Non-utility owned distributed energy resources (DERs) are mostly untapped currently, but they can provide many grid services such as voltage regulation and service restoration, if properly controlled, and can improve the distribution system's reliability when coordinated with utility-owned assets such as self-healing control and microgrids. This paper integrates transactive energy control into the distribution system reliability evaluation to quantitatively assess the impact of non-utility owned DERs on reliability improvement. A transactive reactive power control strategy is designed to incentivize the DERs to provide reactive power support for improving voltage profiles thus enabling additional customer load restoration during an outage. Also, an operational sequence to coordinate the non-utility owned DERs with the utility owned self-healing control and utility owned microgrids is designed and integrated into the service restoration process with the operational constraints guaranteed by checking the three-phase unbalanced power flow for post-fault network reconfiguration. The reliability indices are then calculated through a Monte Carlo simulation. The transactive reactive power control strategy is tested on a four-feeder distribution system operated by Duke Energy in the U.S. Results demonstrate that the non-utility owned DERs with the transactive control improve the reliability of both the system and critical loads by more than 30%.

A new microgrid scheduling model with resiliency guaranteed under the risk of both utility failure and prevailing uncertainties of renewable generation and load is proposed in this paper. The proposed model minimizes the overall operating cost of the microgrid by efficiently coordinating the power supply from local distributed energy resources and the main grid. The resiliency is ensured by maintaining certain amount of flexibility in local distributed energy resources, which can be quickly deployed to keep the power supply uninterrupted whenever the utility grid suddenly goes down. In addition, the uncertainties of renewable generation and load are captured with the proposed two-stage robust optimization model. By solving the proposed optimization, the solution not only guarantees the resiliency of the microgrid by supporting possible islanding incidents without load interruption, but also ensures robustness against the randomness of renewable generation and load. Results of case studies on a typical microgrid demonstrate the effectiveness of the presented robust microgrid scheduling model.

This paper proposed an distributed energy management for modern distribution systems with various actively interfaced participants, such as distributed energy resources (DERs), flexible loads, and different kinds of microgrids. Given different ownerships, objectives, requirements on autonomy and data privacy, a multi-objective optimization model considering various network operational objectives and constraints was formulated to coordinated the operation of all active participants for better economics and/or system operator preferred performances. The formulated optimization problem was iteratively solved in a distributed way using the alternating direction method of multipliers (ADMM) algorithm. For each iteration, all participants could adjust their schedules based on their own objectives and the price and nodal unbalance signals received. Then, the distribution management system (DMS) updates the nodal price signals according to the generation-load unbalance at the corresponding bus calculated using the previously updated schedules of all participants. The updated price and nodal unbalance signals are distributed to participants on corresponding buses for another iteration until the calculated generation-load unbalance of all buses are small enough, i.e., power balance is achieved at each bus under updated price signals. In addition, the analytical hierarchy process (AHP) was employed to determine the corresponding weighting coefficients of different objectives. The validity of proposed method is verified by simulations on a modern distribution systems with several actively interfaced microgrids, DERs and flexible loads. The effects of weighting coefficients on the obtained solution as well as convergence of ADMM are also investigated.

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply.

Load unbalance in electric distribution systems is unavoidable. Unbalanced load currents will lead to negative sequence (NS) voltages that may damage electric equipment. Unbalanced power flow analysis is a common tool to detect and mitigate NS voltage issues and requires accurate models of grid components. While traditional source models are available, grid-forming (GFM) inverter models are not well developed. GFM inverters implement various control strategies, which affect their power flow models. In this article, a novel GFM inverter model considering control effects is proposed. We show that for some control methods, unbalanced system loading will lead to unbalanced terminal voltages of the GFM inverters, which are modeled through an equivalent negative sequence impedance. The proposed models are initially validated using a simple test circuit. Then, they are applied in the power flow analysis on the IEEE 13-bus and 34-bus systems to demonstrate the accuracy improvement over the state-of-the-art. Using time-domain simulations as benchmarks, we show that the proposed models reduce the calculation error of negative sequence voltages by at least 25% in unbalanced distribution systems.