Jirawadee Polprasert - Academia.edu (original) (raw)

Papers by Jirawadee Polprasert

81 Abstract— This paper presents an analytical approach to determine the optimal location and siz... more 81 Abstract— This paper presents an analytical approach to determine the optimal location and size of distributed generation (DG) in the electrical distribution system of Naresuan University (NU). Based on available data of the system, the single line diagram is first drawn and line impedances among buses are estimated. The latter values are calculated based on the distance between bus locations and the electrical conductor characteristics. According to the power transformer rates and the maximum total load of the NU system (13.60 MW), the load consumptions of all main loads connected to the NU buses can be assumed. The optimal size and location of DG have been determined to minimize the transmission losses in the system. Placement of a photovoltaic source known as type-I DG has been considered for injecting the real power into the system. The analytical approach is based on the exact loss formula. The effects of optimal size and location of DG are considered and examined in detail ...

2014 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE), 2014

This paper proposes a chaotic based particle swarm optimization with time-varying acceleration co... more This paper proposes a chaotic based particle swarm optimization with time-varying acceleration coefficients (CPSO-TV AC) for solving security constrained optimal power flow (OPF) problem. The proposed CPSO-TVAC is an improved PSO mixing chaotic sequences and crossover operation to enhance the search ability to the global optimum solution. The proposed CPSO-TVAC based optimal power flow is used to minimize the total generation fuel cost satisfying power balance flow equations, real and reactive power generation limits, generator bus voltage limits, tap setting transformer limits, and security voltage and transmission line loading constraints. Test results on the IEEE 30-bus and 118-bus systems indicate that the proposed CPSO-TVAC method renders a lower total generation cost in a faster convergence rate than other heuristic methods, which is favorable for online implementation.

In this paper, robust optimization based AC optimal power flow (ROPF) considering wind and solar ... more In this paper, robust optimization based AC optimal power flow (ROPF) considering wind and solar power uncertainty is proposed. ROPF is used to determine optimal power dispatch and locational marginal prices in a day-ahead market while limiting the risk of dispatch cost variation. ROPF is tested on PJM 5-bus system integrating wind and solar PV generation. Simulation results indicate that ROPF results in a lower expected dispatch cost at the same risk preference level than a stochastic nonlinear programming (SNP) approach. Accordingly, it is potentially useful for day-ahead market operator in policy and decision making.

2021 9th International Electrical Engineering Congress (iEECON)

Rising demand for energy consumption indicates that adequate energy supplies are essential for ec... more Rising demand for energy consumption indicates that adequate energy supplies are essential for economic growth and social development. Nowadays, as fossil fuel is running out and discharging a huge amount of carbon emission, energy transformation to renewables is a must. However, developing and operating clean power plants are a momentous challenge as it is difficult to manage sustainable and long-lasting energy resources. A forecasting model is, therefore, a promising tool to predict the generation, consumption, and reservation of energy.In this paper, a long-term forecasting model for hydropower production using the autoregressive integrated moving average (ARIMA) time series method is proposed. The collected data was obtained from the Son La hydropower plant in Vietnam. The electricity generation in this plant demonstrates an upward trend in the future. Although the power capacity of the hydropower plant is significantly affected by environmental variability, having a forecasting model and a long-term plan will greatly benefit renewable energy production to keep up with economic growth. In addition, the simulation results can be used as a reference for further studies and strategic energy planning.

Energy Procedia

Abstract This paper presents an approach to determine the optimal capacity of battery energy stor... more Abstract This paper presents an approach to determine the optimal capacity of battery energy storage system (BESS) for peak shaving of the electric power load in Naresuan University (NU), Phitsanulok, Thailand. The topology of the system consists of main grid, loads and the proposed BESS. Experimental data are daily load profiles, which were recorded for every 15 minutes over the last year. The consumed electricity energy can well correlate with the temperature as well as the schedules of NU activities for both annual and daily scales. Peak shaving is proposed to reduce the electricity cost contributed from the high load peak during the daytime. Realistic parameters for both AC/DC converter and battery are taken into account. An optimal BESS capacity for saving the electricity cost by peak shaving is calculated by first considering the date when the highest energy demand is recorded. Our results show that the optimal BESS can shave the peak load efficiently. Oversized BESS can further decrease the load peak but the reduced cost per battery capacity is not optimal. In addition, we present and discuss two different management strategies, i.e., time-based and differentiated power criteria, for operating the BESS in this system. BESS with different storage capacity is included into the system and the equivalent electricity cost is estimated. Both time-based and differentiated power criteria can reduce the cost.

2014 International Conference and Utility Exhibition on Green Energy For Sustainable Development, Mar 19, 2014

2014 International Conference and Utility Exhibition on Green Energy For Sustainable Development, Mar 1, 2014

Electric Power Components and Systems, 2016

Abstract This article proposes an improved pseudo-gradient search-particle swarm optimization (IP... more Abstract This article proposes an improved pseudo-gradient search-particle swarm optimization (IPG-PSO) approach for solving the optimal reactive power dispatch (ORPD) problem. This ORPD problem is to determine optimal control variables, such as generator bus voltages, settings of shunt VAR compensators, and tap settings of on-load tap change (OLTC) transformers, for minimizing the real power loss, voltage deviation, and voltage stability index satisfying power balance equations and generator and network operating limit constraints. The proposed method is an improved PSO using a linearly decreasing chaotic inertia weight factor and guided by a pseudo-gradient search, which determines an appropriate direction of particles toward a global optimal solution. The proposed IPG-PSO method is used to minimize three different single-objective functions, including real power loss, voltage deviation, and voltage stability index. Test results on the IEEE 30-bus and 118-bus systems indicate that the proposed IPG-PSO method renders a higher solution quality and faster computing time than other methods. Accordingly, the proposed IPG-PSO for solving ORPD problem is potentially viable for online implementation.

In any power system, unexpected outages of lines or transformers occur due to faults or other dis... more In any power system, unexpected outages of lines or transformers occur due to faults or other disturbances. These events, referred to as contingencies, may cause significant overloading of transmission lines or transformers, which in turn may lead to a viability crisis of the power system. The principal role of power system control is to maintain a secure system state, i.e., to prevent the power system, moving from secure state into emergency state over the widest range of operating conditions. Security Constrained Optimal Power Flow (SCOPF) is major tool used to improve the security of the system. In this paper, Genetic algorithm has been used to solve the OPF and SCOPF problems. As initial effort conventional GA (binary coded) based OPF and SCOPF has been attempted. The difficulties of binary coded GA in handling continuous search space lead to the evolution of real coded GA’s. Solutions obtained using both the algorithms are compared. Results show that real coded GA is more effic...

International Journal of Energy Optimization and Engineering, 2013

This paper proposes a new improved particle swarm optimization (NIPSO) for solving nonconvex econ... more This paper proposes a new improved particle swarm optimization (NIPSO) for solving nonconvex economic dispatch (ED) problem in power systems including multiple fuel options (MFO) and valve-point loading effects (VPLE). The proposed NIPSO method is based on the self-organizing hierarchical (SOH) particle swarm optimizer with time-varying acceleration coefficients (TVAC). The self-organizing hierarchical can handle the premature convergence of the problem by re-initialization of velocity whenever particles are stagnated in the search space. During the optimization process, the performance of TVAC is applied for properly controlling both local and global explorations with cognitive component and social component of the swarm to obtain the optimum solution accurately and efficiently. The proposed NIPSO algorithm is tested in different types of non-smooth cost functions for solving ED problems and the obtained results are compared to those from many other methods in the literature. The r...

This paper proposes an augmented Lagrange Hopfield network (ALHN) for solving economic dispatch (... more This paper proposes an augmented Lagrange Hopfield network (ALHN) for solving economic dispatch (ED) problem with multiple fuel options. The proposed ALHN method is a continuous Hopfield neural network with its energy function based on augmented Lagrangian function. The advantages of ALHN over the conventional Hopfield neural network are easier use, more general applications, faster convergence, better optimal solution, and larger scale of problem implementation. The method solves the problem by directly searching the most suitable fuel among the available fuels of each unit and finding the optimal solution for the problem based on minimization of the energy function of the continuous Hopfield neural network. The proposed method is tested on systems up to 100 units and the obtained results are compared to those from other methods in the literature. The results have shown that the proposed method is efficient for solving the ED problem with multiple fuel options and favorable for imp...

… , IEEE Transactions on, 2004

Advanced correlation filters are an effective tool for target detection within a particular class... more Advanced correlation filters are an effective tool for target detection within a particular class. Most correlation filters are derived from a complex filter equation leading to a closed form filter solution. The response of the correlation filter depends upon the selected values of the optimal trade-off (OT) parameters. In this paper, the OT parameters are optimized using particle swarm optimization with respect to two different cost functions. The optimization has been made generic and is applied to each target separately in order to achieve the best possible result for each scenario. The filters obtained using standard particle swarm optimization (PSO) and hierarchal particle swarm optimization algorithms have been compared for various test images with the filter solutions available in the literature. It has been shown that optimization improves the performance of the filters significantly. INDEX TERMS Correlation filter, optimal trade-off, hierarchical particle swarm optimization, object recognition.

Journal of Automation and Control Engineering, 2014

This paper proposes a stochastic weight trade-off particle swarm optimization (SWT-PSO) method so... more This paper proposes a stochastic weight trade-off particle swarm optimization (SWT-PSO) method solving optimal power flow (OPF) problem. The proposed SWT-PSO is a new improvement of PSO method using a stochastic weight trade-off for enhancing search its search ability. The proposed method has been tested on the IEEE 30 bus and 57 bus systems and the obtained results are compared to those from other methods such as conventional PSO, genetic algorithm (GA), ant colony optimization (ACO), evolutionary programming (EP), and differential evolution (DE) methods. The numerical results have indicated that the proposed SWT-PSO method is better than the others in terms of total fuel costs, total loss and computational times. Therefore, the proposed SWT-PSO method can be a favorable method for solving OPF problem. 