Sidun Fang

Stochastic optimal reactive power dispatch method based on point estimation considering load margin

Conventional optimal reactive power dispatch approaches operate mostly in deterministic form where the power injections are fixed. In practice, however, power injections, especially from intermittent renewable sources, and demand are of uncertainties. To address this problem, in this paper, we develop a load margin constrained stochastic optimal reactive power dispatch (LMC-SORPD) method. We first formulated the considered problem into a chance-constrained programming, which is then solved through genetic algorithm and stochastic power flow based on point estimation. Simulation results on several cases demonstrate that the proposed method is able to prevent the risk of under and over-voltage and increase load margin at a cost of a small but acceptable increase of active power loss. Specified chance-constrained handling techniques are adopted to improve the computational speed. Numerical examples validate the effectiveness of those techniques.

A probabilistic load flow method based on modified Nataf transformation and quasi Monte Carlo simulation

To expose operational risk of large-scale wind power integration system, probability distribution functions (PDFs) of input variables are required to model accurately in probabilistic load flow (PLF) analysis. Unfortunately, PDFs are difficult to obtain in reality. Therefore, a PLF method based on modified Nataf transformation and quasi Monte Carlo simulation is proposed in this paper. This method is able to establish PDF of input variables by their first several orders of moments with the employment of spline reconstruction, then quasi Monte Carlo simulation based on Sobol sequence is adopted to obtain the probability distribution of the output variables. Simulation on IEEE 30 bus system and a real power system demonstrate the validity of the proposed method. The results suggest that the proposed method not only has the advantages of modelling input variables accurately and fast convergence, but also can deal with correlation with convenience.

A stochastic power flow method based on polynomial normal transformation and quasi Monte Carlo simulation

Most common sampling methods adopted in stochastic power flow (SPF), such as simple random sampling (SRS) and Latin hypercube sampling (LHS), are of low accuracy due to their incapability in generating sampling sequences of low discrepancy. In this paper, a SPF method based on polynomial normal transformation and quasi Monte Carlo simulation method is proposed. This method utilized the numerical characteristics of input variables to reconstruct the distribution of their own by polynomial normal transformation, meanwhile, singular value decomposition is adopted to handle the scenario of non-positive definite correlation matrix. At last, Sobol sequences are generated as samples of input variables, then Monte-Carlo simulation method is adopted to attain the probability distribution and numerical characteristics of bus voltage and branch power. The test on IEEE 30 and IEEE 118 systems demonstrate the validity of the proposed method. The simulation results suggested that, compared to Latin hypercube sampling with the same sample size, the proposed method is more effective, which not only has the advantages of high accuracy and calculating efficiency, but also has better convergence characteristics.

A Modified Nataf Transformation-based Extended Quasi-Monte Carlo Simulation Method for Solving Probabilistic Load Flow

Abstract Compared to conventional probabilistic load flow analysis, the extended probabilistic load flow can be stopped by itself when the error restriction satisfied, which is more suitable in practical use. Since the power flow results already obtained can be retained, the computational burdens of extended probabilistic load flow largely depend on the extension of samples. Much of the literature suggests that the quasi-Monte Carlo simulation method is more efficient than Latin hypercube sampling. In this article, the extended technique for quasi-Monte Carlo simulation is proposed. After that, spline reconstruction is utilized to modify the conventional Nataf transformation to obtain correlated samples by the first several orders of moments. Based on the above two techniques, a modified Nataf transformation-based extended quasi-Monte Carlo simulation method is proposed to solve probabilistic load flow problems. Compared to extended Latin hypercube sampling, the proposed method not only has higher computational efficiency but can also extend the samples by arbitrary steps. The results also show that both temporal and spatial correlations can be managed by the proposed method.

Optimal Size and Location of Battery Energy Storage Systems for Reducing the Wind Power Curtailments

Abstract Both the lack of the downward regulation capacity and the transmission capacity limit have led to considerable wind power curtailments in China. The battery energy storage system (BESS) provides a new solution to reduce the wind power curtailments due to its relatively high energy density and flexible installed location. In this paper, a new bi-level programming model is proposed to optimize the size and location of BESS for reducing the wind curtailments. The revenues of BESS, when it is located either at the wind farm or the load center, are considered comprehensively. Moreover, a numerical optimization algorithm is developed to solve the proposed model. Simulation results demonstrate the validity of the proposed model and developed algorithm. They also reveal that the BESS located at the load center offers more net profit compared to the one located at the wind farm. Subsequently, sensitivity analysis is performed to assess the effect of key parameters on the optimal values of BESS.

A method to improve reactive reserve management with respect to voltage stability

Voltage stability margin is associated with reactive power reserve. From this point of view, an optimization method to schedule VAR sources is proposed. Generators have various efficiency of reactive supports to voltage stability because of their location and system condition, etc. Generator participation factor is introduced to assess the importance of generator reactive reserve. The optimization model which maximizes system reactive power reserve is proposed. The model is decomposed to generator master problem and capacitor sub-problem so as to get a better optimization result. The method is tested on IEEE_39 system, and the result shows that the proposed optimization method can improve voltage stability tremendously.

A new type of MW and MVar dispatch index for meeting voltage stability margin criteria based on normal vector of limit surface

This paper presents a new type of index for improving the power system economical dispatch from a voltage stability margin perspective. The proposed index is based on normal vector of voltage stability limit surface, which are supplement and enhancement of participation factor. Firstly, the rationality of this index is proved mathematically. Then numerical simulation on IEEE 39 system demonstrate the validity of the proposed index. Compared to the traditional indexes, proposed index has a wider range of application since it can deal with the critical point of voltage stability, both saddle node bifurcation and limit induced bifurcation. The proposed index can be utilized in active/reactive dispatch for normal operation, and also minimum load shedding strategies in case of critical contingencies.

An improved voltage stability assessment for power system with HVDC

In order to prevent voltage collapse, lots of voltage stability assessments are proposed to search weak buses. However, these assessments are either only related to network topology or time-consumed. Therefore, voltage stability extended voltage sensitivity factor (EVSF), an improved voltage stability assessment considering voltage regulation of generator and HVDC, is given and derived in this paper. And a case is illustrated and analyzed. Comparing with VSF indicator, EVSF is more considerate and sensitive to discover weak buses with multi-infeed HVDC. Its proved that EVSF is an effectiveness assessment for power system voltage stability analysis.

Optimal configuration of battery energy storage system for peak-load regulation

As is well known, the anti-peaking characteristic of wind generation leads to evident curtailments of wind farms. With high energy density and flexible installation position, the battery energy storage system (BESS) can provide a new routine to relax the bottleneck of the peak-load regulation, conducive to the absorption of wind power and the economy of system operation. Therefore, with taking account of both total costs and peak-load regulation benefits of BESS, a benefit-evaluation model for the optimal configuration of BESS is proposed in this paper. This model is formulated as a unit commitment (UC) problem, and solved by CPLEX with the utilization of piecewise linearization. The simulation on a modified IEEE 30 bus system demonstrates the validity of this model. The sensitivity analysis illustrates investment costs of BESS and wind curtailment penalties have significant impacts on the benefit evaluation and the optimal configuration of BESS.