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The paper presents an approach for online centralized control in active distribution networks. It combines a proportional integral (PI) control unit with a corrective control unit (CCU), based on the principle of Model Predictive Control (MPC). The proposed controller is designed to accommodate the increasing penetration of distributed generation in active distribution networks. It helps in continuously satisfying the reactive power requirements of the transmission system operators (TSOs), while maintaining an acceptable voltage profile in the active distribution network, and simultaneously minimizing the total active power losses. The controller also ensures compliance to operation requirements of distribution network operators (DNOs). By replacing the full load flow (LF) calculation with sensitivities, derived from a linearized model of the network, the controller can work in real-time applications. Moreover, the computational burden of the proposed controller is reduced since the CCU is activated only when a voltage violation or considerable change of operation condition occurs. The performance of the proposed controller is demonstrated on a 11-kV test network with 75 buses and 22 distributed generators.

This paper presents a comprehensive approach to evaluate the effects of voltage and reactive power control methods for local and coordinated control schemes applied to wind generators (WGs) in distribution networks. Considering uncertainties related to variation of load demand, wind speed and outage of WGs, the approach employs a Monte Carlo-based framework to ascertain the benefits and drawbacks of each scheme with respect to the resulting statistical attributes of voltage profiles, tap activity of on-load tap changers and total active power losses. A 20 kV radial distribution network with four identical feeders, which resembles a typical case in Germany, is used for numerical tests.

Cooperation of regional operators in solving optimal reactive power dispatch (ORPD) problems in large systems is beneficial despite of many challenges. One major challenge is the fact that each regional operator is typically not willing to reveal the local system data. To deal with such challenge and to try to attain a dispatch resulting in overall optimum, this paper proposes a control scheme in which a large area is partitioned into multi-agent based system where each operator is considered as a control agent and uses a model of its local system and communication links with its neighboring control agents to come to agreement on the evolution of interconnections and to determine optimal local control actions and states. At each agent, a linearized objective function enforced with constraints has to be solved to determine control variables, which are transformer tap positions and reactive power injections. Calculation procedure at each agent based on sensitivity coefficients, thus impact of change magnitudes of control variables on control performance would be significant and hence is fully analyzed. The proposed algorithm is applied to the modified IEEE 30-bus system and numerical results are presented.Index Terms-Mean-variance mapping optimization, online adaptive control, reactive power management, wind power plant.