Search

Power hardware-in-the-loop (PHIL) simulation has become the crucial means of research on modular multilevel converter based high voltage direct current (MMC-HVDC) devices. To deal with the stability and accuracy problems caused by the power interface, an improved damping impedance method (DIM) interface algorithm is proposed by real-time impedance matching in this paper. The trapezoidal integration method is used to disperse the sub-module capacitance, and the turn-off resistance of power device is set to infinity to simplify the calculation process of MMC equivalent impedance, which can realize the efficient impedance matching for the DIM. Moreover, based on the voltage signal reconstructed by a dq coordinate transformation, a time delay compensation control method is proposed for the uncertain interface delay to improve the accuracy of the PHIL simulation. To verify the excellent stability and accuracy performance of the improved DIM, the characteristics of the reference system, DIM and ideal transformer model (ITM) interface systems are compared by digital simulation. The start-up strategy of a practical MMC-HVDC PHIL test platform is designed, and the effectiveness and feasibility of the proposed methods are verified by simulation experiments. [ABSTRACT FROM AUTHOR]

• By reducing the number of inserted submodules in each phase arm, the DC voltage at inverter side can be decreased quickly and the transmission of DC power can be restored. • A method is proposed to determine adjusted value of DC voltage at inverter side according to the drop degree of AC bus voltage at sending end. • By reducing AC components of the arm voltage, the load can actively participate in regulating the unbalanced power of converter station. • The control strategy can be applied to passive networks with high requirements for AC characteristics by ensuring good power quality at receiving end. The LCC-MMC hybrid DC transmission system can combine the economic advantages of LCC and the technical advantages of MMC, and has broad application prospects for supplying power to passive networks. In order to solve the problem of interruption of DC power transmission caused by AC fault at sending end, a fault ride-through coordinated control strategy based on controlling MMC arm voltage is proposed. The discharge mechanism of submodule capacitor and AC fault characteristics are analyzed by establishing the mathematical model of LCC-MMC hybrid DC transmission system. A control strategy for adjusting the AC and DC components of MMC arm voltage is designed. The DC power transmission can be maintained by reducing DC component of the arm voltage, and load can actively adjust the unbalanced power of converter station by reducing AC component of the arm voltage. The principles for parameters selection are proposed according to different severity of AC fault and the regulation limit of AC component is set according to the characteristics of passive networks. The control strategy can make the load and MMC work together to maintain safe and stable operation of the system. Finally, the effectiveness of proposed coordinated control strategy is verified by simulation results for AC fault of different severity. [ABSTRACT FROM AUTHOR]

• A decentralized economic dispatch model under low-carbon economy is proposed. • Carbon capture power plants and carbon emission trading scheme are considered. • A time-varying carbon emission quota allocation method is proposed. • An over-relaxed ADMM algorithm is adopted to solve the proposed model. This paper proposes a decentralized power system economic dispatch (DPSED) model considering carbon capture power plants (CCPPs) and carbon emission trading scheme (CETS) under a low-carbon economy. First, CETS is introduced and analyzed, and a time-varying carbon emission quota allocation method is proposed. The centralized power system economic dispatch model (CPSED) under a low-carbon economy is established with the objective function to minimize the total operation cost in which CCPPs are introduced that can capture CO 2 to reduce carbon emission trading cost. Then, the centralized economic dispatch problem is reformulated into a decentralized model. It is composed of a set of sub-problems in individual areas that can preserve privacy and be solved independently. The alternating direction method of multipliers (ADMM) algorithm is employed to solve the decentralized optimization model, reducing the amount of exchanged information and preserving the privacy of information shared among participating areas. Moreover, the over-relaxed ADMM algorithm is further adopted to accelerate the convergence. Finally, case studies are performed on a 6-bus system and an IEEE 118-bus system to validate the effectiveness of the proposed model and algorithm. Numerical results demonstrate that CCPPs could reduce carbon emissions, help wind power utilization, and achieve economic operation. [ABSTRACT FROM AUTHOR]

• An adjustable robust power dispatch model under low-carbon economy is proposed. • Combined wind-storage system and carbon capture power plants are considered. • Carbon emissions are considered as controllable variables to be minimized. • The robust dispatch model is transformed into a single level LP problem. This paper proposes an adjustable robust power dispatch (ARPD) model under low-carbon economy to accommodate the uncertainty of wind power with combined wind-storage system (CWSS) and carbon capture power plants (CCPPs). First, battery energy storage (BES), which is considered as adjustable under worst-case scenarios, is introduced to wind power plants to form a combined wind storage system structure to improve operation flexibility. Then, a dispatching model of CCPPs is presented and analysed. The operating characteristics of CCPPs make it possible to control net power outputs and carbon emissions independently and flexibly. The integration of BES and carbon capture and storage (CCS) improves the operation flexibility of both wind power plants and conventional power plants. The objective function of the proposed model under interval-uncertain wind power is to minimize the total cost under the worst wind power output case and the context of low-carbon economy. The proposed model is implemented on the modified PJM 5-bus system with one wind farm and the IEEE-118 bus system with five wind farms. Numerical results demonstrate that the proposed model is effective at reducing carbon emissions and wind power curtailment, and verify that as the number of CCPPs increases, the overall costs come down. [ABSTRACT FROM AUTHOR]

• A novel stochastic bi-level strategic bidding model for P2G facility is proposed. • Carbon emission trading scheme (CETS) and its impact on LMP are considered. • The bi-level model is converted into mixed-integer linear programming (MILP). • The proposed bidding model can increase the profit of P2G facility. • CETS can increase the profit of P2G facilities and reduce carbon emission. As an emerging energy storage technology for renewable power utilization, power-to-gas (P2G) requires efficient bidding strategies to increase profit. This paper proposes a bi-level strategic bidding model for P2G with the consideration of a carbon emission trading scheme (CETS), an embedded locational marginal price (LMP) and wind power uncertainty, where the upper level model aims to maximize the profit of P2G facilities and the lower level model carries out the market clearing process. Under a CETS, a P2G facility purchases electricity power according to the LMP and is assumed to sell synthetic natural gas (SNG) and carbon emission permits for revenue. The electricity market clearing process is represented by a stochastic low carbon economic dispatch (ED) model considering the CETS, P2G and wind power uncertainty. On this basis, the formulation of a CETS embedded LMP (CETS-LMP) is presented and analyzed here. The bi-level model is reformulated and converted into mixed-integer linear programming (MILP) using strong duality theory. Case studies performed on a modified PJM 5-bus system and an IEEE 118-bus system verify the effectiveness of the proposed model and demonstrate that considering the CETS can increase the profit of P2G facilities and reduce carbon emission. [ABSTRACT FROM AUTHOR]

• A power system unit commitment model with flexibility of CCGT is proposed. • Natural gas transmission constraints and reserve scheduling are considered. • The model is transformed into an iterative MISOCP problem. • Startup-shutdown cost and wind power curtailment can be reduced. With the integration of large-scale renewable energy including wind power into the power grid, efficient flexible resources are required for wind power accommodation. The combined-cycle gas turbines (CCGTs) are widely used in the power system with flexible operation characteristics, which leads to enhanced interdependencies between the power grid and the natural gas network. In this paper, a unit commitment (UC) model with natural gas transmission constraints and reserve scheduling considering the flexibility of CCGT with quick startup-shutdown and flexible operation characteristics is proposed, to reduce wind power curtailment and high startup and shutdown cost of conventional generation units in the power system. Considering the complex operating conditions of CCGT and the non-convexity of Weymouth equation in natural gas network, this paper adopts an improved mode-based model (MBM) for modeling of CCGT and converts the Weymouth equation into a second-order cone relaxation (SOCR) formulation with penalty term through a concave-convex process (CCP) to make the relaxation tight, thus transforming the UC model into an iterative mixed-integer second-order cone programming (MISOCP) problem to be efficiently solved. The effectiveness of the proposed model on reducing wind power curtailment and startup-shutdown cost is demonstrated through case studies. [ABSTRACT FROM AUTHOR]

• A local electricity-heat integrated energy market clearing method is proposed. • Local electricity and heat markets are cleared simultaneously. • The equilibrium between DSO and TSO is considered. • The model is transformed into an MISOCP problem. With the increasing interconnection of active distribution network (ADN) with the integration of distributed generations (DGs) and district heating network (DHN), local electricity-heat integrated energy market provides the opportunity of coordinated energy pricing and trading with transmission system operator (TSO). The market clearing results of distribution system operator (DSO) on local electricity and heating markets will be affected wholesale market clearing. This paper proposes a bi-level optimization model for local electricity-heat integrated energy market clearing for integrated ADN and DHN, and distribution locational marginal pricing coordinated with the wholesale market clearing of transmission system. In the proposed model, the upper-level model indicates the local electricity-heat integrated market clearing by DSO and the lower-level model indicates the wholesale electricity market clearing by TSO. The locational marginal price (LMP) of the substation of the PCC point will affect the market clearing of ADN and DHN, and further affect the distribution locational marginal price (DLMP). Moreover, the market clearing actions of DSO would affect the wholesale electricity market clearing and LMP. The equilibrium of DSO and TSO is found by transforming the proposed bi-level model into a mathematical program with equilibrium constraint (MPEC) model. The MPEC formulation is further converted into mixed integer second order cone programming (MISOCP) for effectively solving. The effectiveness of the proposed model on reducing the DLMP and improving economy of ADN and DHN are demonstrated through case studies. [ABSTRACT FROM AUTHOR]

• A five-terminal HVDC model suitable for wind farm clusters integration is built. • An improved droop control method is proposed with an adjustable coefficient. • The application of lag compensator technique improves dynamic response capability. • The effectiveness and superiority of proposed method are verified via 4 test cases. With the continuous expansion of wind farm clusters, the multi-terminal modular multilevel converter based high voltage direct current (MMC-HVDC) transmission has been employed for wind power delivery. To improve the control flexibility, dynamic voltage adjustment speed and rationality of power allocation, various coordination control methods have been recently investigated in multi-terminal MMC-HVDC transmission system. An attempt is made in this paper to contribute to the optimization of coordination control in the multi-terminal MMC-HVDC system connected to wind farms. Based on the analysis of DC voltage, power deviation and droop coefficient, an improved droop control strategy with adjustable coefficients is first proposed and thereby applied to multi-terminal MMC-HVDC transmission system with wind farm clusters. Arguably, the droop coefficient correction should be an effective method for optimizing power allocation and reducing DC voltage deviation between the receiving converters. In addition, a lag compensator is introduced to improve the response speed of the inner loop controller when the improved droop control is adopted. Furthermore, the influence of droop coefficients on the stability of the control system is discussed, and the dynamic response of the improved control system is also analyzed under the different droop and time coefficients, which can provide guidelines for the control optimization of multi-terminal MMC-HVDC system. Finally, a model of a five-terminal MMC-HVDC transmission system is built based on the RT-LAB simulator, and the simulation results show that the proposed method can not only optimize the voltage control and power allocation, but also improve the system response speed. [ABSTRACT FROM AUTHOR]

• The approach realizes dynamic patterns estimation in one holistic framework. • It is first time for ERA to estimate mode shape, participation factor and coherency. • The approach extends the application of ERA in power systems modal analysis. • The approach can reveal the inherent dynamic features of power systems. In power systems, electromechanical oscillatory dynamics, dominant modes, mode shapes, participation factors and coherent groups of generators are all important modal parameters. Most of the existing measurement-based methods focus on estimating one or two aspects among dominant modes, mode shapes, participation factors, and coherent groups. Nevertheless, none of existing methods explore all the four aspects from synchrophasor measurements at the same time. In this work, an eigensystem realization algorithm (ERA) based data-driven approach is developed to estimate dominant modes, mode shapes, participation factors and coherent groups from synchrophasor measurements in a holistic framework. In the proposed approach, the reduced power system dynamic model is first estimated by ERA from multichannel synchrophasor measurements. Then, based on the estimated power system dynamic model, electromechanical oscillation modes, corresponding mode shapes and the left eigenvalue vectors are solved. Next, using the solved mode shapes and left eigenvalue vectors, the participation factors of the generators associated with the electromechanical oscillation modes are calculated. Further, the direction cosines among the generators representing coherent strength of generators are calculated by using the achieved mode shapes. Finally, in accordance with the calculated direction cosines, the coherent generators are then identified. The proposed approach is demonstrated with the simulation data of the 16-machine, 68-bus test system and the field Phasor Measurement Units (PMUs) data collected in Liaoning Electric Power Grid. The results demonstrate that the proposed data-driven approach captures dominant modes, mode shapes, participation factors, and coherent groups of generators from synchrophasor measurements with high accuracy and efficiency. [ABSTRACT FROM AUTHOR]