Titirut Mekbunditkul and Sorachai Phisalbutr

DOI: https://doi.org/10.6000/1929-7092.2017.06.23

Published: 09 June 2017

Abstract: This paper is concerned with the National Statistical Office of Thailand, and constructs a Code of Practice and indicators for quality management of official statistics in Thailand. Official statistics for quality management from three international agencies include the United Nations Statistics Division (UNSD), European Statistical System (Eurostat), and International Monetary Fund (IMF). Factor analysis is used to determine the important indicators and their respective weights. The research shows that a Code of Practice for quality management of official statistics in Thailand should be comprised of 9 rules and 35 common indicators.

Aumnad Phdungsilp

DOI: https://doi.org/10.6000/1929-7092.2017.06.24

Published: 09 June 2017 

Abstract: Cities around the world have developed innovative plans and strategies to reduce rampant and uncontrolled energy use and CO₂ emissions. It is not surprising that many cities have adopted long-term emission reduction goals. However, a detailed analysis of energy use and the resulting carbon emissions are rare in developing countries. This paper presents historical trends of energy demand and energy-related CO₂ emissions for Bangkok, Thailand. The CO₂ emissions account for the use of fossil fuels only. It also presents the projections of energy use and CO₂ emissions from 2010 to 2050. Using a bottom-up energy model and scenario analysis, the paper employs a Long-range Energy Alternative Planning (LEAP) system to simulate four sectors in Bangkok. The results identified by the BAU (business-as-usual) scenario indicate that total energy is expected to reach 54,560 kilotonne of oil equivalent (ktoe) with 191 million tonne CO₂ (Mt-CO₂) by 2050. Under the alternative scenario, if all policy interventions are implemented simultaneously, the potential for energy-savings and reduced CO₂ emissions in 2050 are estimated to be 32,120 ktoe and 106.19 Mt-CO₂. Other international cities may wish to apply the strategies and analytical approaches presented in this paper for developing appropriate policies and measures in their own jurisdictions.

Anurak Choeichum, Narongdech Keeratipranon and Chaiyaporn Khemapatapan

DOI: https://doi.org/10.6000/1929-7092.2017.06.25

Published: 09 June 2017 

Abstract: The ever increasing growth of energy consumption has stimulated an energy crisis, not only in terms of energy demand, but also the impact of climate change from greenhouse gas (GHG) emissions. Renewable energy sources (RES) have high potential toward sustainable development, with a wide variety of socioeconomic benefits, including diversification of energy supply and creation of domestic industry. This paper presents a solution to optimal multi-fuel allocation for the electric power generation planning problem via genetic algorithms (GA). The objective is to maximize the electric power energy output and minimize generation cost. This is a difficult problem because of its data variation and volatility. GA can provide an appropriate heuristic search method and return an actual or near optimal solution. This paper uses some heuristics during crossover and mutation for tuning the system to obtain a better candidate solution. An experimental result showed significantly improved results compared with other techniques. The results in this paper should be useful for connecting power generation with economic growth.

Phatcharasak Phawanaphinyo, Narongdech Keeratipranon and Chaiyaporn Khemapatapan

DOI: https://doi.org/10.6000/1929-7092.2017.06.26

Published: 09 June 2017 

Abstract: Electric power is the main energy source for a modern society. Good management of electric power cycle is essential for a sustainable society. The electric power cycle is composed of Generation, Transmission, Distribution, and Consumption. Smart Grid (SG) is a system that integrated traditional grids with Information and Communication Technology (ICT). In addition, SG has the ability to integrate electrical power supply from both to main power substation and Distributed Generation (DG), which compensates for the power demand during peak times. However, SG still has a similar problem to the original grid in terms of active power loss, from electric current injecting through the transmission line. This paper solves the active power loss problem by feeder routing using the Adjusting Dijkstra’s Cost Method, follow by deciding the allocation position and sizing of DG by the use of Evolutionary Computing, namely Harmony Search (HS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO). The experiments evaluate the performance of the algorithm using power flow analysis, Backward / Forward Sweep Method, on the IEEE 33 bus system. From the experimental results, PSO provides the best performance. The overall active power loss in the cases of 3 DGs was reduced from 202.67 to 52.29 kW, representing a reduction of 74.20%..

Renu Sukharomana and Chia-Lin Chang

DOI: https://doi.org/10.6000/1929-7092.2017.06.27

Published: 09 June 2017 

Abstract: The paper examines the demand for narcotic drugs, based on Becker (1968), as purported rational behavior of human beings. The results from sampling surveys in eight provinces in Thailand in 2014, representing nationwide drug users/addicts, show that the demand for narcotics (amphetamines, ice drug, and marijuana) are price inelastic (between -0.533 and -0.701), as well as normal goods. The key econometric coefficients in models A and B are 0.192 and 0.0467, respectively, and an increase in income will lead to an increase in the demand for narcotics. In addition, factors affecting the demand for narcotics are the age and age squared of the user, friendship, family member relationship, social relationship, reasons for drug use, risk behavior, and expected punishment. Public policy implications are also proposed and analysed.