Optimum size of thermal power stations

It is well known that the price per unit of generated electrical energy decreases with increasing size of the generator, which implies longer transmission lines and hence larger transmission losses. Considering both these facts, the optimum size of a thermal power station has been obtained by using life-cycle costing analysis; the demand is proposed to be met by a base load generator and a peak load generator. The dependence of the investment ratio (the ratio of present worth of net income to the capital investment) on relevant parameters has been studied. It is seen that there exist optimum sizes of base load generator and peak load generator of a power station, for a given load density. The effect of electricity price, coal price and escalation rates on the optimum sizes has also been investigated. The analysis has been made for constant demand as well as for growing demand. The effect of the ratio of base load to peak load on the economics has also been investigated. The cost data from a recent study in India have been used.     

The optimal fuel mix and redistribution of social surplus in the Korean power market

This paper investigates the difference between the optimal fuel mix incorporating a pre-installed generation capacity constraint and the actual fuel mix in the Korean power market. Since the restructuring of the market, the fuel mix has been determined partly by investors and partly by the Basic Plan for Long-Term Electricity Supply and Demand (BPE). Both the system marginal price (SMP), and the capacity payment (CP), which has been based on the fixed cost of a specific gas turbine generator, were intended to provide an investment incentive in the market; however, they did not bring about an optimal fuel mix in Korea. Under the circumstances of a shortage of base load generators, these generators may garner excessive profits due to a high SMP level. However, the adjustment scheme of profit between KEPCO and Gencos left scant profit for generators. This paper suggests that a contract is needed to create the appropriate profit and tax levels for these base load generators. The redistribution of profit improves equality between consumers and generators, and the proper margin creates incentives for base load technology investment in Korea.     

风光互补对电网输电服务价格的影响

风电和光电各自出力的不稳定性提高了输电服务成本,制约了它们的发展.利用风能和太阳能的互补性可提高发电的可靠性.研究了风光互补后对电网输电服务价格的影响,提出了考虑可再生能源并网的输电服务价格函数表达式,建立了以该函数值最小为目标,以系统发电不足概率(LOLP)和能量缺失率(LPSP)为约束条件的输电服务价格优化模型.采用粒子群算法对目标函数进行求解,对风光互补前后的输电服务价格进行对比,并求出使输电服务价格最低的风光容量配比.通过对实例系统进行计算,验证了该方法的有效性,指出风光互补能有效地降低输电服务价格.     

Flexible demand response programs modeling in competitive electricity markets

In recent years, extensive researches have been conducted on implementation of demand response programs (DRPs), aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, DRPs are divided into two main categories namely, incentive-based programs (IBPs) and time-based rate programs (TBRPs). Mathematical modeling of these programs helps regulators and market policy makers to evaluate the impact of price responsive loads on the market and system operational conditions. In this paper, an economic model of price/incentive responsive loads is derived based on the concept of flexible price elasticity of demand and customer benefit function. The mathematical model for flexible price elasticity of demand is presented to calculate each of the demand response (DR) program’s elasticity based on the electricity price before and after implementing DRPs. In the proposed model, a demand ratio parameter has been introduced to determine the appropriate values of incentive and penalty in IBPs according to the level of demand. Furthermore, the importance of determining optimum participation level of customers in different DRPs has been investigated. The proposed model together with the strategy success index (SSI) has been applied to provide an opportunity for major players of the market, i.e. independent system operator (ISO), utilities and customers to select their favorite programs that satisfy their desires. In order to evaluate the performance of the proposed model, numerical studies are conducted on the Iranian interconnected network load profile on the annual peak day of the year 2007.     

需求不确定时电力最优价格上限管制分析

采用随机需求下的连续时间模型,基于实物期权理论,运用几何布朗运动方程模拟了需求波动,分析了发电方最优投资策略,探讨了在需求不确定条件下电力价格最优上限管制问题。结果表明,需求不确定条件下最优价格上限依然为竞争性条件下的投资边际价格,最优上限价格取决于需求波动和风险率。     

Welfare implications of capacity payments in a price-capped electricity sector: A case study of the Texas market (ERCOT)

The aim of this paper is to analyze the welfare consequences of introducing capacity compensation payments in restructured and liberalized electricity markets. For that purpose, we set up a two-stage framework in which two kinds of electricity generators, peak load and base load generators, choose their capacity investment levels first and then compete on the basis of bids in a centralized market to sell electricity to consumers. We use data from the Texas ERCOT to evaluate consumers' welfare. We find that the introduction of capacity payments has two countervailing effects. On the one hand, it increases the wholesale electricity price. On the other hand, it reduces price volatility and increases the reliability of the system. We find that capacity payments are more beneficial for consumers in a perfectly competitive market than in the presence of certain degree of market power.     

An improved mechanism for capacity payment based on system dynamics modeling for investment planning in competitive electricity environment

Many countries have experienced restructuring in their electric utilities. This restructuring has presented the power industries with new challenges, the most important of which is long-term investment planning under uncertain conditions. This paper presents an improved mechanism for capacity payment. The mechanism has been investigated based on system dynamic modeling. In our proposed mechanism, generators will recover a part of their investment through capacity payment. While the payment for any plant remains constant during the operation period, it depends on the investment needed to build it. The main factors affecting long-term planning have been considered in our model. The approach can be used to investigate the effects of fixed as well as variable capacity payment in market investment. We used the probability density function of load as a new concept to calculate average market price. Delays in unit constructions, estimation of demand, and market capacity growth during construction periods have been included in the proposed algorithm as parameters, which affect the regulator's decision for changing capacity payment. The model can be used by regulators to investigate strategies that may affect the fluctuations in the market.     

Techno‐economic optimization of hybrid power system using genetic algorithm

This paper presents an optimum sizing methodology to optimize the hybrid energy system (HES) configuration based on genetic algorithm. The proposed optimization model has been applied to evaluate the techno‐economic prospective of the HES to meet the load demand of a remote village in the northern part of Saudi Arabia. The optimum configuration is not achieved only by selecting the combination with the lowest cost but also by finding a suitable renewable energy fraction that satisfies load demand requirements with zero rejected loads. Moreover, the economic, technical and environmental characteristics of nine different HES configurations were investigated and weighed against their performance. The simulation results indicated that the optimum wind turbine (WT) selection is not affected only by the WT speed parameters or by the WT rated power but also by the desired renewable energy fraction. It was found that the rated speed of the WT has a significant effect on optimum WT selection, whereas the WT rated power has no consistent effect on optimal WT selection. Moreover, the results clearly indicated that the HES consisting of photovoltaics (PV), WT, battery bank (Batt) and diesel generator (DG) has superiority over all the nine systems studied here in terms of economical and environmental performance. The PV/Batt/DG hybrid system is only feasible when wind resource is very limited and solar energy density is high. On the other hand, the WT/Batt/DG hybrid system is only feasible at high wind speed and low solar energy density. It was also found that the inclusion of batteries reduced the required DG and hence reduced fuel consumption and operating and maintenance cost. Copyright © 2014 John Wiley & Sons, Ltd.     

考虑分时电价的煤矿运输系统改造分析

介绍了生产流程中影响负荷转移的重要因素,分析了生产流程中的负荷构成,并考虑分时电价因素,建立了负荷转移模型。将该模型成功应用到煤矿传输系统中,借助分时电价,帮助煤矿企业合理转移负荷,避开峰时电价,达到节约用电成本的目的。     

Technology parameter for thermal power stations

The technology parameter which represents the ratio of fractional change of an investment to fractional change in cost of electrical energy has been computed for thermal power stations. The value lies below ten which signifies that the is good scope for additional investment (bigger power stations).     

Investment cost for geothermal power plants

Stepwise development strategy is considered a suitable method for securing a cost-effective way for the development of geothermal power plants. This strategy has been in use in Iceland for the last decade. Geothermal high-temperature fields are developed in steps of 20–30 MW. About 6 years are required for each step in the development. Parallel development of several fields in a country might be preferable, especially when a rapid increase of the generation capacity is required in that country. The capacity factor of geothermal power plants depends on the mix of power plants serving the electricity grid. Where geothermal power plants can be operated as base load, the capacity factor is usually in excess of 0.9. The investment cost of geothermal power plants is divided into the cost of surface equipment and activities and the cost of subsurface investment. The surface costs include the cost of surface exploration, and the plant and steam-gathering system, while the cost of subsurface investment is that of drilling. Surface equipment costs can be estimated with the same accuracy as other construction works at the surface (buildings, roads, bridges), whereas higher uncertainty might be associated with the cost of drilling. Analyses of the surface costs of five power plants in Iceland show that the investment cost of the surface equipment is linear with size, in the range 20–60 MW. Surface costs were found to be about 1000 USD/kW with a relative error of 10%. Stefánsson (Stefánsson, V., 1992. Success in geothermal development. Geothermics 21, 823–834) published a statistical study of the drilling results in 31 high-temperature fields in the world. Using these results, it is possible to estimate the expectation value and its limits of error for the subsurface investment in an arbtitrary geothermal field. The results obtained for the range 20–60 MW are summarized as follows:

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A fuzzy inference model for short-term load forecasting

This paper is concerned with the short-term load forecasting (STLF) in power system operations. It provides load prediction for generation scheduling and unit commitment decisions, and therefore precise load forecasting plays an important role in reducing the generation cost and the spinning reserve capacity. Short-term electricity demand forecasting (i.e., the prediction of hourly loads (demand)) is one of the most important tools by which an electric utility/company plans, dispatches the loading of generating units in order to meet system demand. The accuracy of the dispatching system, which is derived from the accuracy of the forecasting algorithm used, will determine the economics of the operation of the power system. The inaccuracy or large error in the forecast simply means that load matching is not optimized and consequently the generation and transmission systems are not being operated in an efficient manner. In the present study, a proposed methodology has been introduced to decrease the forecasted error and the processing time by using fuzzy logic controller on an hourly base. Therefore, it predicts the effect of different conditional parameters (i.e., weather, time, historical data, and random disturbances) on load forecasting in terms of fuzzy sets during the generation process. These parameters are chosen with respect to their priority and importance. The forecasted values obtained by fuzzy method were compared with the conventionally forecasted ones. The results showed that the STLF of the fuzzy implementation have more accuracy and better outcomes.     

Winds of change: How high wind penetrations will affect investment incentives in the GB electricity sector

Wind power is widely expected to expand rapidly in Britain over the next decade. Large amounts of variable wind power on the system will increase market risks, with prices more volatile and load factors for conventional thermal plant lower and more uncertain. This extra market risk may discourage investment in generation capacity. Financial viability for thermal plant will be increasingly dependent on price spikes during periods of low wind. Increased price risk will also make investment in other forms of low-carbon generation (e.g. nuclear power) more challenging.     

Demand response modeling considering Interruptible/Curtailable loads and capacity market programs

Recently, a massive focus has been made on demand response (DR) programs, aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, demand response programs are divided into two main categories namely, incentive-based programs and time-based programs. The focus of this paper is on Interruptible/Curtailable service (I/C) and capacity market programs (CAP), which are incentive-based demand response programs including penalties for customers in case of no responding to load reduction. First, by using the concept of price elasticity of demand and customer benefit function, economic model of above mentioned programs is developed. The proposed model helps the independent system operator (ISO) to identify and employ relevant DR program which both improves the characteristics of the load curve and also be welcome by customers. To evaluate the performance of the model, simulation study has been conducted using the load curve of the peak day of the Iranian power system grid in 2007. In the numerical study section, the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption are shown. In addition, by using strategy success indices the results of simulation studies for different scenarios are analyzed and investigated for determination of the scenarios priority.     

Energy consumption and economic growth in Turkey during the past two decades

The Turkish economy has undergone a transformation from agricultural to industrial, enhanced by rapid urbanization, especially after 1982. Turkey's gross national production has grown at an average annual rate of 5% since 1983, ranking it at the top of the OECD countries, although the growth pattern has been uneven. Economic growth in recent years has been associated with the privatization of public enterprises. Turkey's energy demand has risen rapidly as a result of social and economic development. The country's energy consumption has grown considerably since the beginning of the 1980s. The Turkish government encourages foreign and Turkish private sector investors to implement the energy projects and is currently working on a new investment model for the construction of new generation plants to create the additional capacity needed. The Turkish energy sector, with its current size of 30 billion US dollars and projected size of 55 billion US dollars by 2015, as well as the fundamental restructuring process it has been going through since 2001, attracts both local and foreign investors. The sector needs an investment amount of approximately 130 billion US dollars by 2020. The aim of the present paper is to investigate the increasing of Turkish energy demand with the growth of the economy and utilization of domestic energy sources and the case of investments and imports in Turkey during the past two decades.     

世界促进风电产业发展最新动向

近年来可再生能源发电发展迅速,其中风力发电表现尤为突出.在一些风电先行国家的推动下,风电机组大型化取得长足进展,单机容量从亚兆瓦级迅速提升到兆瓦级,研制中的10MW级风电机组即将问世.机组的大型化提高了风电的经济性和竞争力.风机设备利用率将由目前的25％左右提高至2015年的28％,同时投资成本将大幅下降,按照GWEC的高增长方案预测,投资成本将由2009年的1350欧元/kW降至2030年的1093欧元/kW.鉴于风力发电的间歇性和随机性,蓄电技术成为大量引入可再生能源的有效手段,美欧日等都投入专项经费支持蓄电技术的研究开发.IEA最近在报告中指出,与热电联产组合的方式可大幅扩大可再生能源的利用,其重点在于热供应.智能电网将成为解决风电大规模接入和输送问题的根本途径,它将使电力系统整体利用效率大大提高,有利于抑制发电厂的化石燃料消费.我国在智能电网方面已取得了一定成果,但仍面临许多问题.各国政府的可再生能源电力收购政策促进了风电产业的发展,其中德国的风电收购政策值得我国借鉴.     

Predictive control of an integrated PV-diesel water and power supply system using an artificial neural network

This paper discusses the development of a predictive artificial neural network (ANN)-based prototype controller for the optimum operation of an integrated hybrid renewable energy-based water and power supply system (IRWPSS). The integrated system, which has been assembled, consists of photovoltaic modules, diesel generator, battery bank for energy storage and a reverse osmosis desalination unit. The electrical load consists of typical households and the desalination plant. The proposed Artificial Neural Networking controller is designed to be implemented to take decision on diesel generators ON/OFF status and maintain a minimum loading level on the generator under light load and high solar radiation levels and maintain high efficiency of the generators and switch off diesel generator when not required based on predictive information. The key objectives are to reduce fuel dependency, engine wear and tear due to incomplete combustion and cut down on greenhouse gas emissions. The statistical analysis of the results indicates that the R² value for the testing set of 186 cases tested was 0.979. This indicates that ANN-based model developed in this work can predict the power usage and generator status at any point of time with high accuracy.     

如何应对当前我国电力供应不足的问题

2003年我国经济增长速度将7.8～8.3%,全社会用电量需求增长也将达11～13%。本文分析了当前我国电力供需紧张的主要原因,电网负荷率降低使得可发电量有余、可供电力不足。为了解决当前电力供应不足的问题,本文提出采用需求侧管理的办法,通过拉大峰谷电价,推出尖峰电价及可中断负荷等措施,降低1000万kW的高峰负荷,缓解电力供应紧张的局面。     

A comparative life cycle energy cost analysis of photovoltaic and fuel generator for load shedding application

Comparative life cycle energy cost analysis for different electricity generators (photovoltaic generator, kerosene generator and diesel generator) used during load shedding is presented. The parameters considered for calculation of the unit cost of energy are: the discount rate, inflation rate, IREDA loan facility to promote PV, operation and maintenance cost of PV and fuel generator (FG) set and the associated fuel cost. It is found that the unit cost of PV electricity is comparable to or less than that of FG generated electricity at present market prices.     

Optimisation and techno-economic feasibility analysis of hybrid (photovoltaic/wind/fuel cell) energy systems in Kerman,Iran; considering the effects of electrical load and energy storage technology

A hybrid (photovoltaic, PV/wind/fuel cell, FC) system comprising different combinations of PV arrays, wind turbine, hydrogen tank, electrolyser, and FC has been investigated for stand-alone applications. Load demand was the electrical requirements of atypical residential apartment having a total area of 500 m² with a peak electrical load of 35 kW and a yearly load of 24.4 MWh in Kerman, Iran. The assessment criterion for the analysis was levellised cost of energy of each system configuration. National Renewable Energy Laboratory's Hybrid Optimization Model for Electric Renewable software was utilised as the assessment tool of the present study. The effect of electrical load profile on the optimisation results has also been investigated considering a demand load profile with a low peak of 12 kW. Also, a comparison was made between the hybrid (PV/wind/diesel/bat) systems and the hybrid (PV/wind/FC) system of the current study at different fuel price scenarios.