Demand Side Management and its Possibilities in Jordan

Abstract

The increase in energy consumption and energy bills in Jordan have been escalating rapidly, which requires a special concern as a large percent of the energy is imported. The need for the reducing peak demand of the distribution network is essential to decrease the overall electricity generation cost. This study was aimed at presenting a model for a home that manages its energy consumption, and the maximum savings possible if the load shifting to off-peak times was applied. It also introduced a tariff that is more concerned in time of use rather than consumption only. The power consumption profile is collected for a sample house. The profile for a week was registered and graphed. The pricing suggested was calculated per day. Moreover, some samples applied worldwide were discussed to find a suitable model. It was found that a saving rate of 16% is achievable if the time of use charge is applied. Additionally, a peak load reduction of 3.5 kWH average per day (in the peak hours) is possible.

A Practical Load Disaggregation Approach for Monitoring Industrial Users Demand with Limited Data Availability

“…The technical data and daily working hours for stonecutting machines are shown in Table 5 [51]. According to Shams Abad industrial zone visits, each manufacturer's area is around 2.5 hectares, and the total area for the stonecutting industry was calculated using Equation (7) to be 1661 ha. The total number of machines in the zone was calculated using Equations ( 8) and (9).…”

“…In the domestic sector, while there are different patterns and appliances in different countries [6], generally, some loads such as washing machines, vacuum cleaners, irons, and pool pumps are considered flexible for time-shifting with minimal impact on user comfort. In contrast, some other loads such as fridges, TV, and computers should be considered inflexible for time-shifting to maintain customer comfort [7]. To provide appropriate DSM programmes for the domestic sector, smart sensor data and diaries of appliances are needed.…”

Analyzing the Impacts of a Deep-Learning Based Day-Ahead Residential Demand Response Model on The Jordanian Power Sector in Winter Season

“…Hence, a DR system that targets the residential sector can be a great asset and opportunity for the GO to optimize the daily demand curve and achieve more optimal grid operation, especially at peak periods by reducing peak demand. Tawalbeh et al investigated the use of Time of Use (TOU) pricing in Jordan's residential sector and showed that a peak demand energy of 3.5kWh could be achieved [14]. Jarad and Ashhab showed that a cost saving of 20% and energy consumption reduction of 15% could be achieved through better energy efficiency measures for residential consumers in Jordan [15].…”