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In northern China, the combined heat and power (CHP) units account for a large proportion of the local generation capacity. However, the inherent heat-power coupling of CHP units poses a large barrier for wind power accommodation. To facilitate the local wind integration, the key is to improve the flexibility of the CHP system, and there are two types of feasible methods. One is the addition of heat storage tanks and electric boilers into the CHP system, and this method has been considered in the scheduling of the CHP system, such as the unit commitment (UC) optimization. The other type of method is the flexibility retrofit of CHP units, including the two-stage bypass modification and low-pressure cylinder removal (LPCR). However, prior research has not attempted to integrate the flexibility retrofit into the UC scheduling. To fill this gap, this paper proposes a novel UC model incorporating the bypass and LPCR retrofit of CHP units. In this model, the constraints on the safe operation region, fuel cost, reserve provision, ramping and mode switching of different types of CHP units are thoroughly described. Cases studies are conducted on a test system. Simulation results show that the proposed UC model is capable of utilizing the bypass and LPCR retrofit to facilitate wind accommodation, with the wind curtailment reduced by 81.94% and 20.45% under the bypass and LPCR retrofit, respectively.

Active power sharing and voltage regulation are two of the major control challenges in the operation of the voltage source converter based multi-terminal high-voltage DC (VSC-MTDC) system when integrating large-scale offshore wind farms (OWFs). This paper proposes two novel adaptive voltage reference based droop control methods to regulate pilot DC voltage and share the power burden autonomously. The proposed Method I utilizes DC grid lossy model with the local voltage droop control strategy, while the proposed Method II adopts a modified pilot voltage droop control (MPVDC) to avoid the large errors caused by the DC grid lossless model. Dynamic simulations of a five-terminal MTDC grid are carried out using MATLAB/Simulink SimPowerSystems /Specialized Technology to verify the proposed autonomous control methods under various types of disturbance and contingency. In addition, comparative study is implemented to demonstrate the advantages of the proposed methods.

Abstract In this article, the stability of a synchronous motor generator pair (SMGP) used for improving the inertia of grid‐connected renewable energy systems is investigated. The useful operational regime for different sets of system parameters is identified, such as electromagnetic torque, damping co‐efficient, and inertia by employing bifurcation analysis to detect stability boundaries. For the first time, the existence of bi‐stable regimes for the SMGP with non‐linear stability analysis is revealed. The authors' analysis unravels the possibility of the system getting transited to unsafe operation even when the system is in the linearly stable region. The existence of the bistable regime indicates the possibility of the system becoming unstable even when the eigenvalues are in the left half plane. The authors also identify globally stable and globally unstable regimes in the parameter space. The safe operating range of inertia and damping co‐efficient values helps in the design of a suitable MGP set that is robust to frequency deviations, even with a low inertia source. With the recommended values of electromagnetic torque, the authors' analysis provides a safe operational regime for power generation from renewable energy sources.

This study proposes an enhanced Kepler Optimization (EKO) algorithm, incorporating fractional-order components to develop a Proportional-Integral-First-Order Double Derivative (PI–(1+DD)) controller for frequency stability control in multi-area power systems with wind power integration. The fractional-order element facilitates efficient information and past experience sharing among participants, hence increasing the search efficiency of the EKO algorithm. Furthermore, a local escaping approach is included to improve the search process for avoiding local optimization. Applications were performed through comparisons with the 2020 IEEE Congress on Evolutionary Computation (CEC 2020) benchmark tests and applications in a two-area system, including thermal and wind power. In this regard, comparisons were implemented considering three different controllers of PI, PID, and PI–(1+DD) designs. The simulations show that the EKO algorithm demonstrates superior performance in optimizing load frequency control (LFC), significantly improving the stability of power systems with renewable energy systems (RES) integration.

Abstract Variable renewable generation and load fluctuations induce significant balancing cost in power system operation. To overcome this issue, this paper proposes a control architecture that leverages inherent regulation capabilities of wind turbines to minimize the system‐wide balancing costs. Instead of handling wind power fluctuations via power filtering algorithms that are agnostic to system‐wide power imbalance, this paper aims to optimize the wind power generation profile from system perspective. In the proposed method, wind turbines are modelled as semi‐dispatchable units, where the dispatch command is dynamically generated at every automatic generation control cycle by considering mileage payments as an indicator of system‐wide imbalance. As a result, local resources of wind turbines are optimally leveraged in real‐time to mitigate system‐wide power imbalances. The proposed strategy and state‐of‐the‐art techniques are compared in comprehensive high‐fidelity case studies. Our simulation results demonstrate that the proposed system‐aware regulation scheme can alleviate system balancing costs without investments into energy storage systems.

As the offshore wind installations are moving further from shore, the transmission distance also increases. Synthesize the cost of construction and maintenance, as well as the technical maturity, grid-connection via AC network will still be a preferred power delivery method for offshore wind power projects in the near future. However, according to the “8•9” blackout in the UK, there is sub-synchronous oscillation (SSO) risk in the AC network connected offshore wind projects, which was attributed to the mismatch between the power electronic source and the power grid. In this article, both eigenvalue analysis and time-domain simulation method are used to evaluate the operating SSO stability of grid integration of large scale offshore wind power. It suggests that transmission system via long distance cables naturally forms a weak AC network, and the SSO characteristics of AC grid connected offshore wind farm is closely related to the wind turbine parameters, offshore distance and the active power output level. At last, the principle of parameter configuration in offshore wind turbines is proposed based on different offshore distances.