Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1146

Search results for: electricity market

1146 Financial Portfolio Optimization in Electricity Markets: Evaluation via Sharpe Ratio

Authors: F. Gökgöz, M. E. Atmaca

Abstract:

Electricity plays an indispensable role in human life and the economy. It is a unique product or service that must be balanced instantaneously, as electricity is not stored, generation and consumption should be proportional. Effective and efficient use of electricity is very important not only for society, but also for the environment. A competitive electricity market is one of the best ways to provide a suitable platform for effective and efficient use of electricity. On the other hand, it carries some risks that should be carefully managed by the market players. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Markowitz’s Mean-variance, Down-side and Semi-variance methods for a case study. Performance of optimal electricity sale solutions are measured and evaluated via Sharpe-Ratio, and the optimal portfolio solutions are improved. Two years of historical weekdays’ price data of the Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: Electricity market, portfolio optimization, risk management in electricity market, Sharpe ratio.

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1145 Financial Portfolio Optimization in Turkish Electricity Market via Value at Risk

Authors: F. Gökgöz, M. E. Atmaca

Abstract:

Electricity has an indispensable role in human daily life, technological development and economy. It is a special product or service that should be instantaneously generated and consumed. Sources of the world are limited so that effective and efficient use of them is very important not only for human life and environment but also for technological and economic development. Competitive electricity market is one of the important way that provides suitable platform for effective and efficient use of electricity. Besides benefits, it brings along some risks that should be carefully managed by a market player like Electricity Generation Company. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Value at Risk methods for case studies. Performance of optimal electricity sale solutions are measured and the portfolio performance has been evaluated via Sharpe-Ratio, and compared with conventional approach. Biennial historical electricity price data of Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: Electricity market, portfolio optimization, risk management, Sharpe ratio, value at risk.

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1144 Optimal Choice and Location of Multi Type Facts Devices in Deregulated Electricity Market Using Evolutionary Programming Method

Authors: K. Balamurugan, R. Muralisachithanandam, V. Dharmalingam, R. Srikanth

Abstract:

This paper deals with the optimal choice and allocation of multi FACTS devices in Deregulated power system using Evolutionary Programming method. The objective is to achieve the power system economic generation allocation and dispatch in deregulated electricity market. Using the proposed method, the locations of the FACTS devices, their types and ratings are optimized simultaneously. Different kinds of FACTS devices are simulated in this study such as UPFC, TCSC, TCPST, and SVC. Simulation results validate the capability of this new approach in minimizing the overall system cost function, which includes the investment costs of the FACTS devices and the bid offers of the market participants. The proposed algorithm is an effective and practical method for the choice and allocation of FACTS devices in deregulated electricity market environment. The standard data of IEEE 14 Bus systems has been taken into account and simulated with aid of MAT-lab software and results were obtained.

Keywords: FACTS devices, Optimal allocation, Deregulated electricity market, Evolutionary programming, Mat Lab.

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1143 Influence of Distributed Generation on Congestion and LMP in Competitive Electricity Market

Authors: Durga Gautam, Mithulananthan Nadarajah

Abstract:

This paper presents the influence of distributed generation (DG) on congestion and locational marginal price (LMP) in an optimal power flow (OPF) based wholesale electricity market. The problem of optimal placement to manage congestion and reduce LMP is formulated for the objective of social welfare maximization. From competitive electricity market standpoint, DGs have great value when they reduce load in particular locations and at particular times when feeders are heavily loaded. The paper lies on the groundwork that solution to optimal mix of generation and transmission resources can be achieved by addressing congestion and corresponding LMP. Obtained as lagrangian multiplier associated with active power flow equation for each node, LMP gives the short run marginal cost (SRMC) of electricity. Specific grid locations are examined to study the influence of DG penetration on congestion and corresponding shadow prices. The influence of DG on congestion and locational marginal prices has been demonstrated in a modified IEEE 14 bus test system.

Keywords: Congestion management, distributed generation, electricity market, locational marginal price, optimal power flow, social welfare.

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1142 Overview of Risk Management in Electricity Markets Using Financial Derivatives

Authors: Aparna Viswanath

Abstract:

Electricity spot prices are highly volatile under optimal generation capacity scenarios due to factors such as nonstorability of electricity, peak demand at certain periods, generator outages, fuel uncertainty for renewable energy generators, huge investments and time needed for generation capacity expansion etc. As a result market participants are exposed to price and volume risk, which has led to the development of risk management practices. This paper provides an overview of risk management practices by market participants in electricity markets using financial derivatives.

Keywords: Financial Derivatives, Forward, Futures, Options, Risk Management.

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1141 Modeling Prices of Electricity Futures at EEX

Authors: Robest Flasza, Milan Rippel, Jan Solc

Abstract:

The main aim of this paper is to develop and calibrate an econometric model for modeling prices of long term electricity futures contracts. The calibration of our model is performed on data from EEX AG allowing us to capture the specific features of German electricity market. The data sample contains several structural breaks which have to be taken into account for modeling. We model the data with an ARIMAX model which reveals high correlation between the price of electricity futures contracts and prices of LT futures contracts of fuels (namely coal, natural gas and crude oil). Besides this, also a share price index of representative electricity companies traded on Xetra, spread between 10Y and 1Y German bonds and exchange rate between EUR and USD appeared to have significant explanatory power over these futures contracts on EEX.

Keywords: electricity futures, EEX, ARIMAX, emissionallowances

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1140 Differential Evolution Based Optimal Choice and Location of Facts Devices in Restructured Power System

Authors: K. Balamurugan, V. Dharmalingam, R. Muralisachithanandam, R. Sankaran

Abstract:

This paper deals with the optimal choice and location of FACTS devices in deregulated power systems using Differential Evolution algorithm. The main objective of this paper is to achieve the power system economic generation allocation and dispatch in deregulated electricity market. Using the proposed method, the locations of the FACTS devices, their types and ratings are optimized simultaneously. Different kinds of FACTS devices such as TCSC and SVC are simulated in this study. Furthermore, their investment costs are also considered. Simulation results validate the capability of this new approach in minimizing the overall system cost function, which includes the investment costs of the FACTS devices and the bid offers of the market participants. The proposed algorithm is an effective and practical method for the choice and location of suitable FACTS devices in deregulated electricity market.

Keywords: FACTS Devices, Deregulated Electricity Market, Optimal Location, Differential Evolution, Mat Lab.

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1139 Electricity Price Forecasting: A Comparative Analysis with Shallow-ANN and DNN

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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1138 Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: Building energy prediction, data mining, demand response, electricity market.

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1137 Application of Universal Distribution Factors for Real-Time Complex Power Flow Calculation

Authors: Abdullah M. Alodhaiani, Yasir A. Alturki, Mohamed A. Elkady

Abstract:

Complex power flow distribution factors, which relate line complex power flows to the bus injected complex powers, have been widely used in various power system planning and analysis studies. In particular, AC distribution factors have been used extensively in the recent power and energy pricing studies in free electricity market field. As was demonstrated in the existing literature, many of the electricity market related costing studies rely on the use of the distribution factors. These known distribution factors, whether the injection shift factors (ISF’s) or power transfer distribution factors (PTDF’s), are linear approximations of the first order sensitivities of the active power flows with respect to various variables. This paper presents a novel model for evaluating the universal distribution factors (UDF’s), which are appropriate for an extensive range of power systems analysis and free electricity market studies. These distribution factors are used for the calculations of lines complex power flows and its independent of bus power injections, they are compact matrix-form expressions with total flexibility in determining the position on the line at which line flows are measured. The proposed approach was tested on IEEE 9-Bus system. Numerical results demonstrate that the proposed approach is very accurate compared with exact method.

Keywords: Distribution Factors, Power System, Sensitivity Factors, Electricity Market.

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1136 Electricity Load Modeling: An Application to Italian Market

Authors: Giovanni Masala, Stefania Marica

Abstract:

Forecasting electricity load plays a crucial role regards decision making and planning for economical purposes. Besides, in the light of the recent privatization and deregulation of the power industry, the forecasting of future electricity load turned out to be a very challenging problem. Empirical data about electricity load highlights a clear seasonal behavior (higher load during the winter season), which is partly due to climatic effects. We also emphasize the presence of load periodicity at a weekly basis (electricity load is usually lower on weekends or holidays) and at daily basis (electricity load is clearly influenced by the hour). Finally, a long-term trend may depend on the general economic situation (for example, industrial production affects electricity load). All these features must be captured by the model. The purpose of this paper is then to build an hourly electricity load model. The deterministic component of the model requires non-linear regression and Fourier series while we will investigate the stochastic component through econometrical tools. The calibration of the parameters’ model will be performed by using data coming from the Italian market in a 6 year period (2007- 2012). Then, we will perform a Monte Carlo simulation in order to compare the simulated data respect to the real data (both in-sample and out-of-sample inspection). The reliability of the model will be deduced thanks to standard tests which highlight a good fitting of the simulated values.

Keywords: ARMA-GARCH process, electricity load, fitting tests, Fourier series, Monte Carlo simulation, non-linear regression.

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1135 A Profit-Based Maintenance Scheduling of Thermal Power Units in Electricity Market

Authors: Smajo Bisanovic, Mensur Hajro, Muris Dlakic

Abstract:

This paper presents one comprehensive modelling approach for maintenance scheduling problem of thermal power units in competitive market. This problem is formulated as a 0/1 mixedinteger linear programming model. Model incorporates long-term bilateral contracts with defined profiles of power and price, and weekly forecasted market prices for market auction. The effectiveness of the proposed model is demonstrated through case study with detailed discussion.

Keywords: Maintenance scheduling, bilateral contracts, market prices, profit.

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1134 Dynamic Self-Scheduling of Pumped-Storage Power Plant in Energy and Ancillary Service Markets Using Sliding Window Technique

Authors: P. Kanakasabapathy, Radhika. S,

Abstract:

In the competitive electricity market environment, the profit of the pumped-storage plant in the energy market can be maximized by operating it as a generator, when market clearing price is high and as a pump, to pump water from lower reservoir to upper reservoir, when the price is low. An optimal self-scheduling plan has been developed for a pumped-storage plant, carried out on weekly basis in order to maximize the profit of the plant, keeping into account of all the major uncertainties such as the sudden ancillary service delivery request and the price forecasting errors. For a pumped storage power plant to operate in a real time market successive self scheduling has to be done by considering the forecast of the day-ahead market and the modified reservoir storage due to the ancillary service request of the previous day. Sliding Window Technique has been used for successive self scheduling to ensure profit for the plant.

Keywords: Ancillary services, BPSO, Power System Economics (Electricity markets), Self-Scheduling, Sliding Window Technique.

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1133 GenCos- Optimal Bidding Strategy Considering Market Power and Transmission Constraints: A Cournot-based Model

Authors: A. Badri

Abstract:

Restructured electricity markets may provide opportunities for producers to exercise market power maintaining prices in excess of competitive levels. In this paper an oligopolistic market is presented that all Generation Companies (GenCos) bid in a Cournot model. Genetic algorithm (GA) is applied to obtain generation scheduling of each GenCo as well as hourly market clearing prices (MCP). In order to consider network constraints a multiperiod framework is presented to simulate market clearing mechanism in which the behaviors of market participants are modelled through piecewise block curves. A mixed integer linear programming (MILP) is employed to solve the problem. Impacts of market clearing process on participants- characteristic and final market prices are presented. Consequently, a novel multi-objective model is addressed for security constrained optimal bidding strategy of GenCos. The capability of price-maker GenCos to alter MCP is evaluated through introducing an effective-supply curve. In addition, the impact of exercising market power on the variation of market characteristics as well as GenCos scheduling is studied.

Keywords: Optimal bidding strategy, Cournot equilibrium, market power, network constraints, market auction mechanism

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1132 Day Type Identification for Algerian Electricity Load using Kohonen Maps

Authors: Mohamed Tarek Khadir, Damien Fay, Ahmed Boughrira

Abstract:

Short term electricity demand forecasts are required by power utilities for efficient operation of the power grid. In a competitive market environment, suppliers and large consumers also require short term forecasts in order to estimate their energy requirements in advance. Electricity demand is influenced (among other things) by the day of the week, the time of year and special periods and/or days such as Ramadhan, all of which must be identified prior to modelling. This identification, known as day-type identification, must be included in the modelling stage either by segmenting the data and modelling each day-type separately or by including the day-type as an input. Day-type identification is the main focus of this paper. A Kohonen map is employed to identify the separate day-types in Algerian data.

Keywords: Day type identification, electricity Load, Kohonenmaps, load forecasting.

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1131 Using Exponential Lévy Models to Study Implied Volatility patterns for Electricity Options

Authors: Pinho C., Madaleno M.

Abstract:

German electricity European options on futures using Lévy processes for the underlying asset are examined. Implied volatility evolution, under each of the considered models, is discussed after calibrating for the Merton jump diffusion (MJD), variance gamma (VG), normal inverse Gaussian (NIG), Carr, Geman, Madan and Yor (CGMY) and the Black and Scholes (B&S) model. Implied volatility is examined for the entire sample period, revealing some curious features about market evolution, where data fitting performances of the five models are compared. It is shown that variance gamma processes provide relatively better results and that implied volatility shows significant differences through time, having increasingly evolved. Volatility changes for changed uncertainty, or else, increasing futures prices and there is evidence for the need to account for seasonality when modelling both electricity spot/futures prices and volatility.

Keywords: Calibration, Electricity Markets, Implied Volatility, Lévy Models, Options on Futures, Pricing

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1130 Electrolysis Ship for Green Hydrogen Production and Possible Applications

Authors: Julian David Hunt, Andreas Nascimento

Abstract:

Green hydrogen is the most environmental, renewable alternative to produce hydrogen. However, an important challenge to make hydrogen a competitive energy carrier is a constant supply of renewable energy, such as solar, wind and hydropower. Given that the electricity generation potential of these sources vary seasonally and interannually, this paper proposes installing an electrolysis hydrogen production plant in a ship and move the ship to the locations where electricity is cheap, or where the seasonal potential for renewable generation is high. An example of electrolysis ship application is to produce green hydrogen with hydropower from the North region of Brazil and then sail to the Northeast region of Brazil and generate hydrogen using excess electricity from offshore wind power. The electrolysis ship concept is interesting because it has the flexibility to produce green hydrogen using the cheapest renewable electricity available in the market.

Keywords: Green hydrogen, electrolysis ship, renewable energies, seasonal variations.

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1129 Implementation of Neural Network Based Electricity Load Forecasting

Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw

Abstract:

This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.

Keywords: Neural network, Load forecast, Time series, wavelettransform.

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1128 Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market

Authors: Ioannis P. Panapakidis, Marios N. Moschakis

Abstract:

The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: Deregulated energy market, forecasting, machine learning, system marginal price, energy efficiency and quality.

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1127 Hourly Electricity Load Forecasting: An Empirical Application to the Italian Railways

Authors: M. Centra

Abstract:

Due to the liberalization of countless electricity markets, load forecasting has become crucial to all public utilities for which electricity is a strategic variable. With the goal of contributing to the forecasting process inside public utilities, this paper addresses the issue of applying the Holt-Winters exponential smoothing technique and the time series analysis for forecasting the hourly electricity load curve of the Italian railways. The results of the analysis confirm the accuracy of the two models and therefore the relevance of forecasting inside public utilities.

Keywords: ARIMA models, Exponential smoothing, Electricity, Load forecasting, Rail transportation.

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1126 Profit Optimization for Solar Plant Electricity Production

Authors: Fl. Loury, P. Sablonière

Abstract:

In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.

Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.

Keywords: Molten Salt Storage System, Concentrated Solar Tower Power Plant, Robust Stochastic Model Predictive Control.

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1125 Effects of the Second Entrant in GSM Telecommunication Market in MENA Region

Authors: A.R. Yari, M.R. Sadri

Abstract:

For the first incumbent operator it is very important to understand how to react when the second operator comes to the market. In this paper which is prepared for preliminary study of GSM market in Iran, we have studied five MENA markets according to the similarity point of view. This paper aims at analyzing the impact of second entrants in selected markets on certain marketing key performance indicators (KPI) such as: Market shares (by operator), prepaid share, minutes of use (MoU), Price and average revenue per user (ARPU) (for total market each).

Keywords: GSM Market, Second entrant, MENA.

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1124 Variation of Spot Price and Profits of Andhra Pradesh State Grid in Deregulated Environment

Authors: Chava Sunil Kumar, P.S. Subrahmanyan, J. Amarnath

Abstract:

In this paper variation of spot price and total profits of the generating companies- through wholesale electricity trading are discussed with and without Central Generating Stations (CGS) share and seasonal variations are also considered. It demonstrates how proper analysis of generators- efficiencies and capabilities, types of generators owned, fuel costs, transmission losses and settling price variation using the solutions of Optimal Power Flow (OPF), can allow companies to maximize overall revenue. It illustrates how solutions of OPF can be used to maximize companies- revenue under different scenarios. And is also extended to computation of Available Transfer Capability (ATC) is very important to the transmission system security and market forecasting. From these results it is observed that how crucial it is for companies to plan their daily operations and is certainly useful in an online environment of deregulated power system. In this paper above tasks are demonstrated on 124 bus real-life Indian utility power system of Andhra Pradesh State Grid and results have been presented and analyzed.

Keywords: OPF, ATC, Electricity Market, Bid, Spot Price

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1123 Assessing Relationship between Type of Financial Market and Market Indices in Tehran Stock Exchange

Authors: Zahra Amirhosseini, Alireza Bashiri

Abstract:

The aim of this study was to examine and identify the type of Iranian financial market in terms of being symmetrical or asymmetrical and to measure relationship between type of market and the market's indices. In this study, daily information on the market-s Share Price Index, Industrial Index and Top Fifty Most Active Companies during the years 1999-2010 has been used. In addition, to determine type of the financial market, rate of return on Security is taken into account. In this research, by using logistic regression analysis methods, relationship of the market type with the above mentioned indices have been examined. The results showed that the type of the financial market has a positive significant association with market share price index and Industrial Index. Index of Top Fifty Most Active Companies is significantly associated with type of financial market, however this relationship is inverse.

Keywords: All Share Price Index, Asymmetrical Market, Industrial Index, Symmetrical Market, Top Fifty Most Active Companies Index

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1122 DEMO Based Optimal Power Purchase Planning Under Electricity Price Uncertainty

Authors: Tulika Bhattacharjee, A. K.Chakraborty

Abstract:

Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.

Keywords: Deregulation, Differential Evolution, Multi objective Optimization, Pareto Optimal Set, Optimal Power Flow

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1121 Restructuring Kuwait Electric Power System: Mandatory or Optional?

Authors: Osamah A. Alsayegh

Abstract:

Kuwait-s electric power system is vertically integrated organization owned and operated by the government. For more than five decades, the government of Kuwait has provided relatively reliable electric services to consumers with subsidized electric service fees. Given the country-s rapid socio-economical development and consequently the increase of electricity demand, a question that inflicts itself: Is it necessary to reform the power system to face the fast growing demand? This paper recommends that the government should consider the private sector as a partner in operating the power system. Therefore, power system restructuring is needed to allow such partnership. There are challenges that prevent such restructuring. Abstract recommendations toward resolving these challenges are proposed.

Keywords: Deregulation, electricity market, ISO, private sector.

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1120 Electricity Consumption and Economic Growth: The Case of Mexico

Authors: Mario Gómez, José Carlos Rodríguez

Abstract:

The causality between energy consumption and economic growth has been an important issue in the economic literature. This paper studies the causal relationship between electricity consumption and economic growth in Mexico for the period of 1971-2011. In so doing, unit root and causality tests are applied. The results show that energy consumption and economic growth series are stationary and there is also a causality relationship running from economic growth to electricity consumption. Therefore, any energy conservation policy would have little or no impact at all on economic growth in México.

Keywords: Causality, economic growth, electricity consumption, Mexico.

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1119 The modeling of Brand Loyalty in the Brewing Market in Poland

Authors: Honorata Howaniec

Abstract:

Brand loyalty is a strategic asset of the company. In the era of competition to have loyal customers decides on the market superiority of enterprises. Creating the loyalty of buyers, however, is a lengthy process and requires the appropriate business strategy, preceded by the proper market research. The purpose of the paper is to present the concept of brand loyalty, the creation of loyalty of customers, the benefits and determinants of loyalty on the example of brewery market in Poland.

Keywords: brand, brand loyalty, brewery market

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1118 Solar Energy Potential and Applications in Myanmar

Authors: Thet Thet Han Yee, Su Su Win, Nyein Nyein Soe

Abstract:

Energy consumption is one of the indices in determining the levels of development of a nation. Therefore, availability of energy supply to all sectors of life in any country is crucial for its development. These exists shortage of all kinds of energy, particularly electricity which is badly needed for economic development. Electricity from the sun which is quite abundant in most of the developing countries is used in rural areas to meet basic electricity needs of a rural community. Today-s electricity supply in Myanmar is generated by fuel generators and hydroelectric power plants. However, far-flung areas which are away from National Grids cannot enjoy the electricity generated by these sources. Since Myanmar is a land of plentiful sunshine, especially in central and southern regions of the country, the first form of energy- solar energy could hopefully become the final solution to its energy supply problem. The direct conversion of solar energy into electricity using photovoltaic system has been receiving intensive installation not only in developed countries but also in developing countries. It is mainly intended to present solar energy potential and application in Myanmar. It is also wanted to get the benefits of using solar energy for people in remote areas which are not yet connected to the national grids because of the high price of fossil fuel.

Keywords: Electricity supply in Myanmar, National Grids, solarenergy.

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1117 The Impact of Subsequent Stock Market Liberalization on the Integration of Stock Markets in ASEAN-4 + South Korea

Authors: Noor Azryani Auzairy, Rubi Ahmad

Abstract:

To strengthen the capital market, there is a need to integrate the capital markets within the region by removing legal or informal restriction, specifically, stock market liberalization. Thus the paper is to investigate the effects of the subsequent stock market liberalization on stock market integration in 4 ASEAN countries (Malaysia, Indonesia, Thailand, Singapore) and Korea from 1997 to 2007. The correlation between stock market liberalization and stock market integration are to be examined by analyzing the stock prices and returns within the region and in comparison with the world MSCI index. Event study method is to be used with windows of ±12 months and T-7 + T. The results show that the subsequent stock market liberalization generally, gives minor positive effects to stock returns, except for one or two countries. The subsequent liberalization also integrates the markets short-run and long-run.

Keywords: ASEAN, event method, stock market integration, stock market liberalization.

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