Modular multilevel converter (MMC) is believed the most competitive solution for high-voltage direct current (HVDC) transmission using voltage source converters. Circulating current suppressing strategies based on proportional resonant (PR) controllers are widely used in MMC. This kind of strategies can effectively eliminate all the circulating current components in MMC-HVDC. Unfortunately, it can result in dc-line voltage ripples under unbalanced grid conditions, and thus, deteriorates system performance and stability. Moreover, its existing control model may not exactly reveal the inherent characteristic of MMC, and consequently blocks the further understanding and application. To solve these two problems, first, this paper builds a new and effective control model for this strategy. Second, based on the new model, this paper studies the relationship between circulating current reference value and submodule capacitor voltage, modulation index, and arm current to correct and improve the current understanding of this control strategy. Finally, three improved strategies based on PR controllers are proposed. These improved control strategies can eliminate both circulating current and dc-line voltage ripples, which greatly enhance the fault ride-through capability of MMC-HVDC without adding extra control cost or the number of controllers.

In this paper, new formulations of the power flow and continuation power flow that allow for electro-thermal coupling in transmission lines have been proposed. The new formulations capture the overhead lines' electro-thermal coupling effects by treating their series resistances as temperature dependent variables. They generate results that can differ from the results of conventional formulations markedly, particularly for problems centring on line impedances. The paper demonstrates this by applying the new formulations to the power transfer limit calculation. Generally, power transfer limits are defined either by encountering a line's thermal limit or detecting the onset of voltage collapse in the system. Studies based on 2-bus and 14-bus test systems are used to demonstrate the efficacy of the new formulations for both situations. For these studies, specific point-to-point power transfer limits are calculated with and without the lines' electro-thermal coupling effects and the results are compared.

This article presents a model predictive control (MPC) based multitime scale co-optimized dispatch for integrated electricity and natural gas system (IEGS) considering the bidirectional interactions and renewable uncertainties. In the proposed model, optimal dispatch is extended into three substages optimization problems of day-ahead, intraday, and real-time to coordinate the economy and accuracy of operations. The different optimization strategy is designed in each dispatching stage according to the operating characteristics of multienergy coupled units and high-penetration intermittent wind power. In the day-ahead stage, the unit commitment is tackled to arrange the start-stop plan of slow-response units, maintained in intraday and real-time stages to ensure full-term optimal economic operation. In the intraday stage, MPC-based rolling optimization is implemented to obtain the unit output scheme with the lowest operating cost target. Furthermore, the output scheme is rolling adjusted in the real-time stage based on the ultrashort-term forecast value, and a closed-loop feedback mechanism is introduced to achieve accurate power balance. In each stage, stochastic decision-making is executed based on the stochastic scenario method, efficiently capturing the uncertainty in IEGS. Besides, the proposed nonlinear model is transformed into a mixed-integer second-order cone programming problem using McCormick relaxation, which can be efficiently solved by commercial solvers. Simulation results on IEEE39-Gas20 and IEEE118-GAS40 test systems demonstrate the superiority of the proposed method in operational economy and wind power utilization, and also verify the effectiveness of the method to accurately track random fluctuations without obvious computational burden.

In addition to maintaining the power balance, the major tasks of multi-area automatic generation control (AGC) involve regulating the power exchange among subareas. This study presents a new power flow model allowing for multi-area AGC that achieves cooperation among the participating generators, which are deployed separately in the interconnected subarea networks. The formulations of the power exchange among the subareas are derived from the active power flow equations of the tie-lines. The node parameters representing the level and allocation of the unbalanced power are introduced. Then, the proposed power flow model is established by integrating the formulations of the node power injection and power exchange. Meanwhile, the unknown variables in the integrated model can be synchronously adjusted by the Newton iteration method, which depends on the integrated Jacobian matrix. Furthermore, being improved based on the integrated formulations, some related algorithms, including but not limited to sensitivity analysis, are expected to produce more precise solutions. The case studies of the IEEE 5 bus test system, the IEEE RTS-1996 test system, and the IEEE 300 bus test system illustrate the convergence and efficiency of the proposed power flow method. Moreover, the case studies also demonstrate that the integrated formulations based sensitivity analysis can generate more reliable results.

The emerging prosumers have changed the way traditional distribution systems operate. While harvesting the benefits of Distributed Energy Resources (DERs), prosumers’ self-dispatching and internal energy trading can also bring technical challenges and economic loss to the distribution system operator (DSO). To this end, a DSO-prosumers cooperated scheduling framework for the transactive distribution system, which considers the impact of prosumers’ peer-to-peer (P2P) energy trading, is proposed in this paper. First, by incorporating the P2P energy trading among prosumers into scheduling, prosumers and the DSO can cooperate to optimize the power flow. Meanwhile, the Nash bargaining theory is introduced to achieve the optimal allocation of interests. Then, to improve the computational efficiency, the established bargaining problem is decomposed into two subproblems, i.e., the optimal physical power flow problem, and the virtual power flow bargaining problem. Finally, in order to protect individual privacy, each problem is solved via the alternating direction method of multipliers (ADMM) algorithm in a distributed manner. Case study based on the IEEE 33-bus test system verifies the effectiveness of the proposed method.