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Zhao J.,Hohai University | Tang J.,Hohai University | Luo W.,Liaoning Electrical Power Dispatching Control Center | Zhao J.,Liaoning Electrical Power Dispatching Control Center
Proceedings - 2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation, IMSNA 2013 | Year: 2013

A novel day-ahead generation scheduling and spinning reserve determination model was proposed for power grid with large-scale wind power. The load shedding losses and the wind curtailment losses were estimated by using the probability density function. And they are taken as two operation risk costs integrated into the generation cost objective function. While fully meeting the unit ramp rate constraints and the network security constraints, the day-ahead generation schedule of conventional units and the up/down spinning reserve capacities were solved simultaneously. The priority list method and the minimum marginal cost based economic dispatch algorithm are used to solve the proposed model. Numerical results of modified IEEE reliability test system show that the proposed model and method are effective. © 2013 IEEE. Source


Zhao J.Q.,Hohai University | Zhang C.L.,Hohai University | Luo W.H.,Liaoning Electrical Power Dispatching Control Center | Zhao J.,Liaoning Electrical Power Dispatching Control Center
Advanced Materials Research | Year: 2014

Among the solving methods of probabilistic optimal power flow (P-OPF), Monte Carlo Simulation (MCS) combined with random sampling (RS) is widely used due to its high accuracy. In order to further improve that, this paper proposes a way of using Monte Carlo Simulation with Latin hypercube sampling (LHS) to calculate the consumption of generating cost under many random variables. Numerical results of IEEE 14-bus and IEEE 118-bus systems show that the Latin hypercube sampling method provides more accurate performance in dealing with POPF under the condition of a smaller sample size, comparing with random sampling method. Thus the Latin hypercube sampling method can replace the MCS with random sampling as the benchmark method of other algorithms. © (2014) Trans Tech Publications, Switzerland. Source


Liu X.-T.,Hohai University | Zhao J.-Q.,Hohai University | Luo W.-H.,Liaoning Electrical Power Dispatching Control Center | Zhao J.,Liaoning Electrical Power Dispatching Control Center
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2013

The correlation among input variables in power system affects the accuracy of probabilistic load flow (PLF) calculation. A PLF algorithm is proposed based on third-order polynomial normal transformation (TPNT) combining cumulants and Gram-Charlier expansion. The method that transforms a multivariate non-normal dependent random variables group into a multivariate standard normal independent one is used to calculate input variables and power flow based on correlation coefficient matrix and draw cumulative distribution curves of node status variables and load flow. The simulation results of the IEEE14-bus system with several correlative wind farms show that the proposed method is effective and accurate. Source


Zhao J.,Hohai University | Tang J.,Hohai University | Luo W.,Liaoning Electrical Power Dispatching Control Center | Zhao J.,Liaoning Electrical Power Dispatching Control Center
Dianli Zidonghua Shebei/Electric Power Automation Equipment | Year: 2014

A day-ahead generation scheduling and spinning reserve decision-making model is proposed for power system with large-scale wind power. The power outage loss and wind curtailment loss of system are estimated with the probability density functions of random wind power and power loads, which, as the risk cost, are integrated into the objective function of generation cost. The day-ahead generation schedule of each conventional unit and the up/down spinning reserve capacity are calculated with the constraints of unit ramp rate and system security. The priority list method and the economic dispatch algorithm based on the minimum marginal cost are adopted to solve the model. Results of case analysis show that, the proposed model and method are effective. Source

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