Integrated demand response based on household and photovoltaic load and oscillations effects. (16th November 2021)

• Record Type: Journal Article
• Authors: Cao, Wenxuan; Pan, Xiao; Sobhani, Behrouz
• Is Part Of: International journal of hydrogen energy. Volume 46:Number 79(2021)
• Page Start: 39523
• Page End: 39535
• Publication Date: 2021-11-16
• Subjects: Optimization -- Grasshopper search algorithm -- Household energy management -- Load management; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2021.08.212
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: Due to the attractiveness of household gas-electric tools, in this paper, an optimization technique is suggested based on the integrated demand response (IDR) and degree of tolerance for household energy management. The proposed method is mostly used to express the dynamic change in the forms of energy and undetermined variables in the systems, resulting from household and photovoltaic (PV) load. Thermostatically controlled demands include gas-electricity and air conditioning, and cut-able loads include gas-electric stove and washing machine. The interval optimization is modeled for optimizing the operation and greenhouse gas emission costs in multi-purpose systems. The undetermined variables are formulated as interval statistics and the limitations are simplified by degree of tolerance. In order to solve it, the interval optimization technique is converted into certainty optimization with the interval order relationship and the delayed probability degree. Then, the developed grasshopper search algorithm is based on the chaos theory to solve the interval optimization model in order to respond to uncertainty and demands of the users, such that degree of tolerance of cost that is acceptable by users is optimized. Contrary to other optimization algorithms, the grasshopper search algorithm can be combined with other methods. In this paper, the chaos theory is adopted to find a better solution. Since the information is placed in the search space without order, using this technique considerably leads to good convergence speed, precise final solution finding, not being trapped in local minima, lower SD, and robustness. Both methods of IDR and degree of tolerance for the household gas-electric equipment manage to reduce energy consumption by about 25% compared to traditional methods. Highlights: Gas-electric equipment is integrated in household energy management. A novel IDR method in HMES is proposed, while uncontrollable loads are also executed. To deal with HMES uncertainty with electric equipment, interval optimization is used. The users' degree of tolerance in HMES with gas-electric equipment is modeled. New model of the GSA based on chaos theory is introduced.