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In the paper the methods of probabilistic load flow, including linear method of generalized disturbance, are used to detect sensor variables in an electric power system, identify their probabilistic characteristics, detect critical variables, for which the probability that they lie in the feasible range is lower than the required one, and select the control actions to increase this probability. The...
For the approximation of low-voltage grid dynamics we present an energy based bottom-up model to create highly diverse household load profiles. In an object-oriented approach, nodal loads are represented by classifications of appliances and distributed to the phases in order to consider the characteristically unbalanced load of residential customers over time. Probability parameters, regarding time...
The energy transition will bring large changes to residential load profiles. In order to assess whether the current low voltage (LV)-grids are capable of handling these changes, future scenario analysis must be used to assess the grid adequacy. To this end, an approach is proposed, incorporating scenario-based household load modelling, LV-feeder clustering and probabilistic load flow calculations...
This paper deals with the definition of demand flexibility time intervals. These intervals are extracted from the binomial probability model of load variation patterns with the two possible categories of increase and non-increase in demand. These intervals along with the information on the coefficient of variation of the aggregate demand are used to assess the potential of demand flexibility exhibited...
Evaluating the performance of various power system reliability criteria and their management is important in order to obtain a cost effective reliability level of the power system. However, the performance of reliability criteria depends on several parameters, of which one is value of lost load (VoLL). Value of lost load is typically difficult and complex to model, which hampers making a general conclusion...
Due to renewable energy sources (RES) variable nature and their wide integration into power systems, setting an adequate operating power reserve is important to compensate unpredictable imbalance between generation and consumption. However, this power reserve should be ideally minimized to reduce system cost with a satisfying security level. Although many forecasting methodologies have been developed...
This paper presents a probabilistic network usage computing using distribution factors method. A software tool is developed in Mathlab environment and contains a part dedicated to probabilistic power flow computing and another part allocated to network usage allocated to generators and consumers. Case study is applied on West, South-West and North-West parts of Romanian Power System. Useful results...
This paper proposes a multi-agent model and strategy for aggregator-based residential demand response, and details how elements in the system interact to solve an issue requiring load to be temporarily decreased. The system uses assets such as plug-in hybrid electric vehicles, air conditioning units, and electric water heaters to achieve this goal. Simulation results, based on probabilistic models...
This paper introduces the concept of a probabilistic indicator to aid power system operator decision making during short-time emergency loadings stemming from operational uncertainty. It is based on a state based Monte Carlo sampling method and is thus able to capture the stochastic nature of power system operation. The methodology developed within this paper also incorporates conductor properties...
Power systems are vulnerable to both natural and man-related threats. The resulting contingencies - either single or multiple - may lead to wide-spread blackouts. However, the probabilities of the different events span over a wide range, hence the associated risk may be quite diverse. To address these issues a probabilistic risk assessment methodology and tool were developed within the Seventh Framework...
This paper presents a Monte-Carlo based approach for probabilistic estimation of rated demand at bulk supply point at different times during the day. The required data are substation measured RMS real power, reactive power and voltage. Along with component-based load modeling approach, Monte-Carlo simulation is used to generate all possible combinations of percentages of different load categories...
This paper compares the most commonly used ensemble decision tree methods for on-line identification of power system dynamic signature considering the availability of Phasor Measurement Units (PMU) measurements. Since previous work has shown that the surrogate split method included in classification and regression tree is not good enough to handle the unavailability of measurement signals, more effective...
It poses high requirements for the calculation speed and the precision of the solving method when we consider the large-scale transmission expansion planning (TEP) problems. Therefore, combined with the respective characteristics of EDA (Distribution of Estimation Algorithm) and DE (Differential Evolution algorithm), this paper puts forward a new hybrid EDA/DE algorithm for large-scale TEP problems...
In the context of transmission system planning, research proposes methods to assess the effect of uncertainties of power system operating condition due to forecasting errors of intermittent generation and loads. In particular probabilistic power flow methods are illustrated to calculate the probability distributions of the voltages and the branch currents, starting from the distributions of power...
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