Fractional Order AGC for Distributed Energy Resources Using Robust Optimization

Pan, Indranil; Das, Saptarshi

doi:10.1109/tsg.2015.2459766

Cited by 201 publications

(167 citation statements)

References 40 publications

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“…In this regard, fuel cell can be consolidated with these energy resources accompanied by the energy storage systems such as: battery and flywheel to break through the aforementioned issue. The components of the various energy resources have been linearized and modeled to construct the consolidated hybrid power system . The general schematic of the hybrid power system based on various energy generation‐storage power plants is presented in Figure .…”

Section: Linearization and Modeling Of Interconnected Power System Wimentioning

confidence: 99%

Optimal Fractional Order BELBIC to Ameliorate Small Signal Stability of Interconnected Hybrid Power System

Falehi

2019

Env Prog and Sustain Energy

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The small signal stability of power systems integrated with fallback large‐scale distributed energy resources is of utmost importance during the perturbation conditions. Among the various renewable resources in power systems: photovoltaic, fuel cell, wind turbine, diesel engine, aqua electrolyser, battery, ultra‐capacitor, and flywheel is becoming more favored in last decades. AGC, a main control system of frequency modulation, must correctly alleviate the low frequency oscillations caused by the perturbation and variable output power of renewable resources. In this regard, FOBELBIC is here introduced to enhance the damping capability of AGC. Since both the frequency and tie‐line power oscillations must be concomitantly alleviated, the small signal stability problem has been multi‐objectively formulated. Due to the exploration capability of MOALO, it has been chosen to extract the optimal parameters of FOBELBIC. Furthermore, MOPSO, MOBA, and NSGA‐II have been studied to demonstrate the capability of MOALO. To verify and validate the damping performance of suggested controller, it has been evaluated in three‐area reconstructed power system under the load perturbations as well as wind speed and sun radiation variations, and at the same time compared with BELBIC and PID controllers. Finally, the simulation results have evidently confirmed the damping the performance of MOALO‐based FOBELBIC to enhance the small signal stability of hybrid power system. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13146, 2019

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Section: Linearization and Modeling Of Interconnected Power System Wimentioning

confidence: 99%

Optimal Fractional Order BELBIC to Ameliorate Small Signal Stability of Interconnected Hybrid Power System

Falehi

2019

Env Prog and Sustain Energy

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“…These robust stable solutions are considered as the mid-points of the images showing the iso-performance contours where the midpoint represent the performance with fixed robust stable PID controller gains on the nominal process model parameters as reported in section 4.1. Moving towards a better performance as often done in optimization based controller design approaches using single or multiple control objectives may not necessarily yield a robust stable solution (Pan & Das 2016). Rather here we take a different route and design a robust stable solution first (as the centroid of the stability region in controller parameter space) followed by investigating the resulting performance improvement or degradation for uncertain process parameters using this robust stable solution.…”

Section: 5mentioning

confidence: 99%

Performance analysis of robust stable PID controllers using dominant pole placement for SOPTD process models

Das

Halder

Gupta

2018

Knowledge-Based Systems

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Abstract:This paper derives new formulations for designing dominant pole placement based proportionalintegral-derivative (PID) controllers to handle second order processes with time delays (SOPTD). Previously, similar attempts have been made for pole placement in delay-free systems. The presence of the time delay term manifests itself as a higher order system with variable number of interlaced poles and zeros upon Pade approximation, which makes it difficult to achieve precise pole placement control. We here report the analytical expressions to constrain the closed loop dominant and nondominant poles at the desired locations in the complex s-plane, using a third order Pade approximation for the delay term. However, invariance of the closed loop performance with different time delay approximation has also been verified using increasing order of Pade, representing a closed to reality higher order delay dynamics. The choice of the nature of non-dominant poles e.g. all being complex, real or a combination of them modifies the characteristic equation and influences the achievable stability regions. The effect of different types of non-dominant poles and the corresponding stability regions are obtained for nine test-bench processes indicating different levels of open-loop damping and lag to delay ratio. Next, we investigate which expression yields a wider stability region in the design parameter space by using Monte Carlo simulations while uniformly sampling a chosen design parameter space. The accepted data-points from the stabilizing region in the design parameter space can then be mapped on to the PID controller parameter space, relating these two sets of parameters. The widest stability region is then used to find out the most robust solution which are investigated using an unsupervised data clustering algorithm yielding the optimal centroid location of the arbitrary shaped stability regions. Various time and frequency domain control performance parameters are investigated next, as well as their deviations with uncertain process parameters, using thousands of Monte Carlo simulations, around the robust stable solution for each of the nine test-bench processes. We also report, PID controller tuning rules for the robust stable solutions using the test-bench processes while also providing computational complexity analysis of the algorithm and carry out hypothesis testing for the distribution of sampled data-points for different classes of process dynamics and non-dominant pole types. Keywords:dominant pole placement, PID controller tuning, second order plus time delay (SOPTD), control performance, robust stable controller, stability region, signal/system norms, gain/phase margin 2 Nomenclature: m : Non-dominance parameter for pole placement,

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“…Recently, the fractional order concept in the design process of PID controllers has attracted much attention [31][32][33]. In [31], the FOPID controller is utilized in a hybrid power system to improve frequency oscillation damping. In [32], it is demonstrated that the FOPID controllers have more flexibility, and they are able to simultaneously satisfy multiple conflicting design objectives for a wider dynamic range than the simple PID structure, which traditionally is used in the industry.…”

Section: Fractional Order Pid Controllermentioning

confidence: 99%

“…This is the reason for the endeavours to examine other control methods like intelligent [29] and robust [30] controllers in the LFC structure. Recently, the fractional order concept in the design process of PID controllers has attracted much attention [31][32][33]. In [31], the FOPID controller is utilized in a hybrid power system to improve frequency oscillation damping.…”

Section: Fractional Order Pid Controllermentioning

confidence: 99%

Coordination of Heat Pumps, Electric Vehicles and AGC for Efficient LFC in a Smart Hybrid Power System via SCA-Based Optimized FOPID Controllers

et al. 2018

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Due to the high price of fossil fuels, the increased carbon footprint in conventional generation units and the intermittent functionality of renewable units, alternative sources must contribute to the load frequency control (LFC) of the power system. To tackle the challenge, dealing with controllable loads, the ongoing study aims at efficient LFC in smart hybrid power systems. To achieve this goal, heat pumps (HPs) and electric vehicles (EVs) are selected as the most effective controllable loads to contribute to the LFC issue. In this regard, the EVs can be controlled in a bidirectional manner as known charging and discharging states under a smart structure. In addition, regarding the HPs, the power consumption is controllable. As the main task, this paper proposes a fractional order proportional integral differential (FOPID) controller for coordinated control of power consumption in HPs, the discharging state in EVs and automatic generation control (AGC). The parameters of the FOPID controllers are optimized simultaneously by the sine cosine algorithm (SCA), which is a new method for optimization problems. In the sequel, four scenarios, including step and random load changes, aggregated intermittent generated power from wind turbines, a random load change scenario and a sensitivity analysis scenario, are selected to demonstrate the efficiency of the proposed SCA-based FOPID controllers in a hybrid two-area power system. Keywords: load frequency control; fractional order proportional integral differential controller (FOPID); electric vehicle (EV); heat pump (HP); sine cosine algorithm (SCA); smart hybrid two-area power system

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Fractional Order AGC for Distributed Energy Resources Using Robust Optimization

Cited by 201 publications

References 40 publications

Optimal Fractional Order BELBIC to Ameliorate Small Signal Stability of Interconnected Hybrid Power System

Optimal Fractional Order BELBIC to Ameliorate Small Signal Stability of Interconnected Hybrid Power System

Performance analysis of robust stable PID controllers using dominant pole placement for SOPTD process models

Coordination of Heat Pumps, Electric Vehicles and AGC for Efficient LFC in a Smart Hybrid Power System via SCA-Based Optimized FOPID Controllers

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