A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration
Abstract
:1. Introduction
1.1. Motivations
1.2. Literature Review
- (a)
- Different parts of the power system: PSR needs to be carried out in different types of power systems and at different levels. In [13], the restoration of the transmission system with the goal of finding an appropriate sequence of actions to minimize the size of the blackout over time is presented. To solve the restoration ordering problem (ROP), the DC model and the linear programming approximation of AC (LPAC) power flow are used, and it is shown that the DC model is not sufficiently accurate to solve the ROP. In contrast, the LPAC power flow model is sufficiently accurate to obtain the restoration plans. In [14], the PSR is stated as a multi-objective, multi-variable, and multi-constrained nonlinear optimization problem and a multi-objective model based on the combination of the multi-agent technology and Tabu search method (TSM) is proposed for the restoration of the transmission system. Some of the studies investigate the restoration of the distribution system. In [15], by using the genetic algorithm (GA), the switching operation is minimized during the restoration process. It also reduces the required calculations time. The capabilities of the distributed generations (DGs) in distribution systems are used in [16] to minimize the restoration time and maximize the amount of restored loads.
- (b)
- (c)
- (d)
1.3. Contributions
1.4. Paper Organization
2. Microgrid Control Structure for Black Start
3. Modeling of the Microgrid Components
3.1. Microsource Modeling
3.2. Converter Modeling
4. Proposed Decentralized Approach
4.1. Mathematical Background
4.1.1. Distributed Averaging
4.1.2. Coefficient Setting
4.2. General Assumptions
4.3. Information Sharing Process
4.4. Implementation of the Proposed Multi-Agent Based Approach for MG Restoration
- Step 1:
- Initialization: in this step, the local initial information matrix of each agent () is formed.
- Step 2:
- Information sharing: in this step, each agent receives the information of its neighboring agents through a communication link and updates its information by using the ACA. After reaching the consensus, the common decision will be made.
- Step 3:
- Decision making: when the agents reach the consensus in the sharing information process, a proper decision will be made. Decision making is one of the crucial parts of the agents’ function blocks. This block must be designed to meet the initial restoration steps such as setting up the generation units with black start capability and energizing the restoration path. Moreover, in the next steps, this block must determine a proper sequence for connection of disconnected loads and generation units by providing the maximum amount of the restored loads in the shortest possible time.
Decision Making Process
5. Simulation Results and Discussion
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Steps | Actions | time |
---|---|---|
Step 1 | Connection of microturbine | t = 1 s |
Step 2 | Connection of three apartment buildings at bus 4 | t = 5 s |
Step 3 | Connection of wind turbine | t = 9 s |
Step 4 | Connection of one apartment building at bus 4 | t = 13 s |
Connection of motor load | ||
Connection of one of the residence groups at bus 6 | ||
Step 5 | Connection of fuel cell | t = 17 s |
Step 6 | Connection of three remaining residences at bus 6 | t = 21 s |
Step 7 | Connection of PVs | t = 25 s |
Step 8 | Connection of one apartment building at bus 9 | t = 29 s |
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Rokrok, E.; Shafie-khah, M.; Siano, P.; Catalão, J.P.S. A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration. Energies 2017, 10, 1491. https://doi.org/10.3390/en10101491
Rokrok E, Shafie-khah M, Siano P, Catalão JPS. A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration. Energies. 2017; 10(10):1491. https://doi.org/10.3390/en10101491
Chicago/Turabian StyleRokrok, Ebrahim, Miadreza Shafie-khah, Pierluigi Siano, and João P. S. Catalão. 2017. "A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration" Energies 10, no. 10: 1491. https://doi.org/10.3390/en10101491