A day-ahead market-clearing model is proposed for smart distribution systems in this paper. Various types of distributed energy resources (DERs), such as distributed energy storage, distributed generators, microgrids, and load aggregators, can bid into the day-ahead distribution-level market. Considering system Volt/VAR control, network reconfiguration and interactions with the wholesale market, an optimization model is built to clear the day-ahead market, through which the distribution locational marginal pricing (DLMPs) for both active power and reactive power are determined. Through derivations of the Lagrangian function and sensitivity factors, DLMPs are decomposed to five components, i.e., marginal costs for active power, reactive power, congestion, voltage support, and loss, which provide price signals to motivate DERs to contribute to congestion management and voltage support. Finally, case studies demonstrate the effectiveness of the proposed method.

In order to solve the voltage violation problem caused by high penetration of photovoltaic (PV) units in distribution power networks, this paper proposes a double-layer voltage control strategy based on the distribution network partition. By optimizing the active and reactive power outputs of PV units, the minimization objective of PV active power curtailment and network active power loss can be achieved. In the basis of community detection algorithm, a novel cluster performance index based on the electrical distance and regional voltage regulation capability is presented to partition a distribution network into several clusters. The proposed double-layer voltage control strategy combines the cluster autonomous optimization and distributed inter-cluster coordination optimization in different time scales. The cluster autonomous optimization can eliminate intra-cluster voltage violation rapidly by alternately updating the intra-cluster optimal solution and the virtual slack bus voltage. The distributed inter-cluster coordination optimization with a long-time scale is based on the alternating direction method of multipliers (ADMM) and realizes global optimal control through finite boundary data exchange among adjacent clusters. The effectiveness and feasibility of proposed method have been demonstrated via simulation tests on a real 10.5kV feeder in China and the IEEE 123-bus system.

Distributed generators (DGs) including photovoltaic panels (PVs) have been integrated dramatically in active distribution networks (ADNs). Due to the strong volatility and uncertainty, the high penetration of PV generation immensely exacerbates the conditions of voltage violation in ADNs. However, the emerging flexible interconnection technology based on soft open points (SOPs) provides increased controllability and flexibility to the system operation. For fully exploiting the regulation ability of SOPs to address the problems caused by PV, this paper proposes a robust optimization method to achieve the robust optimal operation of SOPs in ADNs. A two-stage adjustable robust optimization model is built to tackle the uncertainties of PV outputs, in which robust operation strategies of SOPs are generated to eliminate the voltage violations and reduce the power losses of ADNs. A column-and-constraint generation (C&CG) algorithm is developed to solve the proposed robust optimization model, which are formulated as second-order cone program (SOCP) to facilitate the accuracy and computation efficiency. Case studies on the modified IEEE 33-node system and comparisons with the deterministic optimization approach are conducted to verify the effectiveness and robustness of the proposed method.

The asymmetric integration of distributed generators (DGs) exacerbates the three-phase unbalanced condition in distribution systems. The serious unbalanced operation causes inefficient utilization of network assets and security risks in the system. Soft open point (SOP) is a flexible power electronic device which can achieve accurate active and reactive power flow control to balance the power flow among phases. This paper proposes an SOPs-based operation strategy for unbalanced active distribution networks. By regulating the operation of SOPs, the strategy can reduce power losses and simultaneously mitigate the three-phase unbalance of the upper-level grid. Semidefinite programming (SDP) relaxation is advocated to convert the original non-convex, nonlinear optimization model into an SDP formulation, which can be efficiently solved to meet the requirement of rapid adjustment. Case studies are conducted on the modified IEEE 33-node and IEEE 123-node distribution system to verify the effectiveness and efficiency of the proposed strategy.

A novel frequency control method based on double sliding mode (SM) controllers is proposed for isolated micro-grids with renewable sources. In the presented technique, the SM pitch angle controller is designed for wind turbine generator (WTG) system to smooth wind power output. The SM load frequency controller (LFC) is constructed for diesel generator system to restore system frequency to normal through the secondary frequency regulation. Then the adaptive SM LFC is redesigned by taking advantage of the disturbance observer and adaptive law to improve dynamic performance of the diesel generator system. The proposed strategy is tested in a typical isolated hybrid micro-grid with both PV and WTG.

An observer-based dc voltage droop and current feed-forward control for a dc microgrid has been proposed in this paper. With the proposed control scheme, dynamic response of dc voltage control can be improved effectively through using an observer. Moreover, the feedback current for dc voltage droop and the feed-forward current are both obtained from the observer without additional current measurement. Furthermore, system stability analysis shows that, the propose method has enhanced robustness and stability when compared to the traditional droop method under variations of system parameters, such as loads, cable impedances, and droop control gains. In a droop controlled dc microgrid, there exists a trade-off between the load demand sharing accuracy (which needs a high droop gain) and stability (which limits the droop gain). With the above mentioned advantages, the proposed method can effectively address this trade-off in such a system. The effectiveness of the proposed method is verified by experiments in a laboratory dc microgrid with two boost dc-dc converters based distributed generations and a buck type constant power dc load.