The wind turbines (WTs) present in a wind farm (WF) are subjected to varying wind speeds owing to the wake effect. Additionally, the response of a WF is also affected by the low voltage ride-through (LVRT) characteristic imbibed in each doubly-fed induction generator (DFIG) of WF. Consequently, for deriving an equivalent of a large WF, consideration of wake effect and LVRT are crucial. In this paper, a three-step WF aggregation is proposed. Firstly, various wind scenarios from historical wind data are taken, and the Weibull-based probabilistic and wake effect models are developed. Secondly, WTs’ clusters based on their LVRT activation status are obtained. In the final step, the WTs are aggregated based on the pre-fault wind speed, and a multi-machine dynamic equivalent model is developed. Also, a new collector network transformation method is proposed. Various low voltage cases are simulated on a 40 MW test WF at different wind conditions. A comparison of the responses from the proposed equivalent model and the detailed model of the test WF indicates the efficacy of the proposed multi-machine model. A comparison of the errors in responses confirms the superiority of the proposed model over the previous relevant works.

Integrated control strategies with Network Reconfiguration (NR), Demand Response (DR), and voltage control can reduce peak demand, energy loss, and system-wide unbalances in modern three-phase active Electric Distribution Networks (EDNs). However, simultaneous handling of these strategies is computationally complex and challenging. This paper presents a stochastic optimization formulation that slices the problem, solves the sub-problems separately, and splices them back to find optimal solutions efficiently. At the outset, all constraint-violating configurations are eliminated using a graph-theory-based edge traversal search developed from the classic Knuth’s Algorithm-S. Subsequently, deploying suitable indices, cyclic NR-DR assignments are performed to find near-optimal topologies and load schedules concerning the minimum loss, peak load, and unbalances. Further, Voltage Regulators (VRs) are set to achieve loss and unbalance reduction with minimal tap operations. The proposed scheme is tested on the modified IEEE 123-node test feeder with extensive EV and PV penetrations. The results show that this modular scheme provides superior solutions with an almost 75% reduction in time than the conventional co-optimization method. Various other case studies illustrate the effectiveness of the proposed scheme.

Conventional protection schemes are vulnerable to varying changes in a microgrid with different types of distributed generators (DGs), which alter the fault current levels, leading to miscoordination of directional over-current relays (DOCRs). Due to limited storage in numeric relays, having one setting for each network scenario in the relays is infeasible. Also, schemes with one setting considering grid-connected mode (GCM) and islanded mode (IM) of operation with multiple scenarios may be infeasible for a microgrid with inverter-interfaced DGs due to low short-circuit level in IM. Thus, this article proposes an adaptive trip characteristics-based relay coordination scheme for a microgrid with different DGs, where two trip characteristics are assigned to each DOCR, one each for GCM and IM. Also, a novel framework for selecting the suitable trip characteristic is proposed. Hardware-in-loop simulations using Numerical Relay Development Environment for a meshed CIGRE microgrid, modified IEEE 34-bus distribution system, and comparison with previous works validate the proposed method's performance for various scenarios, such as the outage of a DG or line, variations in solar irradiation and wind speed, and network reconfiguration for different fault types during GCM and IM.

In emerging electric power systems, increased transactions often lead to situations where system no longer remains in the secure operating region. The flexible AC transmission system (FACTS) controllers can play an important role in the power system security enhancement. However, due to high capital investment, it is necessary to locate these controllers optimally in the power system. In this paper, a sensitivity based approach has been proposed to decide optimal location of thyristor controlled series compensator (TCSC) and unified power flow controller (UPFC). These factors have been derived in terms of change in a real power flow performance index with respect to their control parameters. The effectiveness of the proposed controllers has been tested on IEEE 30 bus and a 246 bus practical Indian system.