Supplementing demand management programs with distributed generation options

Date

2012-03-01

Author

Fahrioglu, Murat
Alvarado, F. L.
Lasseter, R. H.
Yong, T.

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

196
views

0
downloads

Ever increasing electrical energy demand is forcing power serving entities around the world to use various demand management programs to help in stressful times of the electric power grid. Demand management programs aim to control electrical energy demand among customers and create load relief for electric utilities. Recently demand management contracts have been designed in which incentives are offered to customers who willingly sign up for load interruption. In recent years much technological advancement has been made in distributed generation, and the cost of using this option can bring about extra flexibility into existing demand management schemes. This paper explores the use of distributed generation technology within the existing demand management ideas. More specifically, it compares economic aspects of using demand management contracts with the use of distributed generation. A key observation of this paper is that there may be cases where it is more beneficial to use distributed generation rather than demand management contracts.

Subject Keywords

Distributed generation, Demand management, Economic analysis

URI

https://hdl.handle.net/11511/67511

Journal

ELECTRIC POWER SYSTEMS RESEARCH

DOI

https://doi.org/10.1016/j.epsr.2011.11.017

Collections

Engineering, Article

Suggestions

OpenMETU
Core

A soft computing approach to projecting locational marginal price Nwulu, Nnamdi I.; Fahrioglu, Murat (2013-05-01) The increased deregulation of electricity markets in most nations of the world in recent years has made it imperative that electricity utilities design accurate and efficient mechanisms for determining locational marginal price (LMP) in power systems. This paper presents a comparison of two soft computing-based schemes: Artificial neural networks and support vector machines for the projection of LMP. Our system has useful power system parameters as inputs and the LMP as output. Experimental results obtained...
Application of a Hybrid Machine Learning model on short term electricty demand prediction Assar, Ahmed Khaled Ahmed Farouk; Fahrioğlu, Murat; Sustainable Environment and Energy Systems (2022-2) Electricity demand forecasting is an important procedure in the electricity market and plays a great role in assuring a sustainable and efficient operation chain. By accurately forecasting the demand, one can see a considerable reduction in production costs as well as saving energy resources. Therefore, optimizing the demand forecasting techniques became an inseparable goal of power economics, leading to the introduction of machine learning to this sector that proved to be superior to other pre-defined alte...
Data-driven modeling using deep neural networks for power systems demand and locational marginal price forecasting Jimu, Honest; Fahrioğlu, Murat; Electrical and Electronics Engineering (2022-9) Forecasting electricity demand and locational marginal prices (LMPs) have become critical components for power system security and management. Electricity Demand Forecasting (EDF) aids the utility in maximizing the use of power-generation plants and scheduling them for both reliability and cost-effectiveness. In this thesis, a novel Deep Neural Network Long Short-Term Memory (DNN-LSTM) forecasting model is suggested to improve accuracy and robustness for predicting hourly day ahead power system load and LMP...
Assessment of renewable energy based micro-grids for small communities Sadati, S.M. Sajed; Taylan, Onur; Sustainable Environment and Energy Systems (2016-7) Deploying renewable energy systems to supply electricity faces many challenges related to cost and variability of the renewable resources. One possible solution to these challenges is to hybridize renewable energy systems with conventional power systems and include energy storage systems. In this study, the feasibility analysis of two cases for electricity generation systems as (i) photovoltaic (PV)-battery-pumped hydro system (PHS) and (ii) PV-wind-battery are presented as a Renewable Energy Micro-Gr...
Optimal mix of a solar, wind, and fuel cell hybrid residential system Chehab, Khalil; Fahrioğlu, Murat; Sustainable Environment and Energy Systems (2018-1) Nowadays, supplying electrical power using renewable energy systems faces problems due to the high cost and unreliability of those systems. With the variability of renewable energy sources, a possible way to provide electricity is by combining different renewable sources in one hybridized system. This study is about optimizing and testing the feasibility of different hybridized systems including solar, wind, and fuel cell systems. The study will include on-grid and off-grid optimal solutions for a case stud...

Citation Formats

M. Fahrioglu, F. L. Alvarado, R. H. Lasseter, and T. Yong, “Supplementing demand management programs with distributed generation options,” ELECTRIC POWER SYSTEMS RESEARCH, pp. 195–200, 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67511.