MVO Algorithm Based LFC Design of a Six-Area Hybrid Diverse Power System Integrating IPFC and RFB

Arya³

et al. 2020

Int J Energy Res

Self Cite

The increasing integration of regional power grids, rising penetration of multigeneration sources, and day-ahead power agreements have raised the operational challenges on deregulated modern electric energy systems. Among various challenges, frequency regulation becomes more prominent in the restructured power system (RPS) due to increased uncertainties and intricacies among other operational challenges. A minor deviation in system frequency affects the safety, quality, stability, and operation of the interconnected power system (IPS). An appropriate control mechanism and energy storage device are essential to regulate the system's dynamic responses during continuously varying loading conditions. This study proposed a novel Salp swarm algorithm (SSA) optimized fuzzy-based proportional-integral-derivative filter (FPIDF) controller with redox flow battery (RFB) to regulate the frequency of a realistic multi-area multi-source (thermal-hydro-gas) interconnected power system. All probable contract transaction scenarios are simulated that can be possible in a deregulated power industry. Various nonlinearities such as time delay (TD), governor dead band (GBD), and generation rate constraint (GRC) are incorporated to resemble the realistic operational conditions of the IPS. The effectiveness of the suggested controller has been validated by comparing the system performances with a recently published sine-cosine algorithm (SCA) based proportional-integral (PI) controller and SSA-PID controller. The investigation has been further extended by incorporating RFB in the proposed system. The study reveals that the suggested controller provided superior system control under various system uncertainties in all contact scenarios of the competitive electricity market. Additionally, the system performances have been significantly enhanced due to quick response and precise control offered by RFB.

Section: Cost Functionmentioning

confidence: 99%

J_{ITAE} ((), normalX, normalU) = \int_{0}^{{normalt}_{sim}} ((), (||, {ΔF}_{1}) + (||, {ΔF}_{2}) + (||, {ΔP}_{Tie}^{Actual})) t_{sim} dt

where t sim is total simulation time, X is the independent (state) variable, X = [K 1 , K 2 , K P , K I, K D, N C ] and U is the vector of dependent (control) variables, U = [u 1 , u 2 ].…”

Section: Proposed Control Approachmentioning

confidence: 99%

Frequency stabilization in deregulated energy system using coordinated operation of fuzzy controller and redox flow battery

Sharma¹,

Arya³

et al. 2020

Int J Energy Res

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“…Integral of time-weighted absolute error (ITAE) is mostly used as an objective function in AGC studies due to its better performance [45]. Therefore, the performance index used in this proposed work is the ITAE index for its rapid settling feature and can be expressed by ( 21) as follows:…”

Section: Objective Functionmentioning

confidence: 99%

Grasshopper optimisation based robust power/frequency regulator for shipboard micro‐grid

Prakash

Sharma²,

IET Renewable Power Generation

2020

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Due to the rapid increase in electrical energy requirements in marine power systems (MPSs), and to reduce the consumption of fossil fuel, there is an emergent need to utilise renewable energy sources (RESs) in MPSs, which has been an attractive field of research. This research aims to present a novel load frequency control (LFC) scheme for a shipboard microgrid (SMG) system. Therefore, a MPS with photovoltaic, wind turbine, hybrid energy storage system (ESS), and diesel generator (DG) have been simulated to relate an exact mobile islanded SMG. The system is designed using the transfer function models with the above said generating units and storage systems. Grasshopper optimisation algorithm (GOA) tuned fuzzy-based proportional-integral-derivative with filter control technique has been proposed to investigate the performance of the LFC scheme for the proposed SMG system. GOA and particle swarm optimisation optimised controllers have been designed and performance evaluation has been carried out on the conventional, adaptive neuro-fuzzy inference system, and fuzzy cascaded with a conventional controller. The responses obtained from the simulations for different cases are analysed to justify the novelty and superiority of the proposed technique for frequency and power regulation.

“…Previously, the majority of the works on frequency regulation are carried out including single and two areas [15], multi‐area traditional [16, 17], and deregulated power systems [10, 18] as reviewed effectively in [19, 20]. Several advanced control methodologies have been implemented in the literature for frequency regulation of the traditional and deregulated power systems using conventional controllers such as proportional–integral (PI) [2, 21], and proportional–integral–derivative (PID) [16]. However, the conventional controllers do not deliver the desired performance under the complexity augmented due to the non‐linearity of the system, turbine pressure, and load variation etc.…”

Section: Introductionmentioning

confidence: 99%

Frequency excursion mitigation strategy using a novel COA optimised fuzzy controller in wind integrated power systems

Sharma¹,

IET Renewable Power Generation

Arya³

et al. 2020

Self Cite

The uncertain demeanour from wind generators and loads adversely affect the grid operational stability. Various control approaches have been explored to remedy the system uncertainties while maintaining generation and load demand balance. This study proposes a fuzzy‐based proportional–fractional integral–derivative with filter controller to sustain frequency stability in wind integrated power systems having different configurations. The controller parameters have been tuned using a recently developed coyote optimisation algorithm (COA). The proposed control approach is executed and validated on three distinct configurations of two‐area power systems. All test models are integrated with a doubly fed induction generator (DFIG) type wind turbine units (WTUs). Different case scenarios have been considered to analyse the efficacy of the proposed control strategy in the presence of WTU. Furthermore, the impact of inertial support delivered by the DFIG‐WTU and higher penetration of wind energy in the power system has been studied. The analysis reveals that the control scheme in coordination with WTU support reduces the stress on a wind turbine during the inertial control scheme and maintains the grid frequency stability under unexpected load disturbances. Stability and robustness analysis are also conducted to verify the validity of the introduced control approach.