Optimization of the Midterm Electricity Generation Mix Considering the Effects of Water, Land and Carbon Footprints

Mohsen Bozorg; Hamed Mazandarani Zadeh; Dragan Savic

doi:10.29007/vpvk

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Optimization of the Midterm Electricity Generation Mix Considering the Effects of Water, Land and Carbon Footprints

8 pages•Published: September 20, 2018

Mohsen Bozorg, Hamed Mazandarani Zadeh and Dragan Savic

Abstract

Electric energy plays a key role in the development of modern societies. Each of the electric power generation technologies (e.g., hydroelectric, wind, solar, thermal, etc.) has some advantages and disadvantages with respect to the fundamental resource indicators, including water footprint, land footprint, carbon footprint, as well as electricity generation costs. Due to the shortage and frequent crisis associated with the above resources, optimal selection of the mix of electricity generation technologies is very important and the share of each technology in the capacity expansion of the generation system must be carefully defined. Iran is in an arid and semi-arid region, with less than one third of the average world precipitation. Moreover, the available water resources are restricted due to the water crises in the Middle-East region. In this paper, we first estimated the peak power consumption of Iran in 2024, based on the time-series data from 2004 to 2014. Then, we formulated an optimization problem to find the share of each electric power generation technology to cover the required extra generation capacity for supplying the power consumption in the target year 2024, considering the effect of the four aforementioned performance indicators. The optimization problem is solved using Genetic Algorithm. Numerical results show that in the target year, 20 GW of electricity should be added to the generation capacity. The results also show that, solar thermal and solar photovoltaic are the best electric generation technologies regarding the available resources.

Keyphrases: Electricity generation-mix, Genetic Algorithms, Sustainability, water footprint

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 321--328

Links:	https://easychair.org/publications/paper/cMdh
	https://doi.org/10.29007/vpvk

BibTeX entry

@inproceedings{HIC2018:Optimization_of_Midterm_Electricity,
  author    = {Mohsen Bozorg and Hamed Mazandarani Zadeh and Dragan Savic},
  title     = {Optimization of the Midterm Electricity Generation Mix Considering the Effects of Water, Land and Carbon Footprints},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  pages     = {321--328},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {https://easychair.org/publications/paper/cMdh},
  doi       = {10.29007/vpvk}}

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