Comparative performance of multiple energy storage systems in unified voltage and frequency regulation of power system including electric vehicles

Abstract

Modern power systems are very complicated and have more obligation to uphold the supply of power be reliable, stable, and of decent quality at both the transmission and distribution phases. Preserving grid balance is a significant concern if there is an unforeseen generation deficit or grid disturbance, or intermittent renewable energy sources, such as bio‐diesel, electric vehicles (EVs), and solar power are incorporated into the energy mix. To compensate for this imbalance and enhance the power system's reliability and stability, the energy storage systems (ESS) can be regarded as an appropriate measure. Thus, ESS contributes to greenhouse gas (GHG) emission reductions by successfully integrating more renewable energy sources into the grid. This article presents multiple ESSs, such as pumped hydroelectric storage (PHS), accurate flywheel energy storage (AFES), battery energy storage (BES), capacitive energy storage (CE), and superconducting magnetic energy storage (SMEs) and their comparative performance analysis in unified voltage and frequency control of power system. The proposed interconnected power system includes thermal, solar‐thermal, bio‐diesel‐engine generator, and EVs. In both control systems, a maiden attempt was made to utilize Harris' Hawks optimization‐based fuzzy‐fractional‐order‐tilt‐integral‐derivative (FFOTID) controller. The repercussion of PHS proclaims a substantial amelioration in system performance than other ESSs. Likewise, the system exhibits better dynamics with the coalition of PHS and power system stabilizer (PSS) of AVR compared to their separate intervention. Lastly, sensitivity analysis of proposed controller is analyzed by alteration of load perturbation and nonlinearity of thermal plants, which ensures optimal controller parameters accomplished at nominal conditions are resilient enough.

A Novel Adaptive Neuro-Fuzzy Based Cascaded PIDF-PIDF Controller for Automatic Generation Control Analysis of Multi-Area Multi-Source Hydrothermal System

“…As a result, eleven MFs are considered for both outputs and inputs. All MFs have a value between -1 and 1, [45][46][47][48]. Mamdani, obtain the value for each membership function output.…”

“…Neuron Structure comprises the following elements: xp stands for Inputs, wkp stands for Weights, phi (φ) stands for activation function, and out stands for output. The net input of the activation function is diminished using the threshold [43][44][45][46][47][48][49][50]. Adaptive Neuro-fuzzy inference is used to modify the membership function parameters of fuzzy inference systems of the Mamdani type (ANFIS).…”

“…Table2 displays the mean value of the assessment findings of Unimodal functions of various techniques compared to SOA, as presented in [46]. In terms of optimization, it is evident from the mean values of evaluation results for unimodal functions that SOA is better to any other approach.…”

Chaotic butterfly optimization algorithm based cascaded PI‐TID controller for frequency control in three area hybrid microgrid system

“…LFC for the conventional system has been researched substantially and some of the recent good works are available in References 7–13. FPIDN‐FOPIDN controller, optimized for LFC in an interconnected system comprising of the thermal and thermal hydro gas system 7 .…”

“…Frequency excursions due to the presence of RE in conventional power system is less detrimental as compared to microgrid because the former has comparatively higher inertia. Further, frequency/voltage regulation of multi‐area power systems have been researched recently considering realistic a dish Stirling solar thermal plant, 9 virtual inertia, 10 electric vehicle, 11 several energy storage units, 12 redox flow battery 13 . The performance of the control strategies considered in these works has been satisfactory.…”