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The integration of volatile distributed energy resources (DERs) brings new challenges for the active distribution network maintenance scheduling (DN-MS). Conventionally, the DN-MS is formulated as a deterministic optimization model without considering the uncertainties of DERs. In this paper, the DN-MS is formulated as a multistage stochastic optimization problem, which is cast as a stochastic mixed-integer nonlinear programming model. It aims to reduce the total maintenance cost constrained by the reliability indices. To capture the operational characteristics of active distribution networks, the uncertainties of DERs and post-outage operation strategies of switching devices are incorporated into the model. In general, this type of model is intractable and mainly solved by heuristic search methods with low efficiency. Recently, Monte-Carlo tree search (MCTS) is emerging as a scalable and promising reinforcement learning approach. We propose a stochastic MCTS solution to this problem. In the tree search procedure, a sample average approximation technique is developed to estimate multistage maintenance costs considering uncertainties. To speed up the MCTS, the complicated constraints of the original problem are transformed to penalty or heuristics functions. This approach can asymptotically approximate the optimum with promising computation efficiency. Numerical test results demonstrate the superiority of the proposed method over benchmark methods. [ABSTRACT FROM AUTHOR]

This paper formulates a block-layer method for the reliability assessment of distribution systems. The characteristics of the method include: 1) identifying the impact of distribution component reliability on the system and load points using a block-layer structured assessment; 2) incorporating time-dependent failure parameters; and 3) taking account of the topological, seasonal, and meteorological features of the distribution systems under analysis. The proposed method first identifies the three critical parts of the distribution system: main supply, feeder, and secondary substation. It can also include reserve connections and distributed generation. Second, the method frames these parts into the layered structure, each corresponding to the zone of total load curtailment. To verify this reliability technique, this paper simulates distribution feeders assembled in a number of topologies and compares them with the state sampling technique. Data provided by the local utility company are processed to model the equipment and load for the base year. The results show that the proposed method can provide a wide range of partial and system indices. These values assist in the identification of parts of the distribution system and scenarios with low reliability and to determine possible remedial actions. [ABSTRACT FROM AUTHOR]

Microgrids are able to provide a coordinated integration of the increasing share of distributed generation (DG) units in the network. The primary control of the DG units is generally performed by droop-based control algorithms that avoid communication. The voltage-based droop (VBD) control is developed for islanded low-voltage microgrids with a high share of renewable energy sources. With VBD control, both dispatchable and less-dispatchable units will contribute in the power sharing and balancing. The priority for power changes is automatically set dependent on the terminal voltages. In this way, the renewables change their output power in more extreme voltage conditions compared to the dispatchable units, hence, only when necessary for the reliability of the network. This facilitates the integration of renewable units and improves the reliability of the network. This paper focusses on modifying the VBD control strategy to enable a smooth transition between the islanded and the grid-connected mode of the microgrid. The VBD control can operate in both modes. Therefore, for islanding, no specific measures are required. To reconnect the microgrid to the utility network, the modified VBD control synchronizes the voltage of a specified DG unit with the utility voltage. It is shown that this synchronization procedure significantly limits the switching transient and enables a smooth mode transfer. [ABSTRACT FROM PUBLISHER]

This second part of a two-part paper presents the implementation and simulations of a risk-based optimization approach for distribution expansion planning with distributed generation (DG), as described in Part I. The proposed approach is first applied to a test system in order to test convergence of the optimization algorithm and then comparing its numerical results with the ones from the exhaustive method. Later, the expansion planning of a typical Latin American distribution network is assessed and analyzed. For this, two expansion optimizations are performed: one, taking into account traditional expansion alternatives (without DG) and, the other, considering DG as flexible expansion options. Finally, the computational effort is analyzed. Results show that the greatest contribution of DG lies in the flexibility it gives to expansion planning, mainly by deferring network reinforcements. [ABSTRACT FROM PUBLISHER]