The document presents a hierarchical decentralized network reconfiguration approach to minimize power losses in smart distribution systems. It applies the proposed approach to four test distribution systems and compares the results to existing centralized and harmony search methods. The decentralized approach can achieve similar results as other methods with significantly reduced computation time. It also studies the impacts of time-varying loads and faults through dynamic network reconfiguration on a 118-bus test system. Simulation results show the optimal configuration for each operating period can significantly reduce energy losses.

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Hierarchical Decentralized Network Reconfiguration for Smart
Distribution Systems—Part II: Applications to Test Systems
Abstract
A hierarchical decentralized network reconfiguration approach to minimize power losses for
smart distribution systems was presented in Part I. In this paper, the proposed approach is
applied to four test distribution systems to examine its performance. A demonstration system
consisting of the test system and distributed intelligent agents is built using
MATLAB/Simulink to illustrate how the decentralized approach is implemented. Simulation
results of the proposed approach are then compared with results of a centralized
implementation and the harmony search method. It is shown that the decentralized approach
can achieve similar results as other methods with significantly reduced computation time.
The impacts of time-varying loads and faults are also studied through dynamic network
reconfiguration on the 118-bus test system. Simulation results illustrate that dynamic network
reconfiguration with time-ahead planning can determine the optimal configuration for each
operating period to significantly reduce system energy losses. The enhanced performance of
the hierarchical decentralized approach is clearly established.
Existing method
 Centralized implementation and the harmony search method are the existing methods.
 Different methods of network reconfiguration are existing methods.
Disadvantagesofexisting method
The heuristic approach cannot guarantee global optimality of a solution in a centralized
implementation and can only ensure that a solution is optimal during the operation of a given
loop.
Proposedmethod
The hierarchical decentralized network reconfiguration method to minimize power losses for
smart distribution systems is proposed.
Block diagramof the proposed method

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Advantages of proposed method
 Network decomposition and a multi-agent architecture to obtain the optimal
configuration, and the computation time for obtaining the optimal configuration can be
greatly reduced. Although multiple agents exist, the necessary information exchange
among them is limited to switch states in their own systems, so the burden of
communication and information transfer is quite reasonable.
 For the decentralized method, each decomposed system is reconfigured using the
heuristic approach based on a two-stage methodology, and the solution obtained for each
system is locally optimal, not necessarily globally optimal.
 The hierarchical decentralized approach is a promising option with reasonable tradeoffs
between efficiency and accuracy in view of an increasing emphasis on implementing real-
time distribution system automation.
Designing and software tools used
MATLAB/Simulink
Conclusion
Moreover, although multiple agents exist, the necessary information exchange among them is
limited to switch states in their own systems, so the burden of communication and
information transfer is quite reasonable. Simulation results of four test systems including both
balanced and unbalanced ones show that the proposed approach can converge to an “optimal”
solution with good accuracy and with reduced computational time as compared with other
methodsWith the implementation of the demonstration system built using
MATLAB/Simulink, dynamic network reconfiguration is also simulated to study the impacts
of time-varying loads, fluctuating generation from PV units and faults on the results of
network reconfiguration. The sensitivity of power losses with respect to the load power at
each bus is computed, and the most positive sensitive buses are chosen to connect the PV
units so that largest power loss reductions can be achieved. Simulation results have shown
that the “optimal” topology for each operating window is successfully obtained, and total

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energy losses are greatly reduced after reconfiguration. It is also observed that the
implementation of time-ahead planning can help achieve more energy loss reductions. In
addition, the reconfiguration results for the scenario when faults occur are also given. The
focus of the paper is on finding the “optimal” configuration of the system at steady state, and
the dynamic behaviours and constraints of the system during faults are not within the scope
of the present study. In addition, with the application of multi-agent for solving the
decentralized optimization problems, only the lowest layer agents are initially activated in
response to any changes that occur in an operating window and the computations in the
upper-layer agents are not necessarily needed, provided a much faster response to time-
varying loads and DGs, as well as contingencies and disturbances. This feature is significant
for long-term operations, which enhances the contribution of the proposed approach. Verified
the accuracy and efficiency of the proposed hierarchical decentralized approach for network
reconfiguration, suggesting that the proposed approach is a good choice for applications in
future distribution systems.