Title

Moving Query Monitoring In Spatial Network Environments

Abstract

Kaveh Madani and Jay Lund have developed a new model that can be used for large-scale hydropower planning studies in California with reasonable computational effort and time. The Energy-Based Hydropower Optimization Model (EBHOM) is a non-linear optimization model that finds the reservoir operations and hydropower generation which maximizes hydropower revenues. EBHOM provides planning and management insights about hydropower systems with minimal computational effort. The run time of the model is low and its application to different systems is not costly. The effects of on-peak and off-peak pricing on the hydropower operations are considerable. EBHOM uses a novel method to incorporate the effects of variable pricing on the operations. This is important for hydropower systems that are operated with fluctuating hourly prices. Recently, EBHOM has been improved to also consider the climate change effects on hydropower demand and pricing. The improved EBHOM (EBHOM 2.0) benefits from an Artificial Neural Networks (ANN) module that estimates the changes in hourly hydropower pricing in response to temperature changes.

Publication Date

4-1-2012

Publication Title

Mobile Networks and Applications

Volume

17

Issue

4

Number of Pages

234-254

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/s11036-011-0298-2

Socpus ID

84861833588 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84861833588

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