4.7 Article

Optimal thermal and power planning considering economic and environmental issues in peak load management

Journal

ENERGY
Volume 239, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.121955

Keywords

Optimal thermal planning; Peak load management; Energy hub system; Environmental performance

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This paper discusses the challenges of energy in today's world and the integrated exploitation or hybrid strategies proposed by energy hub. The linear model of the energy hub was designed and operated using the epsilon-constraint method and fuzzy weighted method, considering randomness and uncertainty.
The challenges associated with energy of the todays' world including climate change, growing demand, and interdependence of gas, heat, and electricity have encouraged energy system planners to consider the integrated exploitation or hybrid strategies, which is so-called as the energy hub. According to different definitions presented for the energy hub, various models have been proposed so far for it. In general, the equipment of an energy hub can be divided into three categories: 1) direct connections, 2) converters, and 3) energy storage system. In this paper, a linear model of the energy hub including heating, cooling, and electrical equipment for energy conversion, production, or storage was considered. The proposed model consists of two parts of design and operation, formulated for an annual period in four seasons. The epsilon-constraint method and fuzzy weighted method were used to solve the proposed model, and the two parts of design and operation were introduced as the main problem and sub-problem, respectively. In addition to deterministic model, problem-solving space was considered as scenario-based random taking into account uncertainty in amount of load, energy price, and also production of renewable wind resources. Scenarios were simulated for production of wind resources using historical information and other scenarios were simulated using the Monte Carlo simulation method. Given solution of the problem annually, for reducing volume of calculations, number of scenarios was decreased using the K-Means method. Mathematical model of the proposed model was of the mixed-integer linear type and included binary variables of design and continuous and binary variables of operation. Capacity selection for installation was based on appropriate candidates for each of the equipment, in order to prevent installation of unrealistic capacities in design sector. (C) 2021 Elsevier Ltd. All rights reserved.

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