Analytic Hierarchy Process Algorithm Applied to Battery Energy Storage System Selection for Grid Applications

Abstract

The Brazilian Power Sector is preparing the introduction of battery energy storage in its distribution lines for energy quality control. The technical and financial viability of this new technology depends on several factors: battery technologies, geographical locations, environmental restrictions and the local regulation. One of the objectives of the present project was to create a methodology for helping technicians to choose the best battery technology for each particular application. The Analytic Hierarchy Process -AHP algorithm was selected to take into account all the above-mentioned factors. This methodology was applied to a case study considering four different commercially available battery energy storage systems (BESS) and the methodology was able to recommend the best choice by taking into account all the criteria and subcriteria considered. The second objective of the present project is to evaluate a real hybrid BESS operation composed of two different battery technologies. Up to the moment when this paper was submitted the BESS has not been installed yet. The installation place has already been selected, a feeder-line with 1,360 kW peak power, and monitored for energy quality. The BESS has been sized, a 250 kW/1 MWh flow battery together with a 250 kW/500 kWh lithium-ion battery and the purchase process has been initiated. Both battery technologies will work in separate and joint operations for power quality in on-grid and island cases. HIGHLIGHTS  The Brazilian electricity regulatory agency calls for energy storage projects  Electric utilities evaluate battery energy storage for power quality control  The Analytic Hierarchy Process (AHP) algorithm for battery technology: a strategic choice • Environmental, Technological, Regulatory and Financial AHP criteria Oening A.P.; et al.

Value Evaluation Model of Multi-Temporal Energy Storage for Flexibility Provision in Microgrids

“…The analytic hierarchy process (AHP) enables the systematic, model-based, and datadriven transformation of complex problems, thereby enhancing the scientific nature of decision-making and reducing the difficulty of decision-making. It has been widely applied across multiple research domains, especially in subjective weighting [15,16]. AHP can simulate human cognitive characteristics during the process of systematically weighting the assessment indicators of the utility of energy storage, primarily through the following steps.…”