Due to the growing demand on renewable energy, photovoltaic (PV) generation systems have increased considerably in recent years. However, power output of PV is affected by different weather conditions. Accurate forecasting important for system reliability and promoting large-scale deployment. This paper proposes algorithms forecast based upon classification support vector machines (SVM). In process, conditions are divided into four types which clear sky, cloudy day, foggy rainy day. this...

Very-short term wind power forecasting is one of the most effective ways to deal with challenges increased penetration into electric grid due its fluctuation and volatility. To improve by taking advantage each independent model, a hybrid model proposed means grey relational analysis speed distribution features. The weight estimated according different subsection similar frequency. case study shows that has broader applications in very-short (15-minute-ahead) output forecasting.

The prediction algorithm is one of the most important factors in quality wind-power prediction. In this paper, based on principles wavelet transform and support vector machines (SVMs), as well characteristics wind-turbine generation systems, two methods are presented discussed. method 1, time series model input decomposed into different frequency modes, models set up separately SVM theory. results combined together to forecast final output. For comparison purposes, kernel function applied...

As the output from wind power generation is intermittent in nature, making "dependable" critical for seamless integration of generation. One most favorable solutions incorporating energy storage system (ESS) with farms to establish a wind-energy hybrid system. Since it requires capital investment ESS installation, important estimate appropriate capacity and charging/discharging rate desired applications. In this paper, fluctuation feature analyzed both time domain frequency domain. The...

The precision and reliability of distributed photovoltaic (PV) power forecasting play a crucial role in commercial PV plants for integration operation. However, the stochastic intermittent nature solar radiation affects accuracy. What's more, diverse location various meteorological information have brought challenges to real-time forecasting. Therefore, it is more difficult than centralized power. To solve this problem, we propose four-stage space-time hybrid method plants. Firstly, Global...

In recent years, configuring battery energy storage system (BESS) in wind farm has become the most popular method to smooth power fluctuation. The effectiveness of fluctuation smoothing relies on charging/discharging control and state charge (SOC) regulation BESS. This study proposed a novel optimising SOC approach for BESS which could regulate suitable level maintain an optimal range by utilising prediction information. A prediction‐based calculation module is designed obtain makes have...

Cloud computing is popular in nowadays for its convenient and cheap. Grid provides services of available everywhere, shares everyone. Therefore, smart grid cloud a good way to manage data sharing with all power supply stations. task scheduling one the key technologies that affect resource allocation efficiency environment. The advantages disadvantages algorithms will directly performance both stability entire system platform. problem has been proved be NP-hard problem, traditional algorithm...

Based on the characteristics of power curves wind turbine generator systems and principles support vector machine (SVM), a piecewise (PSVM) model is proposed in this article to improve precision short-term wind-power prediction systems. The operation data from farm north China are used verify model, average mean error root squared PSVM 4.76% 68.83 kW less than that an SVM respectively. Results parameter optimization confirm robustness model.

This study explores the relationship between morphology and solar potential of high-density areas in subtropics high density city known as Shanghai. 1260 parametric scenarios were modeled their irradiation potentials simulated via a customized workflow. In addition to five well-known morphological parameters, this proposed two innovative parameters SSU600 SSU400, which captured receiving properties building envelopes could be easily calculated based on meteorological data. For analytical...

Due to the fluctuation and randomness of photovoltaic power over time, accurate reliable ultra-short-term forecasting is significant for real-time dispatch frequency regulation grids. In this article, improved BO-LSTM frame considering correlation mapping proposed. Firstly, features are extracted resolved according series segments. Then, established model adjusted based on above in separate segment, results deterministic obtained. Furthermore, order obtain performance, time-correlation...

The prediction algorithm is an important key factor in wind power prediction. However, there are pros and cons on different forecasting algorithms. Based the principles of wavelet transform (WT), support vector machine (SVM) as well characteristics turbine generation systems, two methods presented compared this paper. In method 1, time series model input decomposed into frequency composes models set up separately based SVM. results combined together to obtain final output. 2, kernel function...

In recent years, the Internet of Things (IOT) has drawn considerable attention from industrial and research communities. Due to vast amount data generated through IOT devices users, there is an urgent need for effective search engine help us make sense this massive data. With motivation, we begin our initial works on developing a secure efficient (SecDS) based EPC Discovery Services (EPCDS) EPCglobal network, integral part IOT. SecDS designed provide bridge between different partners supply...

Fine-grained access control (FGAC) must be supported by relational databases to satisfy the requirements of privacy preserving and Internet-based applications. Though much work on FGAC models has been conducted, there are still a number ongoing problems. We propose new model which supports specification open policies as well closed in databases. The negative authorization is supported, allows security administrator specify what data should not accessed certain users. Moreover, multiple...

Capacity and output power forecasting have great significance in seamless integration of renewable energy to the grid. However, uncertainty wind intermittence are main factors which affect precision. The data can be treated as a signal stream has characteristics for possible capacity forecasting. Hilbert-Huang Transforms (HHT) Hilbert spectral analysis been applied extensively nonlinear non-stationary stochastic signal. time series transformed into certain signals with different frequencies....