV) generation, however, direct PV power injection has limitations for high level PV penetration. It induces additional regulations in grid power balancing because of lacking abilities of responding to grid issues such as reducing grid peak consumption or avoiding undesired injections. The smart grid implementation, which is designed to meet these requirements, is facilitated by microgrids development. This paper presents a DC microgrid (PV array, storage, power grid connection, DC load) with multi-layer supervision control which handles instantaneous power balancing following the power flow optimization while providing interface for smart grid communication. The optimization takes into account forecast of PV power production and load power demand, while satisfying constraints such as storage capability, grid power limitations, grid time-of-use pricing and grid peak hour. Optimization, whose efficiency is related to the prediction accuracy, is carried out by mixed integer linear programming. Experimental results show that the proposed microgrid structure is able to control the power flow at near optimum cost and ensures self-correcting capability. It can respond to issues of performing peak shaving, avoiding undesired injection, and making full use of locally produced energy with respect to rigid element constraints.
Not file

Dates and versions

hal-01175798 , version 1 (13-07-2015)

Identifiers

Cite

Manuela Sechilariu, Bao Chao Wang, Fabrice Locment, Antoine Jouglet. DC microgrid power flow optimization by multi-layer supervision control. Design and experimental validation. Energy Conversion and Management, 2014, 82, pp.1-10. ⟨10.1016/j.enconman.2014.03.010⟩. ⟨hal-01175798⟩
128 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More