The impact of probability of electricity price spike and outside temperature to define total expected cost for air conditioning
Energy, ISSN: 0360-5442, Vol: 195, Page: 116994
2020
- 5Citations
- 15Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The purpose of this paper is to address the problems experienced by customers in the utilisation of electrical energy for air conditioners (ACs). According to the proposed schema in this paper, the customer will be able to evaluate the impacts of a probable electricity price spike and the outside temperature (Tout) to calculate the total expected electricity cost for an AC (TEC). The aim of this paper is to show how consumers can estimate the TEC for any temperature. In this research, a model considering two types of price spikes (PS) is developed, namely: short-duration and long-duration spikes. To evaluate and examine this model, spike durations of half hour, one hour, and one and half hour were simulated to determine TEC. This proposed schema also examines how the control system applies a pre-cooling method if there is a substantial risk of PS. The results present possible savings on the electrical energy consumption when the consumer applies this method to anticipate spike events. This model is tested considering the demand and market price curves of electricity in South Sulawesi, which were published by the Indonesian State Electricity Company (called PLN=Perusahaan Listrik Negara) and the value of Tout in the Makassar area.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0360544220301018; http://dx.doi.org/10.1016/j.energy.2020.116994; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85078092466&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0360544220301018; https://dx.doi.org/10.1016/j.energy.2020.116994
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know