In low latitudes, ice storage air conditioners (ISACs) have been widely used to cool while locally responding to the distribution network demand. However, due to the lack of the direct cold energy exchange between ISACs, the cooling load could only be shifted on the time scale instead of the space scale, resulting in an unsatisfactory regulation result. To address the above problem, this paper proposes a novel collaborative expansion planning scheme for integrated cooling and power system. Firstly, to increase the regulation flexibility, a novel cold energy supply system is designed, where ice making stations and trucks are used to produce and deliver ices to multiple terminal ISACs. On this basis, taking the capacity of the wind turbines (WTs), large ice makers (LIMs), and trucks as configuration decisions, an optimal expansion planning model is established considering wind generation uncertainties. This model is converted into a classic mixed-integer second-order cone programming (MISCP) problem using linear techniques, and efficiently solved by the Benders decomposition method. Finally, Shapley value method in economics is used to fairly distribute the revenues between the grid operator and ISAC owners. Simulation studies on IEEE 14-node distribution network indicate the proposed expansion model is effective and beneficial.INDEX TERMS Low-latitude distribution network, ice storage air conditioners, expansion planning, integrated cooling and power system, Shapley value method, Benders decomposition method.

The power balance of the tie-line is crucial to the stable operation of a community microgrid. This paper presents a power fluctuation smoothing method of the microgrid tie-line based on virtual energy storage technology. Firstly, the structure characteristics and the energy coupling mode of the combined heat and power system is systematically analyzed. Considering the operating characteristics of heat pumps, micro gas turbines, and buildings’ heat storage characteristics, a virtual energy storage model is established. Secondly, the target power of the tie-line is determined with the storage state indexes into consideration. Subsequently, a power allocation strategy which takes into account the correction of equipment state mapping set is proposed to allocate the tie-line power fluctuations to heat pumps, micro gas turbines, and supercapacitors. Simulation results show this method can realize the coupling coordination between heat and power energy and ensure the smoothing effect of the power fluctuations. Meanwhile, the control flexibility of the combined heat and power system can be enhanced, and the microgrid’s operating economy can be improved.

In order to more effectively reduce the regulation costs of power grids and to improve the automatic generation control (AGC) performance, an optimization mathematical model of generation command dispatch for AGC with an electric vehicle (EV) charging station is proposed in this paper, in which a cost consensus algorithm for AGC is adopted. Particularly, virtual consensus variables are applied to exchange information among different AGC units. At the same time, the actual consensus variables are utilized to determine the generation command, upon which the flexibility of the proposed algorithm can be significantly enhanced. Furthermore, the implement feasibility of such an algorithm is verified through a series simulation experiments on the Hainan power grid in southern China, where the results demonstrate that the proposed algorithm can effectively realize an autonomous frequency regulation of EVs participating in AGC.

The setting of protection parameters is vital to the large-scale application of reverse time overcurrent protection in the distribution networks. A fixed value optimization method of inverse time overcurrent protection for the distribution networks with distributed generation based on the improved Grey Wolf algorithm is proposed, which takes the protection action equation and the sensitivity, speed, and selectivity into consideration. Subsequently, four strategies, including good point set initialization, convergence factor exponential decay strategy, mutation strategy, and heuristic parameter determination strategy, are introduced to improve the Grey Wolf algorithm on the premise of retaining fewer adjustable parameters. Simulation results verify the feasibility and superiority of the proposed model in case of the two-phase and three-phase faults and discuss the influence of time differential on parameters setting and the research direction of algorithm optimization and engineering application.

Aiming at the operation and maintenance requirements of the fault location of high-temperature superconducting cables, a fault location method of high-temperature superconducting cables based on the improved time-frequency domain reflection method and EEMD noise reduction is proposed. Considering the cross-term interference problem in the traditional time-frequency domain reflection method, this paper introduces the affine transformation to project the time-frequency distribution of the self-term and the cross term and further highlights the characteristic differences between the two through coordinate transformation, and the particle swarm algorithm is employed to solve the optimal stagger angle of the affine transformation. The unscented particle filter is adopted to separate the cross term, and EEMD noise reduction is introduced to solve the signal noise problem. Finally, two software programs, PSCAD and MATLAB, are employed for joint simulation to build a model of high-temperature superconducting cable. The simulation example shows that the proposed method in this paper can eliminate the cross-term interference of the traditional time-frequency domain reflection method, effectively locate the fault of the high-temperature superconducting cable, and improve the positioning accuracy.