Yiping Dai

Neuro-fuzzy networks for short-term wind power forecasting

This paper presents a statistical model based on a hybrid computational intelligence technique that merging neural networks and fuzzy logic for wind power forecasting. A mesoscale NWP model is used to forecast meteorological variables at a reference point of a wind farm for the next 36 hours at half-hour intervals. The output of the NWP model, together with measured data form SCADA and wind tower, is processed by the proposed model to accurately forecast the wind power of each wind turbine in the wind farm. The network architecture and the training algorithm are introduced. The forecasting approach is applied for the wind power forecasting of a real wind farm located in China. The root mean square errors (RMSE) between the forecasted wind power and actual wind power are less than 20%. From the forecasting results obtained, we conclude: The trained neuro-fuzzy networks are powerful for modeling the wind farm and forecasting the wind power. Due to the adaptability of neuro-fuzzy networks, the proposed approach can be integrated into an on-line wind power forecasting system that automatically be tuned during operation.

Wind speed prediction using support vector regression

In this paper the wind speed forecasting in a wind farm, applying the algorithm of support vector regression (SVR) to the mean 10-minute time series is presented. By comparing its performance with an back propagation neural network model through simulation results, we could find following facts: firstly, both algorithms are applicable for prediction the wind speed time series in future; secondly, the prediction effect of support vector regression outperforms the back propagation neural network model as indicated by the prediction graph and by the mean square errors and mean absolute errors. Finally, we selected three different stages of the wind speed curve to analyze, the results show that the proposed algorithm fit the original wind speed curve well at the whole process, but the back propagation neural network is inapplicability for the rise stage when the ascent rate suddenly become flatness of the original wind speed curve.

Research on the Primary Frequency Control Characteristics of Generators in Power System

Primary frequency control (PFC) is one of the most important means used in maintaining frequency stability of power systems. However, as a wide dead band is usually set in the governing system of generation units with digital electro-hydraulic (DEH) control system, the function of PFC in stabilizing system frequency during system emergencies is then decreased considerably. In order to study the characteristics of PFC capabilities in generating units, a mathematical model of a three-area power system is presented in this paper. The simulation study shows that PFC capacity is necessary to maintain power system frequency stability at different dead band settings. The relationship between load disturbance and PFC capacity of the system is also studied. The proposed model will provide useful guides for setting and adjustment of governing system parameters and determination of PFC capacity of power systems.

Research on the Influence of Primary Frequency Control Distribution on Power System Security and Stability

Primary frequency control (PFC) has the ability to meet the fast load variation in a power system. Many researches have been done to improve the PFC ability only taking a whole system as the object, which can not give satisfaction to the security and stability of the multi-area power system as it becomes a developing trend in practice. Therefore, it is practically important to study the PFC ability distribution on power system security and stability in multi-area power system. In this paper, a new concept of PFC ability distribution of multi-area power system is presented. The influences of PFC ability distribution on power system frequency characteristics and tie-line power transmission are analyzed with simulation method. It is concluded that uniform PFC ability distribution is a reasonable form for multi-area power system.

Thermodynamic Comparison and Optimization of Supercritical CO2 Brayton Cycles with a Bottoming Transcritical CO2 Cycle

AbstractThis study investigated the feasibility of a combined cycle comprising a topping SCO2 cycle and a bottoming TCO2 cycle (SCO2-TCO2 cycle). A simple SCO2 cycle and a recompression SCO2 cycle were considered as the topping configurations. Thermodynamic analyses and comparison were performed to evaluate the effects of key thermodynamic parameters on the behavior of combined SCO2-TCO2 cycles. In addition, a parameter optimization was achieved by means of a genetic algorithm to reach the maximum overall thermal efficiency. The results show that the thermal efficiency of the simple SCO2-TCO2 cycle increased with an increase in SCO2 turbine expansion ratio and compressor inlet temperature. However, for the recompression SCO2-TCO2 cycle the thermal efficiency increased and then decreased as the SCO2 turbine expansion ratio increased. Both the modified SCO2 cycles with a bottoming TCO2 cycle had higher performance, with thermal efficiency increase of 10.12 and 19.34% for combined recompression and simple co...

Experimental Evaluation of the Regenerative and Basic Organic Rankine Cycles for Low-Grade Heat Source Utilization

AbstractThe present paper conducts the experimental evaluation of the performance of a regenerative organic Rankine cycle (ORC) system working with refrigerant R123 and generating 10-kW-level power. The ORC system consists of an axial-flow single-stage turbine, a regenerator, an evaporator, a condenser, and a pump. The regenerative ORC and the basic ORC system efficiency are evaluated under the same conditions. The degree of superheat of the turbine inlet vapor is controlled by the evaporating temperature. The cooling water flow rate is controlled by adjusting the opening of the valve. The experiment results show that the thermal efficiency of the regenerative ORC is higher than that of the basic ORC by about 25%. The thermal efficiency of basic ORC with saturated vapor at turbine inlet is higher than that with superheated vapor by 3.2%, and the thermal efficiency of the regenerative ORC with saturated vapor at turbine inlet is higher than that with superheated vapor by 4.36%. The enthalpy drop across the...

Thermo-Economic Analysis of a Recompression Supercritical CO2 Cycle Combined With a Transcritical CO2 Cycle

The transcritical CO2 cycle (TCO2 cycle) exhibits good performance in low-grade waste heat recovery area. In this study, a TCO2 cycle was employed as a bottoming cycle to recover the waste heat in the topping recompression supercritical CO2 Brayton cycle (SCO2 cycle). A detailed system analysis was performed of a recompression SCO2 cycle combined with a TCO2 cycle to improve the efficiency of energy conversion. Thermodynamic analysis, calculation of heat exchangers’ area and economic analysis were considered. The SCO2 turbine expansion ratio, TCO2 turbine inlet pressure, high temperature recuperator (HTR) effectiveness and condensation temperature were studied to investigate their effect on the system performance. For the basic analysis, SCO2 turbine inlet temperature was conservatively selected to be 550 °C and the compressor outlet pressure set at 20 MPa. For these operating conditions the proposed combined SCO2-TCO2 cycle yielded about 46% thermal efficiency at a SCO2 turbine expansion ratio of 2.7 and TCO2 turbine inlet pressure of 10 MPa. Similarly, the capital cost per net power output of the combined cycle was found as 6.6 k

Analysis of power system frequency responses with hydro turbines incorporating load shedding

/kW, which was ∼ 6% more expensive than that of the recompression SCO2 cycle without the bottoming cycle under the same operating condition. An optimum TCO2 turbine inlet pressure and an optimum SCO2 turbine expansion ratio existed where the system thermal efficiency reached the maximum value. Furthermore, the system thermal efficiency was very sensitive to the changes in the condensation temperature and the HTR effectiveness. The HTR effectiveness also had a strong effect on the ratio of heat exchangers’ cost to the plant capital cost. Additionally, increasing SCO2 turbine inlet temperature would significantly improve the cycle overall thermal efficiency and decrease the plant capital cost per net power output.Copyright

A new framework for power system identification based on an improved genetic algorithm

As shown in many recent works, the load-frequency behavior can be represented by system frequency response models especially for an islanding process. In this paper, a frequency response model incorporating an under-frequency load-shedding scheme is presented for islanding power system simulations. The model was applied for a practical power system with both hydro and fossil-fired power generators. The governing system models are involved in the model, which have great impact on the system dynamics. Parameter identification method is used to find and verify the model parameters. Similar responses were observed between the simulations and the accident records. The simulation results showed disadvantages of the primary frequency control systems of hydro power generators at the beginning of the load disturbances. An closed fossil fired power plant is proposed to serve against the load disturbances and improved stability was observed according to the system simulation results.

Impact of Overspeed Protection Control on Stability for Islanded Power System

Accuracy parameters of system model are of great importance in stability and security evaluation or simulation for power system. Some of the conventional methods may have inadequate adaptability or effectiveness for identification of different power systems. A new framework for power system identification is proposed based on an improved genetic algorithm with a logarithmic fitness function and an adaptive search space. The framework can be used for most power system models (linear or nonlinear) and can easily be performed on different models just by rebuilding corresponding map lists between the system parameters and the model coefficients. The numerical experiment and practical experiment of a 600MW steam turbine unit are conducted to examine the performance of the framework. The identification results have demonstrated the effectiveness of the proposed framework.