Bat Algorithm Implementation to Optimally Design the Stabilizer Power System on the Suppa Generator

An optimised operation of a thermal power plant is required to optimise fuel consumption cost. It is still high and becomes a problem of economic dispatch in the operation of the plant. Load scheduling and generator capacity are needed to get optimal plant operation, especially energy usage. This paper presented a thermal power plant operation analysis to obtain optimum operational energy costs using the Bat Algorithm (BA). The actual data of 6 thermal power plants to serve the peak loads in 2018 is used for the calculation. The problem solution is simulated and calculated using maximum (95%) capacity and the BA method. The Simulation is done by using MATLAB software. The generator unit and generator load characteristics are collected to obtain objective functions and constraint functions. BA completes this function to get the lowest energy. The BA method will be compared with the calculation of real-time energy generation without BA to analyse its accuracy. The total operational cost of the actual power plant without BA is $ 1,988,410. BA simulation gave the total energy cost is $1,653,374. So, the generated energy savings is 16.85%, or 335,036 MW reduction.

Section: Economic Load Dispatch (Eld) Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Operational Cost Reduction of Gas-Thermal Power Plant Based on Bat Algorithm

Sofwan

Febriansyah

Sugeng

2021

“…The pheromone levels in the ants' paths will increase, while the pheromone levels in the trails where ants don't pass will experience evaporation [9]. The shortest path will often be traversed by ants so that the pheromone levels in that pathway increase and attract other ants to pass the path [21].…”

Section: Power System Stabilizermentioning

confidence: 99%

Optimal Design PSS-Pid Control on Single Machine Infinite Bus Using Ant Colony Optimization

Kadir¹,

Djalal²

2021

Self Cite

Optimization of the controller in a generator can improve system performance. The right parameter optimization is needed to get the optimal performance from the controller. The application of the artificial intelligence method as a parameter optimization method is proposed in this study. By using the smart method based on Ant Colony, the optimal PSS-PID parameters are obtained. With optimal tuning, the system gets optimal Single Machine Infinite Bus (SMIB) system frequency and rotor angle response, indicated by the minimum overshot system response. The SMIB system's stability will be tested. A case study of adding and reducing loads is used, with the proposed control method PSS-PID being optimized using Ant Colony. Based on the analysis using the proposed PSS-PID control, we get the minimum overshoot for the frequency response and rotor angle of the SMIB system. When the load changes at 20 seconds, using the PSS-PID control scheme, the minimum overshoot is -4.316e-06 to 7.598e-05 pu with a settling time of 22.01s. For the rotor angle overshoot response, using the PSS-PID control scheme, the minimum overshoot is -0.01113 to -0.009669 pu with a settling time of 22.36s.

“…The performance of the BA algorithm is very good in carrying out several optimisations, especially in the optimisation of the electric power system. The application of the BA method to the electric power system shows optimal results, such as [9] optimisation of the economical cost of generating, [10,11,12,13], optimal optimisation of Power System Stabilizer parameters to improve power system stability, and [14] optimisation of optimal power flow to reduce losses in transmission. This research proposes an approach based on the Bat Algorithm as a more optimal SMES and CES optimisation method.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of energy storage for load frequency control in micro hydro power plant using Bat Algorithm

Djalal¹,

Kadir²

2022

Self Cite

The rotational speed of a generator affects the frequency and voltage produced, where this change will affect the load side. For that we need a control equipment that can optimize the performance of micro-hydro. Therefore, we need a technology to optimize the performance of micro hydro by applying Load Frequency Control (LFC). LFC designed by implementing Superconducting Magnetic Energy Storage (SMES) and Capacitive Energy Storage (CES), this application will provide power compensation to reduce or even eliminate frequency oscillations caused by changes in consumer electrical power loads. To get optimal microhydro performance, it is necessary to set the right parameters for SMES and CES. SMES and CES parameter tuning in this study is proposed using the Bat Algorithm. The objective function used by this algorithm is to optimize the Integral Time Absolute Error (ITAE). For performance analysis, the system is tested with load changes, then the governor, turbine, and system frequency responses are analyzed. To test the reliability of the system, this study used several scenarios of a combination of control, SMES, CES, with conventional control based on Proportional, Integral, Derivative (PID). The right control parameters will improve system performance more optimally. Optimal system performance can be seen from the response of the governor, turbine, and minimum overshoot of the frequency, as well as the fast settling time for the system to switch to steady state conditions.