|
Blackout Crisis Policy Research: Agent base Stochastic modeling of electricity consumption in Tehran
|
| Saeed Vedadi Kalantar *, Amir Ali Saifoddin |
| Tehran University , saeed.vedadi@ut.ac.ir |
|
|
Abstract: (224 Views) |
| Increasing the peak of electricity network in summer leads to power outages in industries and residential sectors, the most obvious example of which was power outages in the summer of 2018. Due to the high cost of power plant capacity development ($ 500 per kilowatt), demand-side management is the most important strategy to reduce the grid peak. In this study, the effect of behavioral parameters in reducing the peak of the power grid with the help of bottom-up modeling has been identified. Behavioral simulation in this study has been performed with the help of time use data of the Statistics Center of Iran. In this plan, 4228 urban households have been surveyed and the quality of people's behavior in each time step of 15 minutes during the day and night has been determined with 2 deterministic and stochastic approaches. In the stochastic approach, the Markov chain method is used. In this study, scenarios based on household comfort temperature have been developed. The results of the present study indicate that with the flexibility of cooling electricity consumption due to the presence of people in the house and the desired comfort temperature, it is possible to reduce the peak of the electricity network between 70 and 134 MW (equivalent to $ 65 million to build new power plant capacity). It is equal to 10% of the cooling peak of Tehran electricity network. With the spread of this 10% reduction to the whole country, about 6,000 MW (equivalent to $ 3 billion to create a new power plant capacity) the country's peak network has been reduced and the blackout crisis can be easily controlled. |
|
| Keywords: Behavioral modeling, Bottom-up modeling, Stochastic approach, Power grid peak, Power outage crisis |
|
|
Full-Text [PDF 2244 kb]
(89 Downloads)
|
Type of Study: Research |
Subject:
Energy Planning Models
Received: 2023/03/28 | Accepted: 2023/05/8 | Published: 2023/03/1
|
|
|
|
|
|
|
| Send email to the article author |
|
|
|
| Add your comments about this article |
|
|
|
