Abstract

With the ever-intensive utilization of distributed generators (DGs) and smart devices, distribution networks are evolving from a hierarchal structure to a distributed structure, which imposes significant challenges to network operators in system dispatch. A distributed energy-management method for a networked microgrid (NM) is proposed to coordinate a large number of DGs for maintaining secure and economic operations in the electricity-market environment. A second-order conic programming model is used to formulate the energy-management problem of an NM. Network decomposition was first carried out, and then a distributed solution for the established optimization model through invoking alternating-direction method of multipliers (ADMM). A modified IEEE 33-bus power system was finally utilized to demonstrate the performance of distributed energy management in an NM.

Highlights

  • For a geographically dispersed networked microgrid (NM) including a variety of dispatchable distributed generators (DGs), the centralized approach requires significant investment

  • Constraints (3)–(13), and is a nonconvex optimization model that is theoretically intractable for attaining a global optimum, especially for a large-scale problem with numerous decision variables resulting from extensive controllable devices in an NM

  • Note that the above second-order cone (SOC) relaxation is deemed exact for most actual power-distribution networks [3]

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Summary

Multiplier Method

Changsen Feng 1 , Fushuan Wen 2,3, *, Lijun Zhang 4 , Chenbo Xu 4 , Md. Abdus Salam 5 and. Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam. Received: 16 August 2018; Accepted: 12 September 2018; Published: 25 September 2018

Motivation
Literature Review
Contributions
Mathematical Formulation
Objective Function
Constraints
Second-Order Cone Relaxation
Solution Methodology
ADMM Algorithm
Overall Solution Framework
Case Studies
Simulation Data
Results
Voltage
Convergence Analysis
Conclusions
Full Text
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