To improve the diversity and performance of the mayflyalgorithm (MA), this letter adopts the mutation strategies in the process of MA. The opposition-based learning (OBL) and Cauchy mutation strategies are used to mu...
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To improve the diversity and performance of the mayflyalgorithm (MA), this letter adopts the mutation strategies in the process of MA. The opposition-based learning (OBL) and Cauchy mutation strategies are used to mutate the global optimal solution, and the artificial mutation operator is used in the offspring population. The hybrid mutation strategies are used in a cascaded structure. The performance of the proposed algorithms is demonstrated in simulations comparatively.
This study thoroughly investigates the enhancement of power system stability through the coordinated design of Static VAR Compensator (SVC) and Multi-Band Power System Stabilizer type 3C (MB-PSS3C). An improvedmayfly...
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This study thoroughly investigates the enhancement of power system stability through the coordinated design of Static VAR Compensator (SVC) and Multi-Band Power System Stabilizer type 3C (MB-PSS3C). An improved mayfly algorithm (IMA) is employed to optimize the placement and tuning of SVC and MB-PSS3C within the Southern Sulawesi (Sulbagsel) integrated Wind Power Plant (WPP) electricity system. mayfly intelligence is inspired by the mating and flight behaviors of adult mayflies. In its standard form, this algorithm cannot be applied to high-dimensional, nonlinear, and complex space problems. This study proposes an Exponent Decreasing Inertia Weight (EDIW) strategy to enhance the performance of the standard mayflyalgorithm (MA). The IMA demonstrates superior performance compared to other methods, achieving a minimum fitness function value of 80.0582 and converging rapidly by 8th iteration. For SVC, the optimization analysis involved reviewing the voltage profile at each bus and analyzing Optimal Power Flow (OPF). For MB-PSS3C, the optimization focused on evaluating system stability through damping analysis, time-domain simulations, and eigenvalue visualization. The application of IMA-based SVC improved reactive power management in transmission systems, resulting in enhanced voltage profiles, OPF, and reduced transmission losses. Specifically, transmission losses decreased by 3.12% in the normal system case study and by 2.88% in the N-1 contingency case study. Meanwhile, the IMA-based MB-PSS3C enhanced system stability by increasing system damping, reducing generator oscillation overshoot, and improving system eigenvalues. The implementation of MB-PSS3C using IMA across 14 generators achieved the highest damping ratio of 0.7375, compared to 0.7274 for MB-PSS3C with MA.
An improved mayfly algorithm is proposed for the energy saving optimization of parallel chilled water pumps in central air conditioning system, with the minimum energy consumption of parallel pump units as the optimiz...
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An improved mayfly algorithm is proposed for the energy saving optimization of parallel chilled water pumps in central air conditioning system, with the minimum energy consumption of parallel pump units as the optimization objective and the speed ratio of each pump as the optimization variable for the solution. For the problem of uneven random initialization of mayflies, the variable definition method of Circle chaotic mapping is used to make the initial position of the population uniformly distributed in the solution space, and the mayfly fitness value and the optimal fitness value are incorporated into the calculation of the weight coefficient, which better balances the global exploration and local exploitation of the algorithm. For the problem that the algorithm is easy to fall into the local optimum at the later stage, a multi-subpopulation cooperative strategy is proposed to improve the global search ability of the algorithm. Finally, the performance of the improved mayfly algorithm is tested with two parallel pumping system cases, and the stability and time complexity of the algorithm are verified. The experiments show that the algorithm can get a better operation strategy in solving the parallel water pump energy saving optimization problem, and can achieve energy saving effect of 0.72% 8.68% compared with other optimization algorithms, and the convergence speed and stability of the algorithm have been significantly improved, which can be better applied to practical needs.
This study proposes a hybrid dynamic economic environmental dispatch model combining thermal power units, wind turbines, photovoltaic and energy storage device to achieve the balance between operating costs and pollut...
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This study proposes a hybrid dynamic economic environmental dispatch model combining thermal power units, wind turbines, photovoltaic and energy storage device to achieve the balance between operating costs and pollutant emissions under the premise of stabilizing the output of renewable energy. Most studies have addressed economic and environmental issues to optimize dispatch as more and more renewable energy is connected to the grid, while ignoring the stability of renewable energy output. Aiming to solve the problem of instability of renewable energy output, a wind-photovoltaic stable output strategy is proposed, and an energy storage device is used to control the dispatched power of renewable energy. The fitness function is improved and an improvedmayfly (IMA) algorithm using chaotic initialization, inertia weight and mutation strategy is proposed to find the optimal solution, and the performance of the algorithm is verified on two systems with different configurations. In addition, constraints such as the power balance, output of each power generation device and energy storage device are considered. The results show that the operating costs of the IMA algorithm is 4.12%, 13.21% and 15.14% lower than those of the MA, MFO and PSO algorithms, and the proposed model using the IMA algorithm can effectively achieve the balance between economy and environment and obtain stable renewable energy output. This study provides a useful reference for the stable operation of power grid under a variety of renewable energy access conditions.
Accurate and rapid microseismic source location is the foundation for tunnel rockburst warning. Here, we present a novel location strategy that employs an improved mayfly algorithm (IMA) to enhance the convergence spe...
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Accurate and rapid microseismic source location is the foundation for tunnel rockburst warning. Here, we present a novel location strategy that employs an improved mayfly algorithm (IMA) to enhance the convergence speed and accuracy of the virtual field optimization method (VFOM) for tunnel microseismic events. By optimizing the initial position of the mayfly population and the moving velocity of mayfly personals, we develop an IMA with superior convergence speed in searching for source locations. The proposed method utilizes paired microseismic receivers in the tunnel monitoring array to create hyperbolic surfaces. Then, the IMA is employed to rapidly and accurately determine the intersection point of all hyperbolic surfaces, defining it as the microseismic source location. We compare the IMA-VFOM with different error levels in seismic wave velocity or arrival time against other traditional location approaches based on travel time differences. The results confirm that the IMA-VFOM's convergence speed is, on average, more than 4 times that of the MAVFOM algorithm. Compared to conventional methods, the IMA-VFOM method demonstrates higher location accuracy and stability. The average location error of the proposed method is 4.0043 m when applied to real rockburst microseismic events in tunnels.
Aiming at the problem that robot absolute positioning accuracy affects robot machining, a joint compensation method of robot kinematics error based on MRIPN-MA is proposed. Firstly, a robot coordinate measurement syst...
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Aiming at the problem that robot absolute positioning accuracy affects robot machining, a joint compensation method of robot kinematics error based on MRIPN-MA is proposed. Firstly, a robot coordinate measurement system based on wire sensor is built. Secondly, using DH kinematics model, error model and neural network, the theoretical mathematical model of robot error compensation is established. Then, the kinematics parameters and joint variables of the robot are jointly compensated by improved mayfly algorithm (IMA) and multi-representation integrated predictive neural network (MRIPN). Finally, after joint optimization by MRIPN-IMA, the accuracy of the robot is improved by 83.5% . In order to verify the above theory, grinding experiments are used. After the optimization of the robot, 23.975%of the over-cutting phenomenon is reduced. This method can improve the absolute positioning accuracy of the robot and avoid grinding dislocation.
In this article, the improved mayfly algorithm (IMA) is used as an upgraded form of the mayflyalgorithm (MA), featuring simulated binary crossover and polynomial mutation operators replacing the arithmetic crossover ...
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In this article, the improved mayfly algorithm (IMA) is used as an upgraded form of the mayflyalgorithm (MA), featuring simulated binary crossover and polynomial mutation operators replacing the arithmetic crossover and standard distribution mutation operators of the MA. With MA, IMA's achievements and significance are acknowledged. The algorithms achieve a final best solution for the investigated objective functions of the optimal power flow problem in a deregulated electrical power market under different load conditions. The overall load of the power system varies between half of the base load (-50%) and twice the base load (+100%). The investigated objective functions are associated with the financial worth of generators, dissipation of active power in transmission lines, variation of voltage magnitudes at the system bus, and voltage stability index at the load bus of the power system networks. The result achieved by GA, PSO, MA and IMA are attained using the IEEE-30 bus test system in a deregulated power system. Investigations are conducted on the best solutions for each objective function;offers of generators and bids of loads;generator sales and load purchases;and system revenues associated with different load scenarios. The simulated outcomes have confirmed that IMA would triumph over GA, PSO and MA.
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