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Details

  • Name

    Shabnam Pesteh
  • Cluster

    Power and Energy
  • Role

    Research Assistant
  • Since

    05th July 2017
001
Publications

2019

A new interior point solver with generalized correntropy for multiple gross error suppression in state estimation

Authors
Pesteh, S; Moayyed, H; Miranda, V; Pereira, J; Freitas, V; Simoes Costa, AS; London Jr, JBA;

Publication
Electric Power Systems Research

Abstract
This paper provides an answer to the problem of State Estimation (SE) with multiple simultaneous gross errors, based on Generalized Error Correntropy instead of Least Squares and on an interior point method algorithm instead of the conventional Gauss–Newton algorithm. The paper describes the mathematical model behind the new SE cost function and the construction of a suitable solver and presents illustrative numerical cases. The performance of SE with the data set contaminated with up to five simultaneous gross errors is assessed with confusion matrices, identifying false and missed detections. The superiority of the new method over the classical Largest Normalized Residual Test is confirmed at a 99% confidence level in a battery of tests. Its ability to address cases where gross errors fall on critical measurements, critical sets or leverage points is also confirmed at the same level of confidence. © 2019 Elsevier B.V.

2019

Impact of different central path neighborhoods on gross error identification in State Estimation with generalized correntropy interior point method

Authors
Moayyed, H; Pesteh, S; Miranda, V; Pereira, J;

Publication
2019 International Conference on Smart Energy Systems and Technologies (SEST)

Abstract

2016

The IMBPC HVAC system: A complete MBPC solution for existing HVAC systems

Authors
Ruano, AE; Pesteh, S; Silva, S; Duarte, H; Mestre, G; Ferreira, PM; Khosravani, HR; Horta, R;

Publication
ENERGY AND BUILDINGS

Abstract
This paper introduces the Intelligent MBPC (IMBPC) HVAC system, a complete solution to enable Model Based Predictive Control (MBPC) of existing HVAC installations in a building. The IMPBC HVAC minimizes the economic cost needed to maintain controlled rooms in thermal comfort during the periods of occupation. The hardware and software components of the IMBPC system are described, with a focus on the MBPC algorithm employed. The installation of IMBPC HVAC solution in a University building is described, and the results obtained in terms of economical savings and thermal comfort obtained are compared with standard, temperature regulated control.

2015

An Intelligent Weather Station

Authors
Mestre, G; Ruano, A; Duarte, H; Silva, S; Khosravani, H; Pesteh, S; Ferreira, PM; Horta, R;

Publication
SENSORS

Abstract
Accurate measurements of global solar radiation, atmospheric temperature and relative humidity, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight, self-powered and portable sensor was developed, using a nearest-neighbors (NEN) algorithm and artificial neural network (ANN) models as the time-series predictor mechanisms. The hardware and software design of the implemented prototype are described, as well as the forecasting performance related to the three atmospheric variables, using both approaches, over a prediction horizon of 48-steps-ahead.

2015

Improving a neural networks based HVAC predictive control approach

Authors
Ruano, AE; Silva, S; Pesteh, S; Ferreira, PM; Duarte, H; Mestre, G; Khosravani, H; Horta, R;

Publication
2015 IEEE 9th International Symposium on Intelligent Signal Processing (WISP)

Abstract
This paper improves an existing Model Based Predictive Control Approach (MBPC), applied for Heating Ventilation and Air Conditioning (HVAC) control in buildings. The existing approach uses the Predictive Mean Vote (PMV) to assess thermal comfort. It has been found that PMV estimation and forecasts deteriorate when the room is occupied. In order to solve this problem, we propose to incorporate measurements of activity inside the room in the predictive models of the inside air temperature. Another improvement to the existing approach is to use an economic cost function, reflecting the money needed for the HVAC control, instead of a cost function related with the consumption of energy.