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Transient stability assessment (TSA) of power system based on enhanced projection twin support vector machine (SVM) is proposed. The high dimensional binomial optimization problem based on traditional SVM for TSA was transformed into two low dimensional binomial optimization problems, and the improved optimization method of particle swarm was used to optimize the parameters of projection twin SVM to improve the TSA accuracy. Firstly, an initial sample set composed of system features and projection energy function features is constructed to obtain the optimal feature collection through feature compression. Then, the efficiency of transient stability evaluation is improved by solving two low-dimensional binomial optimizations after dimensionality reduction, and the optimal projection axes of the transient stability state are obtained, such as stable and unstable classes. At the same time, improved particle swarm optimization is used for parameter selection to improve accuracy. Finally, the validity and accuracy are verified by the IEEE-39 node system.

During the actual operation of micro grid, the power fluctuation of tie line caused by the Load power fluctuation of renewable energy or load prediction deviation needs to be controlled in real time to ensure the economy of micro grid operation. This paper aims at a power system model based on the framework of "distribution network - industrial park micro grid - enterprise load user", and studies a power control method of micro grid tie line based on user reward scheme. Firstly, the objective economic function of the micro-grid in the park is established, and then the optimal reward scheme for internal load users of the micro-grid in the park is derived according to two typical load response models. The power fluctuation can be stabilized by encouraging load users to respond to demand, thus the internal load users can benefit while reducing their own economic losses and the day-ahead scheduling results of tie lines can be effectively tracked. Taking a production industrial park as an example, the effectiveness of the proposed optimization model and algorithm is verified by an example analysis.

This paper proposes a bi-level optimal energy storage system (ESS) siting and sizing algorithm to mitigate the voltage deviation in distribution networks. In the upper level, a multi-objective optimization model, which minimizes the ESS investment cost, line losses, power purchasing cost, and voltage deviation, is presented. Then analytic hierarchy process (AHP) is introduced to transform the multi-objective model into a single-objective model that can be easily solved. In the lower level, the ESS operation strategy is optimized to smooth the load curve and lower the power purchasing cost. The proposed methodology is tested on the IEEE 33 bus system to evaluate its performance. Simulation results demonstrate that the proposed approach can improve the voltage quality, maximize the network economy, and reduce the real power loss without changing the distribution network topology.

This paper proposes a novel transient stability assessment (TSA) method for hybrid AC/DC systems with VSC-HVDC via port energy. The port energy of VSC-HVDC is described as the function of port state variables and control variables. The representation of port energy greatly enhances the accuracy of the transient stability study and can be extended to arbitrarily power electronics devices. At the same time, this approach can avoid formulating energy function with the complex internal controls of VSC-HVDC. Furthermore, iterative potential energy boundary surface (IPEBS) is employed to TSA. The maximum potential energy is searched on the instability of rotor angle’s swing curves as the critical energy through the dot product criterion. Then, the influence of the VSC-HVDC for transient stability is studied, including the VSC-HVDC transmission capacity of active and reactive power. The accuracy of the proposed energy function calculation is discussed via the different fault location. The feasibility and validity of the proposed method are demonstrated via the modified IEEE 39-bus hybrid AC/DC system.

This paper presents a spectrum analysis-based method to calculate the optimal sizing and operation strategy for a hybrid energy storage system (HESS) combining batteries (BT) and supercapacitors (SC) to integrate high penetrations of wind power into the power grid. BTs and SCs have different response times and energy densities, which can be used to complementarily compensate the generation-demand imbalance. In this paper, the unbalanced power is first converted from time domain to frequency domain by discrete Fourier transform (DFT). Then upper and lower cut-off frequencies are determined to calculate the optimal sizing for each energy storage source. Moreover, a chance-constrained programming model is established to explore the optimal operation strategy for HESS. The model is solved by Monte Carlo simulation and a genetic algorithm. Simulation results on a practical system demonstrate that the proposed method can effectively reduce the ESS investment cost and maximize the economic profits.

This paper proposes a multi-objective approach for low-carbon economic dispatch with carbon capture power plants (CCPPs) and demand response (DR). First, brief dispatching model of CCPPs is presented. The operation mechanism of CCPPs and DR for different objectives is analyzed. Then, the multi-objective low-carbon economic dispatch model with CCPPs and DR is proposed. The objectives include minimizing the bidding cost of conventional power units and wind power, minimizing carbon emissions, maximizing utilized wind power and minimizing DR cost. The weighting coefficients of the objectives are calculated by analytic hierarchy process (AHP). The optimization model is recast as a mixed integer linear programming (MILP) formulation and solved by CPLEX. Finally, numerical results performed on the modified PJM 5-bus system verify the feasibility and effectiveness of the developed model by comparing to single objective cases.

This paper investigates the impact of price-based demand response (DR) programs on available transfer capability (ATC) in deregulated electricity markets. A bi-level optimization model which considers both the interests of load serving entities (LSE) and independent system operators (ISO), has been established. The upper level of the proposed model selects the DR participants by minimizing the DR compensation cost and power purchasing cost, while the lower level conducts economic dispatch and determines the locational marginal prices (LMP). The bi-level optimization problem is first converted to a mathematical programming problem with equilibrium constraints (MPEC) by reformulating the lower level problem as its KKT conditions. Then, the nonlinear terms are eliminated by applying the strong duality theory. Thus the original problem is transformed into a mixed-integer linear programming (MILP) problem, which can be easily solved by the GAMS. The performance of the proposed method is tested on the IEEE 30-bus system. Simulation results validate the effectiveness.

This paper proposes a low-carbon economic dispatch model with combined wind-storage system (CWSS) and carbon capture power plants (CCPPs). First, the battery energy storage (BES) is introduced into wind power plants to form a combined wind-storage system structure, aiming at improving the operation flexibility of wind power. Then, the dispatching model of CCPPs is presented. The operating characteristics of CCPPs make it possible to control the net power outputs and carbon emissions separately and flexibly. The integration of BES and carbon capture and storage (CCS) improves the operation flexibility of wind power plants and conventional power plants, respectively. The low-carbon economic dispatch model considering CWSS and CCPPs is formulated as a mixed integer linear programming (MILP) problem. Numerical results performed on the PJM 5-bus system demonstrate that the proposed model is effective on reduction of carbon emissions and wind power curtailment.

A fast distinguish method to discriminate the critical commutation failure region of multi-infeed HVDC system is proposed in this paper. Based on the nodal impedance matrix and nodal voltage interaction factor (VIF), the extinction angles of convert stations under the single-phase or three-phase to ground fault happening at any bus in AC system is first calculated. If the calculated extinction angle with regard to a certain bus is greater than the critical extinction angle, the single-phase or three-phase to ground fault at that bus will cause commutation failure of the HVDC system. The critical failure impedance boundaries on topology diagram can be therefore delimited by examining every bus in the AC system. The simulation results of a two-infeed HVDC test system verifies the effectiveness and accuracy of the proposed method which detects the commutation failure of multi-infeed HVDC system based on critical failure impedance boundaries.

In this paper, a two-stage mixed integer linear programming (MILP) formulation for source-load coordinated dispatch with wind power considering peak-valley regulation and ramping requirements is proposed. First, the peak-load regulation and ramping requirements of the net load curve are analyzed. Second, the first stage optimization model considering incentive-based demand response (IDR) is formulated to optimize the net load curve, in which the objective function is to minimize the compensation costs of IDR. Several constraints are taken into account to reduce the peak-valley regulation needs and meet the ramping requirements. Then, based on the optimized load curve, the second stage day-ahead dispatch optimization model is proposed to optimize the allocation of generation sources, taking the total costs of power generation minimization as the objective function considering thermal unit reserve costs. The proposed model is applied to a 10-unit system with a wind power farm with 600MW installed capacity. Simulation results demonstrate the effectiveness and feasibility of the proposed model.

In modern power systems, the integration of variable and random renewable energy brings more challenges to real-time voltage stability monitoring and control. Loading margin sensitivity (LMS) is an index that is widely-used to evaluate voltage stability. The accuracy of LMS relies on the credibility of the data collected by local measurement units, which are used to estimate the system model parameters. Considering the noise signals and the variability of renewable generation, this paper proposes a probabilistic LMS calculation method based on bootstrap technique. Through the bootstrap, the proposed method provides a confidence interval estimate for LMS, which is effective to implement in the presence of renewable generation. Finally, the effectiveness of the proposed method is demonstrated by a TSAT simulation on the 48-machine 140-bus NPCC system.

The influence of four different cacuum pressure on drying process of RDX with relative moisture content 8% was investigated at 70°C. The results show that the greater the vacuum is, the shorter the drying cycle is and drying rate accelerates, but when vacuum is up to a certain extent, it is limited to increase the drying rate; critical moisture content and equilibrium moisture content don't generally vary with the change of vacuum. Experimental data was used to simulate relative moisture content and drying rates, and drying formulations were put forward.

This paper presents a new model of probabilistic available transfer capability (abr. ATC) computation, which is based on the improved particle swarm optimization (abr. IPSO). Firstly, pointing to the search characteristics of particle swarm optimization (abr. PSO) penalty function is assigned dynamically according to the amount overrunning the upper-limit or lower- limit of inequality constraints during the calculating process, which accelerates the speed of convergence of PSO. A new self-adaptive adjustment strategy of inertia weight is also proposed, which elevates the adaptability of PSO and accelerates convergence-speed of PSO all the more. Secondly, ATC can be computed by IPSO after critical contingencies are selected by modal analysis method. Lastly, through the probabilistic analysis based on the probability of each contingency happening and ATC corresponding to each contingency, the probabilistic ATC can be gotten. A case study of IEEE-30 bus system demonstrates the rationality and the validity of strategies proposed in this paper.