Generation Control Research Articles

Advanced Sliding Mode Design for Optimal Automatic Generation Control in Multi-Area Multi-Source Power System Considering HVDC Link

The multi-area multi-source power system (MAMSPS), which uses a variety of power sources including gas, hydro, thermal, and renewable energy, has recently been implemented to balance the growing demand for electricity and the overall capacity for power generation. In this paper, an integral sliding mode control with a single-phase technique (ISMCSP) is applied to two areas, with each area including gas–wind–thermal power systems with HVDC system. Firstly, a two-area gas–wind–thermal power system with HVDC (TAGWTPSH) is the first model in this scheme to consider the parameter uncertainties of a MAMSPS. Secondly, sliding mode design law with a single-phase technique is introduced to alleviate chattering and oscillation problems. Then, power system stability is ensured by the Lyapunov control theory based on the new LMIs technique. Thirdly, the ISMCSP’s effectiveness in a MAMSPS is also assessed under random load patterns and parameter variations regarding settling time and over-/undershoot. The ISMCSP was created to alter the fundamental sliding mode control, and therefore the suggested approach performs better than recently published approaches. This is demonstrated by the frequency overshoot deviation value in frequency deviations: 0.7 × 10−3 to 2.8 × 10−3 for the TAGWTPSH with the suggested ISMCSP. In the last case, for random changes in load from −0.4 to +0.5 p. u, the proposed ISMCSP method still stabilizes the frequency of the areas meeting the standard requirements for AGC.

Multi-objective design of fractional frequency-load control for hydro-thermal system considering nonlinear models and uncertainty

One of the crucial quantities in the power system problem is frequency, which should never exceed its nominal value. In normal conditions of load changes, the frequency is adjusted by automatic generation control. Still, in the face of special conditions, such as logging of the downstream network from the main network or a significant amount of generated power leaving the circuit, the power imbalance between generation and consumption causes a rapid frequency drop. In this case, the automatic generation control cannot stop the frequency drop, so the frequency tends toward instability. In this paper, to automatically produce a water-thermal system in two zones of discrete and continuous modes, the design of a fractional controller is discussed and investigated in different functional conditions and uncertainties. The proposed NSGA-II multi-objective method is used in this article to optimize each area’s load frequency control parameters for various goals. The ideal response for the entire network will be obtained by modifying these responses using a multi-factor method. This paper defines a multi-zone frequency load control based on time objective functions and eigenvalues. Based on the speed changes for the proposed algorithm and the novel approachfunction method employed in the control design. The simulation performed and analyzed in different working conditions with different comparative criteria has been discussed and investigated. Compared to more contemporary techniques, the simulation results show that the system’s performance is guaranteed. The main successes of the suggested method in comparison to earlier methods have been the reduction of overshoot, undershoot, and settling time.

Attack-Dependent Adaptive Event-Triggered Security Fuzzy Control for Nonlinear Networked Cascade Control Systems Under Deception Attacks

This article investigates the issue of H∞ security output feedback control for a nonlinear networked cascade control system with deception attacks. First, to further reduce the amount of communication data, reasonably schedule network resources, and alleviate the impact of multi-channel deception attacks, an attack-dependent adaptive event-triggered mechanism is introduced into the primary network channel, and its adaptive triggered threshold can be adjusted according to the random attack probability. Secondly, the output dynamic quantization of the secondary network channel is considered. Then, a novel security cascade output feedback controller design framework based on the Takagi–Sugeno (T-S) fuzzy networked cascade control system under deception attacks is established. In addition, by introducing the Lyapunov–Krasovskii stability theory, the design conditions of the controller are given. Finally, the effectiveness and superiority of the proposed design strategies are verified by two simulation examples of power plant boiler–turbine system and power plant boiler power generation control system.

Back to the nest: the practices employed for succession of heirs in family businesses in Brazil

PurposeThe present study aims to identify the practices employed to bring heirs into family businesses as successors.Design/methodology/approachWe conducted an exploratory, qualitative investigation using a case study approach. Semi-structured face-to-face interviews were conducted with external consultants and with incumbent leaders, next-generation heirs working in the firm (and likely to become successors) and employees from three family firms from different industries and under ownership and control of different generations of their respective families (first, second and third and fourth generations). In addition to surveying their general perceptions of the succession processes in their firms, each informant was asked to rate the degree of importance of 12 succession practices identified in the literature and the extent to which they exist in their respective firms.FindingsOur results showed that heirs typically enter the family business after a development process outside of the family business, which we have termed as coming back to the nest. This process was enacted through practices that we allocated to the following categories: continued development of heirs, developing relationships in the succession process, separation of roles and attitude of the successor heirs. Overall, 8 of the 12 practices derived from the theoretical framework were endorsed as important by representatives of the family businesses and 9 were endorsed by the consultants, 7 of which coincided in both groups. However, only 5 of the practices were identified as present in the firms’ succession processes by the representatives of the family businesses, while the consultants did not identify any of the 12 practices as present.Originality/valueWe present additional important practices, the adoption of which would be beneficial for family business succession, such as adapting external learning to the family business, acquiring leadership skills and experience and developing emotional intelligence. Our study advances the prior literature since we do not merely discuss succession planning but analyze in an applied manner how succession actually takes place in family businesses.

A new integrated modelling and control of ternary pumped storage hydro power generation for small signal stability studies

Pumped storage hydro power generation (PSHPG), a reliable renewable energy source with an energy storage feature, can impart efficient damping torque to power system oscillations to improve small signal stability with appropriate modelling and additional compensation through the governor. But ternary PSHPG (T-PSHPG) has the unique feature of hydraulic short circuit (HSC) mode, where both pumping and generating modes operate simultaneously. This study presents a novel fourth-order modified Heffron Phillips (MHP) model of T-PSHPG in coordination with a multi-band Power system stabilizer (MB-PSS) employing 2-way penstock, where primary penstock circulates water from the upper reservoir to the lower reservoir through the turbine and secondary penstock divides primary penstock, thereby creating short-circuit path through the pump. Also, this model includes additional reactive power droop control to maintain the voltage profile. A new state space matrix has been developed for coordinating T-PSHPG in HSC mode with MB-PSS. The control parameters of the proposed coordinated model are set by a new multi-objective differential evolution-improved particle swam optimization (DE-IPSO) algorithm. With variable load, random solar and wind source penetrations, it has been found that the proposed model can provide adequate damping actions. The sensitivity of the proposed model has been observed by varying critical model parameters by ±50 %. For all conditions, the settling time of speed variation is within 2.672 s to 5.951 s and the minimum damping ratio lies within 0.105 to 0.455. The minimum damping ratio is 0.32 and the settling time is found to be 3.1 s for system response subject to sudden solar power variation, which has been observed by shifting system eigenvalues toward the left half of the complex plane. Time and frequency domain parameters with sensitivity analysis predict system oscillations being damped effectively with consistency for the proposed modelling and control strategy. The results are verified in real-time with OPAL-RT real-time digital simulator. It has been justified by the present study that appropriate modelling of T-PSHPG along with coordinated control action provided by MB-PSS can handle critical power system oscillations efficiently and effective damping torque can be imparted in HSC mode.

Decomposition prediction fractional-order active disturbance rejection control deep Q network for generation control of integrated energy systems

The number of distributed renewable energy sources of integrated energy systems (IESs) are increasing. The volatility of renewable energy exacerbates active power imbalances and increase frequency deviations in power systems. This work proposes a decomposition prediction fractional-order active disturbance rejection control deep Q network (DPFOADRCDQN) to control each generator of IESs more accurately and to reduce systemic frequency fluctuation. According to the fluctuation size of frequency deviation, the sub-signal obtained after the prediction of the modal decomposition of frequency deviation is classified into big fluctuating signals and small fluctuating signals; fractional-order active disturbance rejection control (FOADRC) controls small fluctuating signals; deep Q network (DQN) controls big fluctuating signals. Frequency deviation signals in complex power systems with a large percentage of renewable energy have higher smoothness after modal decomposition, FOADRC can efficiently follow the small fluctuating signals, and DQN can learn the rich data features in the big fluctuating signals and give precise control commands. The DPFOADRCDQN, proportional-integral-derivative, Q-learning, fuzzy control, and the previous state-of-the-art reinforcement learning are simulated in IESs where the renewable energy generators output is 0 %, 20 %, 40 %, 65 %, and 80 % of all generators output, the results show the average frequency deviation, total generation cost, and carbon emission cost are at least 42.7 %, 0.92 %, and 0.93 % smaller than the comparison algorithm, respectively.

Innovation for recycling of organic matter through composter with automatic and sustainable temperature recording accessed via Bluetooth/mobile app.

Compost reactors, commonly used in experiments, industrial assays, and home residue treatment systems, have the potential to facilitate composting. Challenges persist in the realm of small-scale composting, encompassing facets such as temperature monitoring, homogenization of the compost mass, management of moisture with the control of leachate generation, and integration with a renewable energy source. This study assesses a pioneering composter prototype endowed with essential features to ensure a pragmatic and secure composting process. This includes the facilitation of remote access to temperature data via Bluetooth and a mobile application. Across successive trials, the scrutinized composter prototype consistently yielded reproducible outcomes, exhibiting a coefficient of variation below 25% for the majority of appraised parameters. In comparison to a conventional reactor, the decomposing residue mixture within the examined prototype manifested elevated temperatures (p < 0.05). Moreover, the tested prototype demonstrated C/N ratio lower than 20/1 within 45days, a higher final nitrogen concentration, and enhanced germination of seeds that served as phytotoxicity bioindicators. Notably, the prototype needed 46.6% less space, offering improved leachate control, three times faster turning time, temperature monitoring, and reduced fly attraction.

The design of a model predictive control strategy and performance analysis for pumped storage units and super capacitors in power systems

IntroductionSuper capacitors were regarded as one of the most effective frequency regulation technologies in power systems. The major issue of applying super capacitors for frequency regulation is the limited energy capacity and the high construction costs. The pumped storage units have been developed and applied in power systems for decades, whereas it was rarely operated to regulate the system frequency due to the operation limitations. The pumped storage units could be operated as a hydro generator under the generation mode and provide effective frequency regulation service with the conventional automatic generation control (AGC) system while its output power was constant under the pumping mode.MethodIn this paper, the pumped storage unit was controlled to participate in frequency regulation under the generation mode with super capacitors. Considering the AGC system could not consider the state of charging (SOC) of super capacitors for frequency regulation, an optimization model was proposed to determine the operation points for super capacitors and pumped storage units under a model predictive control (MPC) strategy to regulate the system frequency for power systems.Results and DiscussionBased on the various operation scenarios, the effectiveness and costs of pumped storage units and super capacitors to provide frequency regulation services were discussed. It was indicated that pumped storage units and super capacitors were effective technologies for power systems.

Energy management strategy and operation strategy of hybrid energy storage system to improve AGC performance of thermal power units

With the continuous increase of the renewable energy power generation penetration, the intermittency and fluctuation of renewable energy power generation make the traditional thermal power units (TPU) which play the main role of regulation need to undertake more frequent and more severe regulation tasks. In order to improve the automatic generation control (AGC) command response capability of TPU, an operation strategy of hybrid energy storage system (HESS) is proposed in this paper. While assisting TPU to complete the regulation tasks, it gives full play to the advantages of power-type and energy-type energy storage. Moreover, an energy management strategy of energy storage array (ESA) is proposed to improve the overall operation efficiency of ESA while making the state of charge (SOC) of all energy storage subunits consistent. Finally, the effectiveness of the proposed strategy is verified by simulation experiments. The results show that after using HESS to assist TPU operation, the comprehensive regulation performance index of TPU increased from 4.0198 to 7.8112, which significantly improved the operational flexibility of TPU. Meanwhile, the strategy proposed in this paper makes different types of energy storage systems in HESS operate in a relatively healthy SOC range, and the SOC of the flywheel energy storage system (FESS) reaches the limitation value decrease from 6 times to once, ensuring the overall charge and discharge capacity of HESS.

A viscoelastic harvester-absorber for energy generation and vibration control

Abstract A vibration energy harvester harnesses the oscillatory movement and&amp;#xD;converts it into electrical energy. On the other hand, a (dynamic) vibration absorber&amp;#xD;dissipates the mechanical energy of a host structure (primary system). The proposal for&amp;#xD;a harvester-absorber device (HAD), comprinsing a piezoelectric element (conventional&amp;#xD;harvester) bonded with a viscoelastic layer and a steel constrained layer, is based on the&amp;#xD;dual purpose of generating energy and at the same time reducing the vibratory response&amp;#xD;of the primary system. Introducing a viscoelastic dissipative layer in a conventional&amp;#xD;harvester, also offers the advantage of simultaneously reducing wear on the piezoelectric&amp;#xD;element, thereby extending its lifespan and preventing fatigue-related breakage. The&amp;#xD;paper presents a model of a harvester-absorber built from a bimorph piezoelectric&amp;#xD;beam, a layer of viscoelastic material (E-A-R C1002-01PSA) and a beam of steel, which&amp;#xD;acts as a constrained layer. A lumped parameter model is proposed for the theoretical&amp;#xD;description of the HAD which is successfully used to experimentally determine its&amp;#xD;parameters. After that, and using the equivalent stiffness concept, the HAD was&amp;#xD;coupled to a free-free beam with two masses at its ends to study its perfomance over a&amp;#xD;real host structure. The inertance of the composite system and voltage/force frequency&amp;#xD;response function of the HAD were obtained and compared with experimental results.&amp;#xD;The accuracy of the results justifies and validate the model which has the advantage&amp;#xD;of simplicity and can contribute to reducing wear and increasing the lifespan of brittle&amp;#xD;piezoelectric structures.

The Generation, Measurement, Prediction, and Prevention of Residual Stress in Nickel-Based Superalloys: A Review

As a crucial high-performance material, nickel-based superalloys inevitably generate residual stresses during processing, manufacturing, and usage. The mechanical properties of nickel-based superalloys are significantly reduced by residual stress, which becomes one of the important factors restricting material reliability. The systematic analysis of residual stresses in nickel-based superalloys throughout the entire manufacturing and usage processes is insufficient. The residual stress generation factors, measurement methods, prediction models, and control methods in nickel-based superalloys in recent years are summarized in this paper. The current challenge and future development trends in the research process of nickel-based superalloy residual stress are also presented. A theoretical reference for further research on residual stresses in nickel-based superalloys can be provided in this review.

Hybrid modeling with data enhanced driven learning algorithm for smart generation control in multi-area integrated energy systems with high proportion renewable energy

Multi-area integrated energy systems (MA-IES) with a high proportion of renewable energy have become a trend in social development. The access to a large number of distributed energy sources makes the safe, stable, and economic operation of MA-IES suffer serious challenges. To reduce the frequency deviation and area control error (ACE) of MA-IES and to improve the economy of operation, this study proposed a hybrid modeling with data enhanced driven learning algorithm, which combines model-driven and data-driven algorithms, named combined proportion-integral-derivative and deep reinforcement learning (CPIDDRL). Firstly, the frequency deviation signals are collected and judged, and the smaller frequency deviation signals, which are sent to the model-driven part, are regulated by proportion-integral-derivative (PID) controllers. Then, the ACE and large frequency deviation signals are collected and transmitted to the data-driven part, and the Transformer deep learning network is applied to predict the multi-feature timeseries, which are applied to strategy selection for state-action-reward-state-action reinforcement learning. Finally, the model-driven part and data-driven part work together to generate adjustment commands every 4 s. The control effects of CPIDDRL, PID, Q-learning, and sliding model control algorithms are compared in two and four areas integrated energy systems. The results show that, compared to the comparison algorithms, the CPIDDRL reduces the mean values of frequency deviation and ACEs by at least 46.78% and 6.83%, respectively, and the total generation cost by at least 8.20%. CPIDDRL has practical significance in improving system stability, enhancing renewable energy integration capabilities, and promoting the development of smart grids.

A Bi‐level stacked LSTM‐DNN‐based decoder network for AGC dispatch under regulation market framework in presence of VPP and EV aggregators

AbstractThe consideration of mileage settlement in the frequency regulation market has encouraged fast‐acting units, such as converter‐interfaced generators (CIG) and electric vehicle stations, to actively participate in load‐generation balancing through automatic generation control (AGC). Conventional frequency regulation faces challenges in coping with the growing variability of CIGs and also lacks effective incentives for rapid‐responding units. In this context, a bi‐level AGC dispatch approach based on a stacked long short‐term memory (LSTM)‐deep neural network (DNN)‐based decoder framework is proposed for a power system comprising diverse CIGs forming a virtual power plant and electric vehicle aggregators. The proposed decoder network is comprised of stacked LSTM and DNN, wherein the cascaded LSTM layers are introduced to accurately capture temporal information from time series input. The inclusion of a dropout mechanism further enhances the model’s generalisability in unforeseen environments. The proposed dispatch framework uses mileage‐based compensation criteria to optimally allocate instructions among various participating units with differing regulation characteristics. The performance of the proposed method is analysed by considering packet loss, delay, unexpected generation failure, and denial of service attacks. The evaluation of the proposed approach reveals its superior performance compared to proportionality, particle swarm optimisation, decision tree, and DNN methods.

A Simplified Dynamic Model of DFIG-based Wind Generation for Frequency Support Control Studies

In recent years, wind generation has been fast growing and become one of the major generation resources in power systems. Since the wind generation does not inherently equip with frequency support functions, the power system frequency response degrades as the wind penetration increases. Therefore, frequency support control of wind generation has gained increasing focus. However, the dynamic models of wind generation systems, which are required by the control design and analysis, are commonly very complicated and difficult to obtain, especially for the doubly-fed induction generator based wind turbine (DFIG-WT). In this paper, the authors propose a simplified dynamic model for the DFIG-WT. The proposed analytical model is derived from the detailed model by selectively neglecting very fast dynamics while keeping the critical ones. It is suitable for frequency control studies. The model accuracy is first validated against the detailed DFIG-WT model in Simulink. Then, the wind frequency control function is studied based on the proposed model.

Fine-tuning ocean energy storages for reservoir-integrated wave energy converters with dynamic activation of mechanical energy storage features

The proportion of renewable energy in the power supply has experienced substantial growth; however, its intermittent nature and inherent uncertainty present notable challenges in its integration. This study aims to explore the significance of energy flexibility in energy management by focusing on a hybrid renewable wave-wind zero-energy system implemented in a coastal building. Specifically, the study investigates various sources of flexibility within the system and introduces a novel energy storage mechanism utilising the in-built reservoir of the wave energy converter. The research provides new insights into the flexibility of control strategies from the generation and storage sides. The cost-responsive controls involved on/off-peak periods and monthly variations. Several attempts have been made to develop cost-responsive controls that depend upon the electricity tariffs; these include energy shift and peak shaving. The lower discharging limits and trigger lines were compared in the simulation environment to improve the cost-saving, energy-matching, and peak-shaving performances. In this study, the first group scheduled discharging; however, only limited improvements (0.5%) were achieved. Consequently, the second group shifted to varying the minimum fraction state of the reservoir under a lower discharging limit, which reduced operational cost by 4.5%. Using different discharging lines by considering the current month and the period, the third group achieved the expected peak shaving and correspondingly reduced the operational cost to 90.3 %. The final group showed that an additional battery could improve the peak-shaving and cost-saving performance but not the net present value, owing to high investment costs. Furthermore, annual savings increased for different battery capacities from 4.5 % to 6.8 % by conducting the energy shift. Peak shaving control with additional battery reduced maximum demand and substantially reduced costs from 6.4 % to 10.8 %. The study recommends focusing on peak shaving with extra batteries for further cost savings during the on-peak period. This research brings novelty by integrating flexibility control for both generation- and storage-sides in ocean renewable energy systems. It proposes using a wave energy converter as a mechanical energy storage reservoir, reducing costs and ensuring adequate capacity. The study emphasises dynamic storage control, adjusting in real time based on conditions and energy demands.

Prior EEG marks focused and mind-wandering mental states across trials.

Whether spontaneous or induced by a tedious task, the transition from a focused mental state to mind wandering is a complex one, possibly involving adjacent mental states and extending over minutes or even hours. This complexity cannot be captured by relying solely on subjective reports of mind wandering. To characterize the transition in a mind-wandering-inducing tone counting task, in addition we collected subjective reports of thought generation along with task performance as a measure of cognitive control and EEG measures, namely auditory probe evoked potentials (AEP) and ongoing 8-12Hz alpha-band amplitude. We analyzed the cross-correlations between timeseries of these observations to reveal their contributions over time to the occurrence of task-focused and mind-wandering states. Thought generation and cognitive control showed overall a yoked dynamics, in which thought production increased when cognitive control decreased. Prior to mind wandering however, they became decoupled after transient increases in cognitive control-related alpha amplitude. The decoupling allows transitory mental states beyond the unidimensional focused/wandering continuum. Time lags of these effects were on the order of several minutes, with 4-10min for that of alpha amplitude. We discuss the implications for mind wandering and related mental states, and for mind-wandering prediction applications.

Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration

Concerns over fossil fuel emissions and their hazardous effects have led to a shift away from conventional power plants and focus more on the expansion of renewable energy sources. This shift has resulted in reduced inertia and resulted in poor frequency control within electrical power systems. Hybrid Energy Storage Systems (HESS) have been proposed as an effective solution to enhance frequency stability and address the reduced inertia issue. This research evaluates three distinct control models for HESS, Incorporating Supercapacitor Energy Storage (SCES) and Battery Energy Storage Systems (BESS). To optimize the control parameters with the best objectives, all possible sets of objectives with four different optimization algorithms are studied. The three control models considered for the HESS incorporate Virtual Synchronous Generator (VSG) or Virtual Inertia (VI) control with independent or simultaneous optimization of control parameters. The performances of the three control models are evaluated based on three test scenarios incorporating uncertainties, reduced inertia, and uniform and random load disturbances. The findings indicate that the Independently Optimized Virtual Synchronous Generator HESS (IO VSG-HESS) achieves the best settling time post-contingency but offers the least improvement in frequency nadir with an average of 0.31 %. Conversely, the Simultaneously Optimized Virtual Inertia And Virtual Synchronous Generator Controlled HESS (SO VI-VSG-HESS) excel in mitigating small frequency fluctuations with an average improvement in frequency standard deviation of 87.65 %. The Simultaneously Optimized Virtual Synchronous Generator Controlled HESS (SO VSG-HESS) provides the best frequency nadir, with an average improvement of 0.63 %, but with a slight increase in settling time.

Area-wide survey and monitoring of insecticide resistance in the brown planthopper, Nilaparvata lugens (Stål), from 2020 to 2023 in China

The brown planthopper (BPH), Nilaparvata lugens (Stål), is a notorious pest affecting Asian rice crops. The evolution of insecticide resistance in BPH has emerged as a significant challenge in effectively managing this pest. This study revealed the resistance status of BPH to nine insecticides in ten provinces and Shanghai City in China from 2020 to 2023. Monitoring results showed that the resistance of BPH to triflumezopyrim, nitenpyram, and dinotefuran increased rapidly. The average resistance ratio of BPH to triflumezopyrim increased from 2.5 to 7.1 fold, nitenpyram from 18.3 to 37.7 fold, and dinotefuran from 119.5 to 268.1 fold. All populations remained extremely high resistance to imidacloprid, thiamethoxam, and buprofezin. Most field populations of BPH maintained moderate resistance to chlorpyrifos and sulfoxaflor, and high resistance to pymetrozine by rice stem dipping method. However, considering the reproduction-inhibiting character of pymetrozine, susceptible to low resistance levels to pymetrozine were monitored by Insecticide Resistance Action Committee (IRAC) NO.005 method. This result indicated that pymetrozine might lose efficacy in the control of application generation, but it could significantly inhibit the reproduction of field populations of BPH. Additionally, we compared the expression levels of 11 nicotinic acetylcholine receptor (nAChR) genes, the targets of nAChR competitive modulators, in four field populations (FY23, YH23, LJ23, LP23) and susceptible strain. The expression level of nAChR α4 was significantly reduced in all field populations, while α1, α2, α6, and α7 were significantly reduced in some field populations. Our findings provide valuable information for resistance management strategies in N. lugens and offer new insights into the resistance mechanisms of nAChR competitive modulators.

Thermal management and power generation characteristics in a bifurcating channel by using a piezo-embedded inclined elastic fin assembly during turbulent forced convection of ternary nanofluid

Numerous engineering systems use piezoelectric energy harvesters (PE-EHs), which have several benefits including low cost, simplicity, better power density, and ease of installation. They can be used in different applications for energy harvesting and different external sources such as wind and vortex induced vibrations due to fluid–structure interaction can be utilized. This study uses a unique elastic fin PE/EH assembly for power generation, thermal management, and flow control in a bifurcating channel. Performance of the system is improved by using ternary nanofluid in the channel cooling system. Galerkin weighted residual FEM with ALE is used as the solution method. The convective heat transfer performance and power generation by the EH device are investigated in relation to the varying following parameters: Reynolds number (Re between 10000 and 30000), PE-EH inclination (γ between 0 and 60), fin horizontal location (xf between −H and H), and nanoparticle loading in the base fluid (ϕ between 0 and 0.03). The vortex size and distribution near the junction are significantly influenced by the fin inclination and horizontal location of the fin assembly within the bifurcating channel. When varying other parameters of interest, using nanofluid at the highest loading results in significant deflection of the fin assembly and power generation within the PE-EH. Enhancement factors (EFs) for power generation becomes 15.6 and 39.8 when cases of lowest and highest Re are compared with pure fluid and nanofluid while they are 2.93 and 3.38 for thermal performance improvements. Fin inclination of γ=30 is found as the optimum inclination for achieving the highest power from the assembly. Higher inclination of elastic fin/PE-EH assembly results in cooling performance deterioration while average Nu reduces by a factor of 2.94 by varying inclination from γ=30 to γ=60 with nanofluid. For power generation, effects of using nanofluid with varying inclination is significant and EF becomes 252 from γ=0 to γ=30. There are opposing tendencies for the device’s power generation and cooling performance enhancement when the fin’s horizontal placement is changed. EF for average Nu is 7.25 for varying fin location. As the loading of nanoparticle inside the base fluid increases, the average Nu and generated power exhibit non-linear rising characteristics. Polynomial type correlations are provided for the average Nu and power from the device by varying elastic fin assembly inclination and nanoparticle solid volume fraction. Potential of using hybrid nanofluid in PE-EH embedded thermo-fluid system is shown. The design, development, and optimization of self-sufficient power production systems that may be used to various thermo-fluid systems, such as electronic cooling and thermal control in a range of heat transfer devices, may benefit from the findings.

A new mMSA-FOFPID controller for AGC of multi-area power system with multi-type generations

The exceptional growth in the penetration of renewable sources as well as complex and variable operating conditions of load demand in power system may jeopardize its operation without an appropriate automatic generation control (AGC) methodology. Hence, an intelligent resilient fractional order fuzzy PID (FOFPID) controlled AGC system is required. The parameters of controller are tuned utilizing a new modified moth swarm algorithm (mMSA) inspired by the movement of moth towards moon light. At first, the effectiveness of the controller is verified on a nonlinear 5-area thermal power system. The simulation outcomes bring out that suggested controllers provide the best performance over the lately published strategies. In the subsequent step, the methodology is extended to a 5-area system having 10-units of power generations, namely thermal, hydro, wind, diesel, gas turbine with2-units in each area. It is observed that mMSA based FOFPID is more effective related to other approaches. In order to establish the robustness of the controller, the sensitivity examination is executed. Then, experiments are conducted on OPAL-RT based real-time simulation to confirm the feasibility of the method. Finally, mMSA based FOFPID controller is observed superior than the recently published approaches for standard 2-area thermal and IEEE 10 generator 39 bus systems.