DOI: 10.1007/s11708-014-0340-8

Vincenzo BIANCO,Federico SCARPA,Luca A. TAGLIAFICO

Abstract: Gas market in Europe is experiencing a radical change for different reasons, partially determined and accelerated by economic downturn of the last period. In the past few years, many European countries adopted energy policies largely based on the utilization of natural gas. In fact, a sharp increase of the demand was observed and, at the same time, a lot of infrastructures were developed to assure the necessary supply. In the last few years, due to the economic downturn, natural gas demand decreased, causing a consistent oversupply on the market, which altered the consolidated dynamics of the sector. Understanding the changes currently under development in the European gas market is of paramount importance in order to design future strategies for the sector; in particular, it is necessary to understand if the present situation will cause a reshaping of the sector.

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Cite this article: Vincenzo BIANCO,Federico SCARPA,Luca A. TAGLIAFICO. Current situation and future perspectives of European natural gas sector[J]. Frontiers in Energy, 2015. 9(1): 1-6

DOI: 10.1007/s11708-014-0338-2

Y. K. BHATESHVAR,H. D. MATHUR,H. SIGUERDIDJANE

Abstract: Among the available options for renewable energy integration in existing power system, wind power is being considered as one of the suited options for future electrical power generation. The major constraint of wind power generating system (WPGS) is that it does not provide inertial support because of power electronic converters between the grid and the WPGS to facilitate frequency stabilization. The proposed control strategy suggests a substantial contribution to system inertia in terms of short-term active power support in a two area restructured power system. The control scheme uses fuzzy logic based design and takes frequency deviation as input to provide quick active power support, which balances the drop in frequency and tie-line power during transient conditions. This paper presents a comprehensive study of the wind power impact with increasing wind power penetration on frequency stabilization in restructured power system scenario. Variation of load conditions are also analyzed in simulation studies for the same power system model with the proposed control scheme. Simulation results advocates the justification of control scheme over other schemes.

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Cite this article: Y. K. BHATESHVAR,H. D. MATHUR,H. SIGUERDIDJANE. Impact of wind power generating system integration on frequency stabilization in multi-area power system with fuzzy logic controller in deregulated environment[J]. Frontiers in Energy, 2015. 9(1): 7-21

DOI: 10.1007/s11708-014-0339-1

A. CHITRA,S. HIMAVATHI

Abstract: Online estimation of rotor resistance is essential for high performance vector controlled drives. In this paper, a novel modified neural algorithm has been identified for the online estimation of rotor resistance. Neural based estimators are now receiving active consideration as they have a number of advantages over conventional techniques. The training algorithm of the neural network determines its learning speed, stability, weight convergence, accuracy of estimation, speed of tracking and ease of implementation. In this paper, the neural estimator has been studied with conventional and proposed learning algorithms. The sensitivity of the rotor resistance change has been tested for a wide range of variation from -50% to+50% on the stability of the drive system with and without estimator. It is quiet appealing to settle with optimal estimation time and error for the viable realization. The study is conducted extensively for estimation and tracking. The proposed learning algorithm is found to exhibit good estimation and tracking capabilities. Besides, it reduces computational complexity and, hence, more feasible for practical digital implementation.

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Cite this article: A. CHITRA,S. HIMAVATHI. A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction motor drives[J]. Frontiers in Energy, 2015. 9(1): 22-30

DOI: 10.1007/s11708-015-0347-9

C. K. ARAVIND,G. SARAVANA ILANGO,C. NAGAMANI

Abstract: The standalone hybrid power system constitutes a synchronous generator driven by a diesel engine, renewable energy source (wind) apart from a battery energy storage system. A coherent control strategy to regulate the voltage and frequency of the standalone grid is proposed in this paper. The system is simulated using Matlab/Simulink for preliminary validation and further tested on a laboratory prototype which involves a TMS320LF2407A DSP controller to digitally implement the control strategy. The dynamic behavior of the system is perused through the direct connection of an induction machine. The control strategy is verified for step changes in load and variation in wind power.

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Cite this article: C. K. ARAVIND,G. SARAVANA ILANGO,C. NAGAMANI. A smooth co-ordination control for a hybrid autonomous power system (HAPS) with battery energy storage (BES)[J]. Frontiers in Energy, 2015. 9(1): 31-42

DOI: 10.1007/s11708-014-0343-5

Ammar NEÇAIBIA,Samir LADACI,Abdelfattah CHAREF,Jean Jacques LOISEAU

Abstract: Due to the high interest in renewable energy and diversity of research regarding photovoltaic (PV) array, a great research effort is focusing nowadays on solar power generation and its performance improvement under various weather conditions. In this paper, an integrated framework was proposed, which achieved both maximum power point tracking (MPPT) and minimum ripple signals. The proposed control scheme was based on extremum-seeking (ES) combined with fractional order systems (FOS). This auto-tuning strategy was developed to maximize the PV panel output power through the regulation of the voltage input to the DC/DC converter in order to lead the PV system steady-state to a stable oscillation behavior around the maximum power point (MPP). It is shown that fractional order operators can improve the plant dynamics with respect to time response and disturbance rejection. The effectiveness of the proposed controller scheme is illustrated with simulations using measured solar radiation data.

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Cite this article: Ammar NEÇAIBIA,Samir LADACI,Abdelfattah CHAREF,Jean Jacques LOISEAU. Fractional order extremum seeking approach for maximum power point tracking of photovoltaic panels[J]. Frontiers in Energy, 2015. 9(1): 43-53

DOI: 10.1007/s11708-014-0342-6

S. NIKBAKHT NASERABAD,K. MOBINI,A. MEHRPANAHI,M. R. ALIGOODARZ

Abstract: A 320 MW old steam power plant has been chosen for repowering in this paper. Considering the technical conditions and working life of the power plant, the full repowering method has been selected from different repowering methods. The power plant repowering has been analyzed for three different feed water flow rates: a flow rate equal to the flow rate at the condenser exit in the original plant when it works at nominal load, a flow rate at maximum load, and a flow rate when all the extractions are blocked. For each flow rates, two types of gas turbines have been examined: V94.2 and V94.3A. The effect of a duct burner has then been investigated in each of the above six cases. Steam is produced by a double-pressure heat recovery steam generator (HRSG) with reheat which obtains its required heat from the exhaust gases coming from the gas turbines. The results obtained from modeling and analyzing the energy-exergy of the original steam power plant and the repowered power plant indicate that the maximum efficiency of the repowered power plant is 52.04%. This maximum efficiency occurs when utilizing two V94.3A gas turbines without duct burner in the steam flow rate of the nominal load.

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Cite this article: S. NIKBAKHT NASERABAD,K. MOBINI,A. MEHRPANAHI,M. R. ALIGOODARZ. Exergy-energy analysis of full repowering of a steam power plant[J]. Frontiers in Energy, 2015. 9(1): 54-67

DOI: 10.1007/s11708-015-0349-7

M. M. RAJAN SINGARAVEL,S. ARUL DANIEL

Abstract: The number of electric vehicles are increasing in the society as they are considered as zero emission vehicles and also because conventional fuels are becoming expensive. Additional electrical power should be produced to meet the energy requirement of this increase in electric vehicle population. To use the existing grid infrastructure without any failure, installing distributed generator at secondary distribution network is essential. In this work, sizing of wind-driven permanent magnet synchronous generator—photovoltaic hybrid distributed generating system has been attempted to meet the energy demand of electric vehicles of a particular residential area. Different feasible combinations for wind generator capacity and photovoltaic capacity are obtained to satisfy the additional energy requirement. Results are analyzed based on energy, financial payback periods and daily power profile of the hybrid system. Based on this analysis, the sizes of wind generator and photovoltaic array have been chosen to meet the energy demand of electric vehicles of that particular residential locality.

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Cite this article: M. M. RAJAN SINGARAVEL,S. ARUL DANIEL. Sizing of hybrid PMSG-PV system for battery charging of electric vehicles[J]. Frontiers in Energy, 2015. 9(1): 68-74

DOI: 10.1007/s11708-014-0337-3

Mehrdad TARAFDAR HAGH,Homayoun EBRAHIMIAN,Noradin GHADIMI

Abstract: In this paper, a passive neuro-wavelet based islanding detection technique for grid-connected inverter-based distributed generation was developed. The weight parameters of the neural network were optimized by intelligent water drop (IWD) to improve the capability of the proposed technique in the proposed problem. The proposed method utilizes and combines wavelet analysis and artificial neural network (ANN) to detect islanding. Connecting distributed generator to the distribution network has many benefits such as increasing the capacity of the grid and enhancing the power quality. However, it gives rise to many problems. This is mainly due to the fact that distribution networks are designed without any generation units at that level. Hence, integrating distributed generators into the existing distribution network is not problem-free. Unintentional islanding is one of the encountered problems. Discrete wavelet transform (DWT) is capable of decomposing the signals into different frequency bands. It can be utilized in extracting discriminative features from the acquired voltage signals. In passive schemes with a large non-detection zone (NDZ), concern has been raised on active method due to its degrading power quality effect. The main emphasis of the proposed scheme is to reduce the NDZ to as close as possible and to keep the output power quality unchanged. The simulation results from Matlab/Simulink shows that the proposed method has a small non-detection zone, and is capable of detecting islanding accurately within the minimum standard time.

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Cite this article: Mehrdad TARAFDAR HAGH,Homayoun EBRAHIMIAN,Noradin GHADIMI. Hybrid intelligent water drop bundled wavelet neural network to solve the islanding detection by inverter-based DG[J]. Frontiers in Energy, 2015. 9(1): 75-90

DOI: 10.1007/s11708-015-0345-y

Deepak KUMAR,D. K. MOHANTA,M. Jaya Bharata REDDY

Abstract: Power system planning is a capital intensive investment-decision problem. The majority of the conventional planning conducted since the last half a century has been based on the least cost approach, keeping in view the optimization of cost and reliability of power supply. Recently, renewable energy sources have found a niche in power system planning owing to concerns arising from fast depletion of fossil fuels, fuel price volatility as well as global climatic changes. Thus, power system planning is under-going a paradigm shift to incorporate such recent technologies. This paper assesses the impact of renewable sources using the portfolio theory to incorporate the effects of fuel price volatility as well as CO₂ emissions. An optimization framework using a robust multi-objective evolutionary algorithm, namely NSGA-II, is developed to obtain Pareto optimal solutions. The performance of the proposed approach is assessed and illustrated using the Indian power system considering real-time design practices. The case study for Indian power system validates the efficacy of the proposed methodology as developing countries are also increasing the investment in green energy to increase awareness about clean energy technologies.

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Cite this article: Deepak KUMAR,D. K. MOHANTA,M. Jaya Bharata REDDY. Intelligent optimization of renewable resource mixes incorporating the effect of fuel risk, fuel cost and CO₂ emission[J]. Frontiers in Energy, 2015. 9(1): 91-105

DOI: 10.1007/s11708-014-0341-7

Ramin ROSHANDEL,Majid ASTANEH,Farzin GOLZAR

Abstract: The aim of this paper is to investigate the implementation of a molten carbonate fuel cell (MCFC) as a CO₂ separator. By applying multi-objective optimization (MOO) using the genetic algorithm, the optimal values of operating load and the corresponding values of objective functions are obtained. Objective functions are minimization of the cost of electricity (COE) and minimization of CO₂ emission rate. CO₂ tax that is accounted as the pollution-related cost, transforming the environmental objective to the cost function. The results show that the MCFC stack which is fed by the syngas and gas turbine exhaust, not only reduces CO₂ emission rate, but also produces electricity and reduces environmental cost of the system.

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Cite this article: Ramin ROSHANDEL,Majid ASTANEH,Farzin GOLZAR. Multi-objective optimization of molten carbonate fuel cell system for reducing CO₂ emission from exhaust gases[J]. Frontiers in Energy, 2015. 9(1): 106-114

DOI: 10.1007/s11708-015-0348-8

Shangguang YANG,Chunlan WANG,Kevin LO,Mark WANG,Lin LIU

Abstract: Understanding the spatial variability of household carbon emissions is necessary for formulating sustainable and low-carbon energy policy. However, data on household carbon emissions is limited in China, the world’s largest greenhouse gases emitter. This study quantifies and maps household carbon emissions in Shanghai using a city-wide household survey. The findings reveal substantial spatial variability in household carbon emissions, especially in transport-related emissions. Low emission clusters are founded in Hongkou, Xuhui, Luwan, Jinshan, and Fengxian. High emission clusters are located in Jiading and Pudong. Overall, the spatial pattern of household carbon emissions in Shanghai is donut-shaped: lowest in the urban core, increasing in the surrounding suburban areas, and declining again in the urban fringe and rural regions. The household emissions are correlated with a number of housing and socioeconomic factors, including car ownership, type of dwelling, size of dwelling, age of dwelling, and income. The findings underscore the importance of a localized approach to low-carbon policy-making and implementation.

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Cite this article: Shangguang YANG,Chunlan WANG,Kevin LO,Mark WANG,Lin LIU. Quantifying and mapping spatial variability of Shanghai household carbon footprints[J]. Frontiers in Energy, 2015. 9(1): 115-124