Abstract

Implementation of distributed energy resources (DERs) has led to a decrement in the cost of supplying demand in distribution networks. Integration of DERs in the forms of micro-grids (MGs) is a solution to enhance the operation of these resources in the low voltage networks. To meet the demand by MG operator, both technical and economic characteristics as well as the prices offered by retailers are considered to schedule DERs optimally. In these networks, the profit of retailers is maximized by power trading with MGs and optimally purchasing the energy from wholesale markets. Due to the existence of several retailers and MGs in active distribution networks (ADNs), hierarchical decision-making frameworks are needed to model their operation problem. For this purpose, a bi-level optimization technique is proposed in this paper to model the operation problem of retailers and MGs as decision-making variables in distribution networks in the upper and lower levels, respectively. To solve the proposed model, multi-objective particle swarm optimization (MOPSO) algorithm is used. The proposed model and its solution method are applied to a hypothetical distribution network with several retailers and MGs to validate the theories and discussions. Numerical results show that the maximum capacity of DG and the amount of demand have an important effect on this decision and the prices of purchased power from wholesale markets determine the amount of retailers’ offers to MGs.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.