Comprehensive efficiency evaluation model for electrical distribution system considering social and urban factors

This paper addresses a comprehensive efficiency evaluation model for electrical distribution system. Concerning the efficiency of different resources including energy, infrastructure and human resources, the overall distribution system efficiency is determined on the basis of relevant efficiency indicators. The employed efficiency indicators comprising loss, utilization factor, power factor, load factor, energy not supplied and human resource productivity express the efficiency of the above-mentioned resources. The proposed model takes into account the effect of certain external factors on the performance of distribution system. It has been shown that how external factors such as governance, social behavior and urban planning can directly influence the efficiency of the system. The correlation between efficiency indicators and external factors is derived using artificial neural network and a sensitivity analysis is conducted to illuminate the path of efficiency increment through managing the effective external factors. These indices can be used for improvement of the system performance in system planning. An empirical study is addressed here based on a real world distribution network to investigate the performance of the proposed model.

[1]  R. Billinton,et al.  Utilizing Bulk Electric System Reliability Performance Index Probability Distributions in a Performance Based Regulation Framework , 2006, 2006 International Conference on Probabilistic Methods Applied to Power Systems.

[2]  M. Carvalho,et al.  EU energy and climate change strategy , 2012 .

[3]  Mehdi Ehsan,et al.  A distribution network expansion planning model considering distributed generation options and techo-economical issues , 2010 .

[4]  Whei-Min Lin,et al.  Fuzzy neural network output maximization control for sensorless wind energy conversion system , 2010 .

[5]  Jamshid Aghaei,et al.  Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems) , 2013 .

[6]  Antonio Vanderley Herrero Sola,et al.  Organizational human factors as barriers to energy efficiency in electrical motors systems in industry , 2007 .

[7]  M. P. Moghaddam,et al.  Optimal real time pricing in an agent-based retail market using a comprehensive demand response model , 2011 .

[8]  Shahram Jadid,et al.  A fuzzy environmental-technical-economic model for distributed generation planning , 2011 .

[9]  F. Ghaderi,et al.  AGA (Asset Governance Assessment) for analyzing affect of subsidy on MC (Marginal Cost) in electrici , 2010 .

[10]  N. G. Boulaxis,et al.  Optimal Feeder Routing in Distribution System Planning Using Dynamic Programming Technique and GIS Facilities , 2001, IEEE Power Engineering Review.

[11]  W. Axinn,et al.  Social organization and the transition from direct to indirect consumption. , 2010, Social science research.

[12]  Carmen L. T. Borges,et al.  Optimal distributed generation allocation for reliability, losses, and voltage improvement , 2006 .

[13]  S. Sivanagaraju,et al.  Discrete Particle Swarm Optimization to Network Reconfiguration for Loss Reduction and Load Balancing , 2008 .

[14]  M.M.A. Salama,et al.  An integrated distributed generation optimization model for distribution system planning , 2005, IEEE Transactions on Power Systems.

[15]  L. Bertling,et al.  A reliability-centered asset maintenance method for assessing the impact of maintenance in power distribution systems , 2005, IEEE Transactions on Power Systems.

[16]  Nilay Shah,et al.  The impact of CHP (combined heat and power) planning restrictions on the efficiency of urban energy systems , 2012 .

[17]  Hassan Ghasemi,et al.  A new long term load management model for asset governance of electrical distribution systems , 2010 .

[18]  Jordan Pop-Jordanov,et al.  SWOT analyses of the national energy sector for sustainable energy development , 2009 .

[19]  Satya S. Chakravorty,et al.  Improving distribution operations: Implementation of material handling systems , 2009 .

[20]  J. Mora-Florez,et al.  Fault Location in Power Distribution Systems Using a Learning Algorithm for Multivariable Data Analysis , 2007, IEEE Transactions on Power Delivery.

[21]  Ahmed R. Abul’Wafa,et al.  Optimal capacitor allocation in radial distribution systems for loss reduction: A two stage method , 2013 .

[22]  Ernst Worrell,et al.  Policy scenarios for energy efficiency improvement in industry , 2001 .

[23]  G.C. Heffner,et al.  Innovative approaches to verifying demand response of water heater load control , 2006, IEEE Transactions on Power Delivery.

[24]  Reza Dashti,et al.  Demand response regulation modeling based on distribution system asset efficiency , 2011 .

[25]  Mohammad Sadegh Hatamipour,et al.  Evaluation of existing cooling systems for reducing cooling power consumption , 2007 .

[26]  Boqiang Lin,et al.  Impacts of removing fossil fuel subsidies on China: How large and how to mitigate? , 2012 .

[27]  Yi-Ming Wei,et al.  Can market oriented economic reforms contribute to energy efficiency improvement? Evidence from China , 2007 .

[28]  Javad Olamaei,et al.  Loss reduction experiences in electric power distribution companies of Iran , 2012 .

[29]  Ernst Worrell,et al.  Energy efficiency in the German pulp and paper industry – A model-based assessment of saving potentials , 2012 .

[30]  Humberto M. Jorge,et al.  Dealing with the paradox of energy efficiency promotion by electric utilities , 2013 .

[31]  M. L. Dyer,et al.  Distribution Transformer Life Assessment with Ambient Temperature Rise Projections , 2009 .

[32]  Pavlos S. Georgilakis,et al.  A Review of Transformer Losses , 2009 .

[33]  Zhuding Wang,et al.  A set of new formulations and hybrid algorithms for distribution system planning , 2005, IEEE Power Engineering Society General Meeting, 2005.

[34]  Ibrahim Helal A Procedure For Distribution System Planning Of A Large-Scale Agricultural Project , 2008 .

[35]  Reza Dashti,et al.  Reliability based asset assessment in electrical distribution systems , 2013, Reliab. Eng. Syst. Saf..

[36]  Kenichi Wada,et al.  Energy efficiency opportunities in the residential sector and their feasibility , 2012 .

[37]  C. Senabre,et al.  Methods for customer and demand response policies selection in new electricity markets , 2007 .

[38]  Lambros Ekonomou,et al.  Greek long-term energy consumption prediction using artificial neural networks , 2010 .