Investigating the Optimal DOD and Battery Technology for Hybrid Energy Generation Models in Cement Industry Using HOMER Pro

Abstract

Cement industry is one of the highest energy consuming industries. The quantity of fuel and energy needed accounts for most of the cost of cement manufacturing. Thermal power plants generate electricity but are harmful and ineffective by nature. As a backup mechanism to account for main grid failures, batteries can be utilized. In this paper the first ever investigation on battery’s depth of discharge (DOD) for four different kinds of battery technologies is carried out in the framework of cement industry. The intended battery technologies are the lead-acid battery (LA), lithium-ion battery (Li-ion), vana-dium redox battery (VR), and nickel–iron battery (Ni-Fe). Four hybrid energy generation models (HEGMs) for five cement plants of Pakistan using the HOMER pro software are proposed. Cement plants includes Askari Cement Plant, Wah (ACPW); Bestway Cement Plant, Kalar Kahar (BCPKK); Bestway Cement Plant, Farooqia (BCPF); Bestway Cement Plant, Hattar (BCPH); and DG Cement Plant, Chakwal (DGCPC). HEGM-1 comprises of a diesel generator (DGen), a photovoltaic system (PV), a converter, and a battery system. HEGM-2 comprises of a PV system, a converter, and a battery system. HEGM-3 is the grid-connected version of HEGM-1 and HEGM-4 is the grid-connected version of HEGM-2. A base-model consisting of grid only is used as a reference. A multi-criteria decision analysis (MCDA) is performed by formulating a cumulative objective function (COF) which includes net present cost (NPC), levelized cost of energy (LCOE), and greenhouse gas (GHG) emissions. The principal objective is the maximization of COF while simultaneously minimizing the objectives (NPC, LCOE and GHG emissions), based on optimal battery technology and DOD. The results reveal that VR is the most suitable battery technology with 10% DOD. It is achieved for DGCPC with HEGM-3 with 61.49% of NPC, 78.62% of LCOE and 84.00% of GHG emissions reduction as com-pared to the base model.

Optimal Design of Hybrid Microgrid in Isolated Communities of Ecuador

“…In this context, hybrid microgrids appear as an alternative to stimulate the incorporation of renewable resources and reduce fossil fuel consumption in isolated communities, with better environmental performances [2]. Several optimization algorithms have been proposed for the design of hybrid microgrids, including linear programming and mixed-integer linear programming algorithms [3] - [5], particle swarm optimization (PSO) based algorithm [6]- [9], iterative Gauss-Seidel algorithm [10], hybrid optimization of multiple energy resources (HOMER) [11] - [21], stochastic optimization algorithm [22], [23], and evolutionary algorithm [24]- [30]. These algorithms use different objective functions to utilize renewable resources as much as possible.…”

“…Finally, the discussion and conclusion are drawn in Sections IV and V, respectively. [11]- [21], [35] [30] The method for the optimal design of hybrid microgrid is summarized in Fig. 1.…”