Search

The wake effect is the major obstacle to reaching the maximum power generation for wind farms, since choosing the suitable wake model that satisfies both computational cost and accuracy is a difficult task. Deep Reinforcement Learning (DRL) is a powerful data-driven method that can learn the optimal control policy without modeling the environment. However, the "trial and error" mechanism of DRL may cause high costs during the learning process. To address this issue, we propose an ensemble-based DRL wind farm control framework. Under this framework, a new algorithm called Actor Bagging Deep Deterministic Policy Gradient (AB-DDPG) is proposed, which combines the actor-network bagging method with the Deep Deterministic Policy Gradient. The gradient of the proposed method is proved to be consistent with the DDPG method. The experiment results in WFSim show that AB-DDPG can learn the optimal control policy with lower learning cost and a more robust learning process. • This paper proposes an ensemble-based DRL framework for wind farm control. • An algorithm is proposed under the proposed framework to reduce the learning cost. • The gradient used in the proposed algorithm is proved to be consistent with the DDPG. [ABSTRACT FROM AUTHOR]

• A framework solution for multi-timescale coordinated operation of CHP and wind power. • Day-ahead and real-time uncertainties are handled by stochastic optimization. • The solution is applied to a real-life case in Denmark. • Comparative analysis between coordinated operation and independent operation. • Comparative analysis between stochastic and deterministic methods. This paper proposes a multi-timescale coordinated operation approach which coordinates the combined heat and power (CHP) plant and wind farm operation in a deregulated day-ahead heat market and a real-time balancing electricity market. This approach aims to optimize profits of the CHP-wind farm portfolio by considering energy sale in the day-ahead heat market and penalty in the real-time two-price balancing market. Multiple uncertainties of heat load, wind power generation, day-ahead electricity price, up- and down-regulation prices are taken into account for the optimal operation. A stochastic optimization method is applied to solve the proposed coordinated operation problem. The proposed multi-timescale coordinated operation approach is simulated on a real-life system in Copenhagen Denmark where an energy company owns both a CHP plant and a wind farm. The simulation results verify that the proposed method can achieve a profitable operation in the markets and a highly robust operation against the multiple uncertainties. [ABSTRACT FROM AUTHOR]

• Small-signal stability analysis, frequency scan, time domain simulations are carried out to analyse the mechanism and characteristics of such SSI. • A real SSO incident is reported with its field measured data analysed. Replication of this incident in PSCAD/EMTDC is conducted to validate the consistency with theoretical analysis. • Composite short circuit ratio (CSCR) and relative short circuit ratio (RSCR) are developed to investigate characteristics of SSI with two different WPPs existing in the wind farm. Recently, sporadic power oscillations in subsynchronous frequency range were detected in several permanent magnet synchronous generator (PMSG)-based wind farms in Xinjiang, China. Given no existence of fixed series compensation in the system, it can be concluded that this is a new type of subsynchronous interaction (SSI) and different from the previous subsynchronous control interaction (SSCI) occurred in doubly-fed induction generator (DFIG)-based wind farms. Therefore, the characteristics and mechanism behind this phenomenon are so ambiguous that further clarification is needed. To investigate this new type of subsynchronous oscillations (SSO) problem, a real SSI incident is reported, and the equivalent model is established based on multi-machine equivalent aggregation. Refined frequency scan and small-signal analysis are carried out to analyse the mechanism and characteristics of such SSI. Time-domain simulations are conducted to replicate the incident. The results show that the interactions between PMSG-based wind farms and weak grids can trigger negative-resistance and capacitive-reactance effects, which leads to unstable power oscillations. To further investigate the influence of different wind power plants (WPPs), two short-circuit ratio metrics are developed, and time-domain simulations are conducted based on semi-aggregation. The potential hazards of this SSI and its mitigation strategies are also discussed and proposed. [ABSTRACT FROM AUTHOR]