This paper presents a real-time dispatching model for electric autonomous vehicle (EAV) taxis that combines mathematical programming and machine learning. The EAV taxi problem is formulated solved as an integer linear program maximizes the total reward serving customers. optimal dispatch solutions are generated by simulating dispatched optimization model. artificial-neural-network-(ANN)-based w...

Residential loads, especially heating, ventilation and air conditioners (HVACs) electric vehicles (EVs), have great potentials to provide demand flexibility which is an attribute of grid-interactive efficient buildings (GEB). Under this new paradigm, EV HVAC aggregator models are first developed in paper represent the fleet GEBs, aggregated parameters obtained based on a approach data generatio...

Network reconfiguration and emergency power vehicles (EPVs) dispatching are widely used in distribution networks for load restoration. However, their capabilities limited by the allocated amounts of circuit breakers EPVs. E-taxis can also participate restoration as a kind mobile energy storage using vehicle to grid (V2G) technology. uncertainty should be considered To achieve better effectivene...

applications on the web today. So many search engines have been created that it is difficult for users to know where they are, how to use them, and what topics they best address. Metasearch engines reduce the user burden by dispatching queries to multiple search engines in parallel. The SAVVYSEARCH metasearch engine is designed to efficiently query other search engines by carefully selecting th...

This paper focuses on the study of short term load forecasting (STELF) using interval Type-2 Fuzzy Logic (IT2FL) and feed-forward Neural Network with back-propagation (NN-BP) tuning algorithm to improve their approximation capability, flexibility and adaptiveness. IT2FL for STELF is presented which provides additional degrees of freedom for handling more uncertainties for improving prediction a...

We consider the optimal load-shedding problem in electric power systems where a number of transmission lines are to be taken out of service. The nonlinear power flow equations and the binary decision variables lead to a mixed-integer nonlinear program. We show that the load-shedding problem has separable structure that can be exploited by using the alternating direction method of multipliers. W...

Short term electrical load forecasting is critical in ensuring reliability and operational efficiency for electrical systems. With an influx of monitoring data and the growing technical complexity of the grid, there is a great interest and need for accurate forecasting in electricity planning. Our project uses a curated electric load dataset from Kaggle and evaluates the performance of several ...

Accurate electric load forecasting has become the most important issue in energy management; however, electric load demonstrates a seasonal/cyclic tendency from economic activities or the cyclic nature of climate. The applications of the support vector regression (SVR) model to deal with seasonal/cyclic electric load forecasting have not been widely explored. The purpose of this paper is to pre...

In response to the governmental policy of saving energy sources and reducing CO2, and carry out the resident quality of local; this paper proposes a new method for a non-intrusive load-monitoring (NILM) system in smart home to implement the load identification of electric equipments and establish the electric demand management. Non-intrusive load-monitoring techniques were often based on power ...