E‐SOP's contribution in a techno‐economic and clean operation of distribution networks: A multi‐objective optimization approach based on linear models. (2nd December 2019)

• Record Type: Journal Article
• Authors: Baghban‐Novin, Salar; Hamidi, Amir; Golshannavaz, Sajjad; Nazarpour, Daryoush
• Is Part Of: International transactions on electrical energy systems. Volume 30:Number 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-02
• Subjects: day‐ahead scheduling -- distribution network -- energy management -- optimal operation -- renewable energy -- soft open point -- volt/VAr -- voltage control; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.12235
• Languages: English
• ISSNs: 2050-7038

Abstract

Summary: In modern distribution networks (DNs), soft open points (SOPs) are newly introduced power electronic devices that are installed between the adjacent feeders in place of normally open points. The SOPs contribute in Volt/VAr control by accurately adjusting the active power flow and supporting the reactive power from both AC sides. A further step forward alludes to energy storage–integrated SOPs, referred to as E‐SOP, which could significantly influence the active power exchanges through charge/discharge actions in appropriate time intervals, say as the hours with high‐ and low‐price electricity tariffs. Accordingly, E‐SOPs provide a unique opportunity in effective active power control and also Volt/VAr control in the presence of distributed generations (DGs) and renewables. This study proposes a model for day‐ahead operation scheduling of DNs with high penetration of DGs and photovoltaic (PV) considering the installations of E‐SOPs. An accurate linearized model is developed to consider the technical performance of E‐SOP in power flow study. Voltage security, economic, and network emission indices are accounted as a concern of the network operator. To this end, a multi‐objective optimization model is developed based on mixed‐integer linear programming being tackled by an augmented ε‐constraint method. For assessing the effectiveness of the developed model, it is simulated on the IEEE 33‐node test system; however, the IEEE 119‐node test system is also tailored to assess the scalability issues. The obtained results are mainly represented in terms of smart charge/discharge and effective VAr support of E‐SOPs, reduced operation cost, improved voltage profile, and a reduced emission level.