Optimizing Technology Selection for Power Smart Grid Systems: a Case Study of Iran Power Distribution Industry (IPDI)

Abstract

The power smart grid (PSG) as a well-established research area is recently dealing with a wider range of topics such as power systems, energy generation and telecommunication. Selecting proper technologies for PSG systems is a complicated and multi-criteria decision making process. The present paper aims to identify the most important technologies for PSG at IPDI using a multi-criteria decision making (MCDM) technique, simple additive weighting (SAW). To this purpose, competent and knowledgeable decision makers in the field of PSG technologies were requested to evaluate the PSG technologies and its affiliated criteria and comment on them. They were also asked to rate each technology based on criteria set within the framework of SAW. The six-step algorithm of SAW has successfully identified moment billing, wireless technology and load forecasting as the most important technologies for PSG. This study suggests that both potential PSG technologies and criteria should be taken into account to optimize selecting important technologies.

A Dual Model for Selecting Technology and Technology Transfer Method Using a Combination of the Best-Worst Method (BWM) and Goal Programing

“…Also, Kharat et al [46] addressed the criteria of purchase and consumption costs, environmental compatibility, efficiency, technological reliability, expertise requirements, and public acceptance. Moreover, Montazeri and NajartabarBisheh [47] described the criteria for technology localization, the benefits of technology, and the risks of replacing the existing technology with a new one.…”

Using Regression Analysis to Predict the Demand Function of Electricity: A Case Study

“…To understand Iran's energy plan, much efforts have been made by scholars (Esmaeili et al, 2015;Montazeri and Najjartabar-Bisheh, 2017). For example, in 1977, a research institute affiliated with Stanford University attempted to investigate and document the "long-term energy plan" in Iran.…”

“…Regression based models have been giving promising performance to find possible solutions for these kind of problem (Fanoodi et al, 2019). Different type of regression analysis has been used successfully to predict demand in different context such as software development (Urbaczek et al, 2020), supply chain management (Najjartabar-Bisheh et al, 2018), financial management (Saremi et al, 2020), analyzing of productivity (Esmaeili et al, 2019) and healthcare systems (Jahantigh et al, 2017) and many other areas has been used. In this study, the electricity demand of the other variables is described in the following section and the electricity demand in relation to the relevant parameters was calculated.…”

Performance Analysis and Techno-Economic Optimization of Green Energy Systems for Remote Areas in the Maghreb

“…Africa to which the Maghreb belongs, has intently suffered from a lower urbanization rate and break power supply systems, continuing to roll out 4G networks, while the globe communication industry attests today a stiff competition and stagnating revenue growth, to define 5G network requirements. Motivated by relevant works [24][25][26][27][28][29][30], in the context of lowering the energy cost and enhancing the network operation, we have chosen three (3) remote areas from the Maghreb: (Ras El Oued, Cherb Errih, and Ain Amara), owning closest location details and nearest average climate and daylight, situated at an altitude of 890 m (https://earth.google.com/) (https://www. ncdc.noaa.gov/ and https://weatherspark.com/), to be studied as a unique case study within a remote area-prototype (RAP), as given in Fig.…”