An energy-based method to locate oscillation sources in power systems is proposed. The energy identical the transient energy. amount of consistent with amplitude, and then component producing has negative contribution damping considered as source. consistency dissipation torque a generator proved. A compute flow network based on wide area measurement system data independent functions or production can be obtained from net flow. components are emergency control actions should taken them....

Wind energy integration research generally relies on complex sensors located at remote sites. The procedure for generating high-level synthetic information from databases containing large amounts of low-level data must therefore account possible sensor failures and imperfect input data. is highly sensitive to quality. To address this problem, paper presents an empirical methodology that can efficiently preprocess filter the raw wind using only aggregated active power output corresponding...

Due to the strict requirements of extremely high accuracy and fast computational speed, real-time transient stability assessment (TSA) has always been a tough problem in power system analysis. Fortunately, development artificial intelligence big data technologies provide new prospective methods this issue, there have some successful trials on using intelligent method, such as support vector machine (SVM) method. However, traditional SVM method cannot avoid false classification,...

The real-time transient stability assessment (TSA) and emergency control are effective measures to suppress accident expansion, prevent system instability, avoid large-scale power outages in the event of failure. However, is extremely demanding on computing speed, traditional method not competent. In this paper, an improved deep belief network (DBN) proposed for fast stability, which considers structural characteristics construction loss function. Deep learning has been many fields, but...

To cope with the uncertainty and variability of wind power, it is important for power system to maintain adequate reserve capacity. The energy storage ability district heating (DHS) provides considerable flexibility combined heat (CHP) units, hence CHP can also participate in capacity service. However, operation restricted not only by its condition, but DHS which brings difficulty quantifying flexibility. This paper focuses on properly assessing utilizing available units as well addressing...

Stable and safe operation of power grids is an important guarantee for economy development. Support Vector Machine (SVM) based stability analysis method a significant started in the last century. However, SVM has several drawbacks, e.g. low accuracy around hyperplane heavy computational burden when dealing with large amount data. To tackle above problems model, algorithm proposed this paper optimized from three aspects. Firstly, gray area model judged by probability output corresponding...

A newly proposed oscillation energy analysis method for power system low frequency is further developed. The flow in a generator and the dissipations of field winding damper are studied. flows into actually correspond to electric transferred windings. average powers dissipation modes with different frequencies decoupled. For an individual mode, computed using eigenvector coefficient obtained. real-part eigenvalue negatively proportional sum coefficients all generators. It means composite...

In recent years, the energy storage system (ESS) has been demonstrated to be involved in many aspects of integration wind power. For ESS application, allocation installation location, power rating, and rating is first concern. Different from previous studies, this study emphasises significance operation allocation. A bi‐level‐programming‐based model proposed take interaction into consideration at same time, with external level optimising internal operation. The complexity assessment solution...

The uncertainty of wind power forecasting significantly influences systems with high percentage generation. Despite the error causation, temporal and spatial dependence prediction errors has done great influence in specific applications, such as multistage scheduling aggregated integration. In this paper, Pair-Copula theory been introduced to construct a multivariate model which can fully considers margin distribution stochastic characteristics errors. have modelled, their on integrations...

As renewable energy sources are extensively incorporated into electrical grids, the necessity for enhanced flexibility and stability within power system has significantly grown., Demand Response (DR) attracted widespread attention as an effective load management tool. This study delves master-slave game theory-based demand response strategy integrated with energy, aiming to optimize interaction mechanism between grid operators users participating in through a game-theoretic framework,...

Transient stability assessment is examined in a data driven framework. The original transient are embedded into low-dimensional representation space using deep belief network (DBN) based nonlinear learning method. Specifically, unsupervised pre-training used to learn the distribution first, and then expected classification accuracy (ECA) index fine-tune parameters of DBN. structure power grid also considered process. In space, simple linear model utilized classify unstable cases from stable...

With the increasing complexity of power system structures and penetration renewable energy, number possible operation modes increases dramatically. It is difficult to make manual flow adjustments establish an initial convergent that suitable for mode analysis. At present, problems low efficiency long time consumption are encountered in formulation modes, resulting a very limited generated modes. In this paper, we propose intelligent adjustment generation model based on deep network...

The accuracy of wind power forecasting has a very important influence on the safe and stable operation system. However, prediction is difficult, especially under environment massive data. This paper presents novel multi-step ahead model based recurrent neural network (RNN) with long short-term memory (LSTM) unit or gated (GRU) to improve accuracy. Firstly, an overall framework for diverse forms optional hybrid models proposed. Moreover, innovative LSTM/GRU-based developed speed correction...

Recently, [Li, Nguyen, Woodruff, STOC'2014] showed any 1-pass constant probability streaming algorithm for computing a relation f on vector x ∈ {−m, − (m 1), ..., m}n presented in the turnstile data stream model can be implemented by maintaining linear sketch A · × mod q, where is an r n integer matrix and q = (q1, qr) of positive integers. The space complexity not including random bits used sampling matches optimal algorithm. We give multiple strengthenings this reduction, together with...