Impact Of Wind Power Generation Research Articles

Hybrid Energy Storage Power Allocation Strategy for Stabilizing Wind Power Fluctuations

In order to solve the problem of energy shortage, renewable energy such as wind power has developed rapidly worldwide. However, due to its time-varying and uncertain nature, wind power is prone to local fluctuations and operational safety hazards when connected to the power grid. In response to the stable grid connection problem of wind power generation, a hybrid energy storage system is proposed A method was proposed to achieve smooth power fluctuations in wind power generation using a model, and a charging and discharging control and allocation method for energy storage was proposed. Firstly, the preliminary power of hybrid energy storage was obtained using the model predictive control method, Then, an adaptive variational mode decomposition method was used to achieve energy distribution between batteries and supercapacitors. Finally, the measured data of a 100MW wind power plant in Xinjiang was analyzed as an example. The proposed method has been validated to not only achieve reasonable power allocation between hybrid energy storage systems, but also effectively reduce the impact of wind power generation on the power grid, achieving long-term safe operation of hybrid energy storage systems.

A probabilistic approach to assess the impact of wind power generation in transmission network expansion planning

A probabilistic approach to assess the impact of wind power generation in transmission network expansion planning

The Long-Term Impact of Wind Power Generation on a Local Community: Economics Analysis of Subjective Well-Being Data in Chōshi City

In this study, we analyzed the external effects of wind turbines, which are often considered detrimental to the promotion of wind power generation. Understanding these externalities is essential to reaching a consensus with residents who live near the site of a planned wind turbine. Our research objective was to determine the relationship between wind turbines and people’s well-being in areas where they have been installed for a long time. We hypothesized that wind turbines would have a negative impact on people’s well-being. We conducted a survey by postal mail in Chōshi City, Chiba Prefecture, Japan, to examine the external effects of wind turbines, adopting a subjective well-being index to measure respondents’ well-being. Regression analysis suggests that having a view of wind power turbines has a positive effect on the subjective well-being of local residents. Moreover, the results indicate that such well-being increases with increasing distance from the turbines. Except for scenic elements, we found that wind turbines are not always considered desirable by residents. Therefore, it is important to further clarify the external influence of wind turbines and other facilities in local communities.

Impact of wind power generation on ATC calculation with uncertain equal load

Available transfer capability (ATC) is very important for system operators for a fair and transparent electricity market. There are many methods to calculate and to improve the ATC value in the power system. Due to green energy focus across the globe, renewable energy integration to the system to improve the ATC value need to be established. Lots of literature have been published on wind power integration to improve ATC value using active power support. During highly loaded conditions, reactive power plays an important role. In this paper, active as well as reactive power of wind turbine generation for ATC calculation has been considered. The reactive power limit has been considered based on the capability curve of the wind turbine generator. Real-time wind speed data for wind power output calculation are taken. The impact analysis of wind power generation on ATC variation under normal as well as contingency cases has been carried out. The effectiveness of the proposed method is tested on the IEEE-30 bus system.

Assessment of wind power generation impact on the distance protection operation

In the article an experimental power system consisting of Russian equipment, as well as 220 kV power line distance protection, are simulated in the RTDS Simulator. The settings were calculated and the polygonal characteristics of distance protection were constructed. A sequential installation of wind turbines into various nodes of the power system was carried out and the correct operation of the protection was verified. As a result of the study, the impact of wind turbines on the distance protection when they are connected between the protection installation site and the point of the short circuit is revealed. The analysis of this impact is made. Possible ways to solve the identified problems are proposed, such as the use of adaptive distance protection, as well as numerous studies of the behaviour of wind turbines in various operating modes for further analysis and possible adjustment of guidelines for relay protection using new algorithms for calculating and configuring of distance protection. The results of this work can be used to improve and clarify the recommendations for tuning, produced by manufacturers of relay protection devices, which currently do not take into account the impact of wind power generation.

Mixed Copula-Based Uncertainty Modeling of Hourly Wind Farm Production for Power System Operational Planning Studies

An effective model to represent real-world wind power production scenarios is essential for an accurate assessment of the impact of wind power generation on power systems. Such a model should capture the spatial and temporal correlations between different wind turbines that are part of a wind farm. Accurate modeling of these correlations will ensure that the wind power uncertainty can be properly quantified. This is especially critical when analyzing systems with high penetration of wind power productions. This paper addresses this critical need by developing the Hourly Mixed Copula Model , a new probabilistic model, based on Gaussian and Archimedean copulas, to model the uncertainty and variability of wind power generation. This model enables the simulation of realistic scenarios of a wind farm power production. Metrics such as the Euclidean distance and Kullback-Leibler divergence are used to demonstrate the effectiveness of the developed model in incorporating the spatio-temporal dependence among the turbine power productions. The impact of accurate characterization of uncertainty in wind power modeling on power system steady-state operational planning is also demonstrated by case studies. These studies indicate that, in order to correctly evaluate the effect of wind power variation on steady-state operational planning, the dependence among wind power resources should not be neglected for power flow studies.

Wind Power Prediction Based on Extreme Learning Machine with Kernel Mean p-Power Error Loss

In recent years, more and more attention has been paid to wind energy throughout the world as a kind of clean and renewable energy. Due to doubts concerning wind power and the influence of natural factors such as weather, unpredictability, and the risk of system operation increase, wind power seems less reliable than traditional power generation. An accurate and reliable prediction of wind power would enable a power dispatching department to appropriately adjust the scheduling plan in advance according to the changes in wind power, ensure the power quality, reduce the standby capacity of the system, reduce the operation cost of the power system, reduce the adverse impact of wind power generation on the power grid, and improve the power system stability as well as generation adequacy. The traditional back propagation (BP) neural network requires a manual setting of a large number of parameters, and the extreme learning machine (ELM) algorithm simplifies the time complexity and does not need a manual setting of parameters, but the loss function in ELM based on second-order statistics is not the best solution when dealing with nonlinear and non-Gaussian data. For the above problems, this paper proposes a novel wind power prediction method based on ELM with kernel mean p-power error loss, which can achieve lower prediction error compared with the traditional BP neural network. In addition, to reduce the computational problems caused by the large amount of data, principal component analysis (PCA) was adopted to eliminate some redundant data components, and finally the efficiency was improved without any loss in accuracy. Experiments using the real data were performed to verify the performance of the proposed method.

Short-term prediction of market-clearing price of electricity in the presence of wind power plants by a hybrid intelligent system

This paper provides a new hybrid intelligent method for short-term prediction of the market-clearing price of electricity in the presence of wind power plants. The proposed method uses a data filtering technique based on wavelet transform and a radial basis function neural network, which is utilized for primary prediction. The main prediction engine comprises three MLP neural networks with different learning algorithms. To get rid of local minimums and to optimize the all neural networks, the meta-heuristic Imperialist Competitive Algorithm method is used. The input data for network training belong to the Nord Pool power market. The information includes a complete set of the historical record on electricity price and wind power generation. Moreover, the simultaneous impact of wind power generation is analyzed to predict the market-clearing price. Besides, the correlation coefficient factor is provided to consider the impact of wind power in forecasting the electricity price. Simulation results show the supremacy of the proposed method over other methods, to which it has been compared in this study. Also, the prediction error decreases significantly.

The impact of wind-power generation on the planning of regulating reserve

This doctoral thesis focuses on the efficient management of a power system with a large share of wind-power generation and on the methods for planning the operating reserve. The approach proposed in this research involves the use of data directly from the network’s dispatch center and the forecasting systems, as well as already existing day-ahead plans for wind and load power to determine the regulating reserve for the load frequency control (LFC). The same principle is used to find the optimal regulating reserve distribution (RRD) between the available generation units in the system for automatic generation control. It is developed using iterative power-flow computation with a reactive power correction and a stochastic search algorithm for transmission-loss minimization. Moreover, variations in the generation of individual wind-power plants (WPPs) from the plan are considered in the optimal RRD. A special focus of this research has been put on the Croatian power system due to the accessibility of relevant information and operating data. The obtained results of the testing with actual data from the Croatian power system indicate substantial savings in ancillary service costs for the LFC, while ensuring safe system operation. The considerable impact of variations from the plan for each individual WPP generation on the optimal RRD was also identified. Comparing the results for the daily sum of regulating reserves obtained with the proposed and the currently used approaches, the corresponding costs indicate a total saving of 21.2% for all 12 selected days in 2015 when using the proposed approach. In practice, a part of the reserve can be slow, i.e., with a lower unit price, thus the savings would be even higher. Furthermore, the obtained optimal RRD computed according to the proposed approach was compared with four commonly used RRDs in Croatia. The results obtained using the proposed approach indicate a decrease in the total transmission losses of between 1% and 2%. With a larger share of the generation from the WPPs and with more dispersed locations of the WPPs and regulating power plants a larger reduction in the transmission losses is expected.

Impact of wind power generation on a large scale power system using stochastic linear stability

The effect of random and sustained disturbances is studied in this paper. The Ornstein–Uhlenbeck stochastic process is proposed with the aim to represent the variations in the power output produced by wind power generation, considering measurements of a wind farm located in the fourth region of Chile as real field data for its parameters calibration. An example is provided considering the study of the exponential stability using the Lyapunov exponent as an indicator, with the aim to determine the maximum size of a wind farm that can be connected in a busbar of one of Chile’s interconnected power system (Sistema Interconectado del Norte Grande, SING), considering successive increments from the output power from the connected wind farm.

Impact of Wind Power Generation on System Operation and Costs

In this paper, a deterministic security-constrained unit commitment (SCUC) model is deployed in order to optimize generation output and allocation for spinning reserve considering different wind power dispatch modes. In this model, the scheduling of power plants takes into account a simultaneous clearing of power, reserve capacity requirement and CO2 emission and so on. Spinning reserve is modelled as an exogenous parameter which represents load uncertainty and wind power uncertainty. Special attention in the study is given to determine the impact of different dispatch modes with wind power and different levels of spinning reserve requirement on system operation and costs. The proposed model can be formulated as a mixed-integer problem (MIP) and solved in GAMS by using the CPLEX optimizer. The model is applied to a wind-fired intensive power system for three case studies. The results include the optimal spinning reserve and generator output of each generator, CO2 emission cost and cost of wind power for each case study. The results show that taking wind power as a control option can improves system operation and costs if wind generation and traditional sources generation are coordinated properly.

The impact of wind power generation on the electricity price in Germany

This paper investigates the relationship between intermittent wind power generation and electricity price behaviour in Germany. Using a GARCH model, I evaluate the effect of wind electricity generation on the level and the volatility of the electricity price in an integrated approach. The results show that variable wind power reduces the price level but increases its volatility. This paper's results also indicate that regulatory change has stabilised the wholesale price. The electricity price volatility has decreased in Germany after a modification of the marketing mechanism of renewable electricity. This gives confidence that further adjustments to regulation and policy may foster a better integration of renewables into the power system.

Impact of Wind Power on the ATC Values in Hydro- Dominated Power System

The wind power generation is increasing in many countries as a result of decreasing technology costs, active government policies for renewable energy sources, environmental concerns, etc.. This paper investigates the impact of wind power generation on ATC (available transmission capacity) calculation. In order to determine the maximum incremental MW transfer possible between two parts of a power system without violating any specified limits, ATCs are calculated. When calculating ATC values, it is necessary to assume production and consumption pattern in power system. Production of wind power depends on the wind speed, which is a random variable and it is impossible to forecast exactly the production of wind power that is needed for the ATCs calculation. In order to investigate influence of the stochastic wind power production on the ATCs value, computer model of Croatian electric power system is made in Power World Simulator. ATCs are calculated for southern part of Croatian power system in which besides wind power, hydro power plants are only type of power generation. Available wind speed measurements are used as input data for wind power production. The results of the ATC calculation for different scenario of wind power production and location in the Southern Croatian power system are presented and discussed in the paper.

Impact of Wind Power Generation on European Cross-Border Power Flows

A statistical analysis is performed in order to investigate the relationship between wind power production and cross-border power transmission in Europe. A dataset including physical hourly cross-border power exchanges between European countries as dependent variables is used. Principal component analysis is employed in order to reduce the problem dimension. Then, nonlinear relationships between forecast wind power production as well as spot price in Germany, by far the largest wind power producer in Europe, and power flows are modeled using local polynomial regression. We find that both forecast wind power production and spot price in Germany have substantial nonlinear effects on power transmission on a European scale.

Long term impact of wind power generation in the Iberian day-ahead electricity market price

The Iberian power systems went through important changes at the legal, regulatory and organizational levels in the last 20 years. One of the most relevant ones was the increasing penetration of distributed generation, namely wind parks, together with the development of the common market involving Portugal and Spain. In Portugal, distributed generation is paid using feed in tariffs while in Spain it can choose between receiving a regulated feed in tariff or the market price plus a participation prize. The feed in scheme is now under discussion since it is argued that it represents an excessive cost that is internalized in the end user tariffs. However, this discussion is frequently conducted without complete knowledge of the real impact of wind power on the electricity market price, since it contributes to reduce the demand on the market thus inducing a price reduction. To clarify these issues we used a long term System Dynamics based model already reported in a previous publication to estimate the long term evolution of the market price. This model was applied to the Iberian generation system using different shares of wind power capacity to quantify the impact of wind power on the day-ahead electricity market price.

Impact Analysis of Wind Farms in the Jeju Island Power System

This paper presents modeling and impact analysis of wind farms in Jeju island power system, which is made of wind farms, a current source-type high-voltage, direct current (HVDC) system, and thermal power plants. In this paper, four kinds of major components are modeled: a total of 88 MW wind farms, a 300 MW HVDC system, thermal power plants, and the Jeju power system load. To analyze the impact of the wind power generation to the Jeju power system, simulation is carried out for two case studies by using the PSCAD/EMTDC program. One is for the steady-state operation under different wind speed, and the other is for the transient-state operation when all wind farms are disconnected suddenly from the Jeju power grid due to the wind speed higher than the rated value. These comparative studies have been effective in accessing the impact of wind power generation on the Jeju island power system stability.

Assessing the Impact of Wind Power Generation on Operating Costs

Wind power generation is taking an increasing share of the overall energy production in many power systems. While its low marginal operating cost reduces the overall cost of meeting the demand for electrical energy, the stochastic and intermittent nature of wind generation increases the uncertainty that the system operators face and obliges them to procure additional reserve capacity. This paper presents a methodology for quantifying fully the effect of wind power generation on the various components of the cost of operating the system.

퐁력전원이 피크타임과 발전설비구성에 미치는 영향분석: 제3차 신재생에너지 기술개발 및 이용.보급 기본계획 기준

Although renewable power is regarded a way to active response to climate change, the stability of whole power system could be a serious problem in the future due to its uncertainties such as indispatchableness and intermittency. From this perspective, the peak time impact of stochastic wind power generation is estimated using simulation method up to year 2030 based on the 3rd master plan for the promotion of new and renewable energy on peak time. Result shows that the highest probability of wind power impact on peak time power supply could be up to 4.41% in 2030. The impact of wind power generation on overall power mix is also analyzed up to 2030 using SCM model. The impact seems smaller than expectation, however, the estimated investment cost to make up such lack of power generation in terms of LNG power generation facilities is shown to be a significant burden to existing power companies.