Pub Date : 2013-10-01DOI: 10.4018/ijeoe.2013100104
V. Stennikov, T. Oshchepkova, N. Stennikov
The paper addresses the issue of optimal expansion and reconstruction of heat supply systems, which includes a set of general and relatively specific problems. Therefore, a comprehensive approach to their solving is required to obtain a technically admissible and economically sound result. Solving the problem suggests search for effective directions in expansion of a system in terms of optimal allocation of new heat sources, their type, output, operating area; construction of new heat networks, their schemes and parameters; optimal detection of “bottlenecks†in the system and ways of their elimination (expansion, dismantling, replacement, strengthening of heat pipeline sections, construction of pumping stations and other components of heat supply networks). The authors present a mathematical statement of the problem, its decomposition into separate subproblems and an integrated technique to solve it. Consideration is given to a real problem solved for a real heat supply system. A set of arising problems is presented. The application of developed methodological and computational tools is shown.
{"title":"Optimal Expansion and Reconstruction of Heat Supply Systems: Methodology and Practice","authors":"V. Stennikov, T. Oshchepkova, N. Stennikov","doi":"10.4018/ijeoe.2013100104","DOIUrl":"https://doi.org/10.4018/ijeoe.2013100104","url":null,"abstract":"The paper addresses the issue of optimal expansion and reconstruction of heat supply systems, which includes a set of general and relatively specific problems. Therefore, a comprehensive approach to their solving is required to obtain a technically admissible and economically sound result. Solving the problem suggests search for effective directions in expansion of a system in terms of optimal allocation of new heat sources, their type, output, operating area; construction of new heat networks, their schemes and parameters; optimal detection of “bottlenecks†in the system and ways of their elimination (expansion, dismantling, replacement, strengthening of heat pipeline sections, construction of pumping stations and other components of heat supply networks). The authors present a mathematical statement of the problem, its decomposition into separate subproblems and an integrated technique to solve it. Consideration is given to a real problem solved for a real heat supply system. A set of arising problems is presented. The application of developed methodological and computational tools is shown.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"442 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123616610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-10-01DOI: 10.4018/ijeoe.2013100107
V. Stennikov, I. Postnikov
The paper deals with the problem of comprehensive analysis of heat supply reliability for consumers. It implies a quantitative assessment of the impact of all stages of heat energy production and distribution on heat supply reliability for each consumer of the heat supply system. A short review of existing methods for the analysis of fuel and heat supply reliability is presented that substantiates the key approaches to solving the problem of comprehensive analysis of heat supply reliability. A methodological approach is suggested, in which mathematical models and methods for nodal evaluation of heat supply reliability for consumers are developed and the studies on the impact of different elements of fuel and heat supply systems on its level are described. Mathematical modeling is based on the Markov random processes, models of flow distribution in a heat network, deterministic dependences of thermal processes of heat energy consumption and some other models.
{"title":"Methods for Comprehensive Analysis of Heat Supply Reliability","authors":"V. Stennikov, I. Postnikov","doi":"10.4018/ijeoe.2013100107","DOIUrl":"https://doi.org/10.4018/ijeoe.2013100107","url":null,"abstract":"The paper deals with the problem of comprehensive analysis of heat supply reliability for consumers. It implies a quantitative assessment of the impact of all stages of heat energy production and distribution on heat supply reliability for each consumer of the heat supply system. A short review of existing methods for the analysis of fuel and heat supply reliability is presented that substantiates the key approaches to solving the problem of comprehensive analysis of heat supply reliability. A methodological approach is suggested, in which mathematical models and methods for nodal evaluation of heat supply reliability for consumers are developed and the studies on the impact of different elements of fuel and heat supply systems on its level are described. Mathematical modeling is based on the Markov random processes, models of flow distribution in a heat network, deterministic dependences of thermal processes of heat energy consumption and some other models.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114321927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-12DOI: 10.4018/ijeoe.2013100102
A. S. Apartsyn, S. Solodusha, V. Spiryaev
The paper presents a review of the studies that were conducted at Energy Systems Institute ESI SB RAS in the field of mathematical modeling of nonlinear input-output dynamic systems with Volterra polynomials. The first part presents an original approach to identification of the Volterra kernels. The approach is based on setting special multi-parameter families of piecewise constant test input signals. It also includes a description of the respective software; presents illustrative calculations on the example of a reference dynamic system as well as results of computer modeling of real heat exchange processes. The second part of the review is devoted to the Volterra polynomial equations of the first kind. Studies of such equations were pioneered and have been carried out in the past decade by the laboratory of ill-posed problems at ESI SB RAS. A special focus in the paper is made on the importance of the Lambert function for the theory of these equations.
{"title":"Modeling of Nonlinear Dynamic Systems with Volterra Polynomials: Elements of Theory and Applications","authors":"A. S. Apartsyn, S. Solodusha, V. Spiryaev","doi":"10.4018/ijeoe.2013100102","DOIUrl":"https://doi.org/10.4018/ijeoe.2013100102","url":null,"abstract":"The paper presents a review of the studies that were conducted at Energy Systems Institute ESI SB RAS in the field of mathematical modeling of nonlinear input-output dynamic systems with Volterra polynomials. The first part presents an original approach to identification of the Volterra kernels. The approach is based on setting special multi-parameter families of piecewise constant test input signals. It also includes a description of the respective software; presents illustrative calculations on the example of a reference dynamic system as well as results of computer modeling of real heat exchange processes. The second part of the review is devoted to the Volterra polynomial equations of the first kind. Studies of such equations were pioneered and have been carried out in the past decade by the laboratory of ill-posed problems at ESI SB RAS. A special focus in the paper is made on the importance of the Lambert function for the theory of these equations.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127917897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-01DOI: 10.4018/ijeoe.2013070104
E. Maleviti, W. Wehrmeyer, Y. Mulugetta
This paper presents the key findings of a study conducted in Greek hotels. Energy audits were carried out in 43 cases across Greece. The different technical characteristics of each building have a different effect in the total final energy consumption. The findings of this research showed the variable that is the most statistically significant among the selected sample to be used for analyzing further the data. This study showed that this process is necessary to be used as a preliminary step in any type of energy forecasting, since it would define the most appropriate expression to be used for improving the building’s energy performance and reducing their energy consumption. The statistical analysis is very important at that stage since energy is expressed differently, such as kWh/m2 or kWh/person, or kWh. In this particular research, the statistical analysis defines the expression that is more statistically valid to be used in further analysis of the energy data, providing also significant literature about the importance and role of statistical tests.
{"title":"An Empirical Assessment to Express the Variability of Buildings' Energy Consumption","authors":"E. Maleviti, W. Wehrmeyer, Y. Mulugetta","doi":"10.4018/ijeoe.2013070104","DOIUrl":"https://doi.org/10.4018/ijeoe.2013070104","url":null,"abstract":"This paper presents the key findings of a study conducted in Greek hotels. Energy audits were carried out in 43 cases across Greece. The different technical characteristics of each building have a different effect in the total final energy consumption. The findings of this research showed the variable that is the most statistically significant among the selected sample to be used for analyzing further the data. This study showed that this process is necessary to be used as a preliminary step in any type of energy forecasting, since it would define the most appropriate expression to be used for improving the building’s energy performance and reducing their energy consumption. The statistical analysis is very important at that stage since energy is expressed differently, such as kWh/m2 or kWh/person, or kWh. In this particular research, the statistical analysis defines the expression that is more statistically valid to be used in further analysis of the energy data, providing also significant literature about the importance and role of statistical tests.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134474217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-01DOI: 10.4018/ijeoe.2013070103
Tran Trong Dao, I. Zelinka, D. Hoàng
This work deals with using a method of artificial intelligence, mainly the generic probabilistic meta-algorithm can be used in such a difficult task which is analyzed and control of dynamical systems. Simulated annealing (SA) is used in this investigation. The adaptive control system was used in simulations with optimization by Simulated Annealing and the results are presented in graphs.
{"title":"Use of Simulated Annealing for Adaptive Control System","authors":"Tran Trong Dao, I. Zelinka, D. Hoàng","doi":"10.4018/ijeoe.2013070103","DOIUrl":"https://doi.org/10.4018/ijeoe.2013070103","url":null,"abstract":"This work deals with using a method of artificial intelligence, mainly the generic probabilistic meta-algorithm can be used in such a difficult task which is analyzed and control of dynamical systems. Simulated annealing (SA) is used in this investigation. The adaptive control system was used in simulations with optimization by Simulated Annealing and the results are presented in graphs.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114198320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-01DOI: 10.4018/ijeoe.2013070105
Cvetko J. Andreeski
Life insurance is very challenging sector in developing countries. Life insurance makes contribute at the investments in every country, so the more developed life insurance, more investments one should expect. One of the main aspects in calculation of risk in life insurance is using updated tables of mortality and forecast of the future values of mortality. There are many functions and models for mortality forecast calculation. Lee-Carter and Azbel Model for mortality trend calculation are used in this paper. In order to evaluate the results, data sets with the mortality in the Republic of Macedonia are used.
{"title":"Optimal Values for Calculation of Premium in Life Insurance","authors":"Cvetko J. Andreeski","doi":"10.4018/ijeoe.2013070105","DOIUrl":"https://doi.org/10.4018/ijeoe.2013070105","url":null,"abstract":"Life insurance is very challenging sector in developing countries. Life insurance makes contribute at the investments in every country, so the more developed life insurance, more investments one should expect. One of the main aspects in calculation of risk in life insurance is using updated tables of mortality and forecast of the future values of mortality. There are many functions and models for mortality forecast calculation. Lee-Carter and Azbel Model for mortality trend calculation are used in this paper. In order to evaluate the results, data sets with the mortality in the Republic of Macedonia are used.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127935444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-01DOI: 10.4018/ijeoe.2013070101
S. Hutterer, M. Affenzeller
Probabilistic power flow studies represent essential challenges in nowadays power system operation and research. Here, especially the incorporation of intermittent supply plants with optimal control of dispatchable demand like electric vehicle charging power shows nondeterministic aspects. Using simulation-based optimization, such probabilistic and dynamic behavior can be fully integrated within the metaheuristic optimization process, yielding into a generic approach suitable for optimization in uncertain environments. A practical problem scenario is demonstrated that computes optimal charging schedules of a given electrified fleet in order to meet both power flow constraints of the distribution grid while satisfying vehicle-owners’ energy demand and considering stochastic supply of wind power plants. Since solution- evaluation through simulation is computational expensive, a new fitness-based sampling scheme will be proposed, that avoids unnecessary evaluations of less-performant solution candidates.
{"title":"Probabilistic Electric Vehicle Charging Optimized With Genetic Algorithms and a Two-Stage Sampling Scheme","authors":"S. Hutterer, M. Affenzeller","doi":"10.4018/ijeoe.2013070101","DOIUrl":"https://doi.org/10.4018/ijeoe.2013070101","url":null,"abstract":"Probabilistic power flow studies represent essential challenges in nowadays power system operation and research. Here, especially the incorporation of intermittent supply plants with optimal control of dispatchable demand like electric vehicle charging power shows nondeterministic aspects. Using simulation-based optimization, such probabilistic and dynamic behavior can be fully integrated within the metaheuristic optimization process, yielding into a generic approach suitable for optimization in uncertain environments. A practical problem scenario is demonstrated that computes optimal charging schedules of a given electrified fleet in order to meet both power flow constraints of the distribution grid while satisfying vehicle-owners’ energy demand and considering stochastic supply of wind power plants. Since solution- evaluation through simulation is computational expensive, a new fitness-based sampling scheme will be proposed, that avoids unnecessary evaluations of less-performant solution candidates.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127102147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-01DOI: 10.4018/ijeoe.2013070106
P. Roy, D. Mandal
The aim of this paper is to evaluate a hybrid biogeography-based optimization approach based on the hybridization of biogeography-based optimization with differential evolution to solve the optimal power flow problem. The proposed method combines the exploration of differential evolution with the exploitation of biogeography-based optimization effectively to generate the promising candidate solutions. Simulation experiments are carried on standard 26-bus and IEEE 30-bus systems to illustrate the efficacy of the proposed approach. Results demonstrated that the proposed approach converged to promising solutions in terms of quality and convergence rate when compared with the original biogeography-based optimization and other population based optimization techniques like simple genetic algorithm, mixed integer genetic algorithm, particle swarm optimization and craziness based particle swarm optimization.
{"title":"Hybridization of Biogeography-Based: Optimization with Differential Evolution for Solving Optimal Power Flow Problems","authors":"P. Roy, D. Mandal","doi":"10.4018/ijeoe.2013070106","DOIUrl":"https://doi.org/10.4018/ijeoe.2013070106","url":null,"abstract":"The aim of this paper is to evaluate a hybrid biogeography-based optimization approach based on the hybridization of biogeography-based optimization with differential evolution to solve the optimal power flow problem. The proposed method combines the exploration of differential evolution with the exploitation of biogeography-based optimization effectively to generate the promising candidate solutions. Simulation experiments are carried on standard 26-bus and IEEE 30-bus systems to illustrate the efficacy of the proposed approach. Results demonstrated that the proposed approach converged to promising solutions in terms of quality and convergence rate when compared with the original biogeography-based optimization and other population based optimization techniques like simple genetic algorithm, mixed integer genetic algorithm, particle swarm optimization and craziness based particle swarm optimization.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122279499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-01DOI: 10.4018/ijeoe.2013070107
V. Savsani
Rolling element bearings are widely used as important components in most of the mechanical engineering applications. These bearings find wide applications in automotive, manufacturing and aeronautical industries. The problem associated with rolling element bearings are that the design and selection are based on different operating conditions to reach their excellent performance, long life and high reliability. This leads to the requirement of optimal design of rolling element bearings. Optimization aspects of a rolling element bearing are presented in this paper considering three different objectives namely, dynamic capacity, static capacity and elastohydrodynamic minimum film thickness. The design parameters include mean diameter of rolling, ball diameter, number of balls, and inner and outer race groove curvature radii. Different constants associated with the constraints are given some ranges and are included as design variables. The optimization procedure is carried out using artificial bee colony (ABC) optimization technique, artificial immune algorithm (AIA), and particle swarm optimization (PSO) technique. Both single and multi-objective optimization aspects are considered. The results of the considered techniques are compared with the previously published results. The considered techniques have given much better results in comparison to the previously tried approaches.
{"title":"Multi-Objective Design Optimization of Rolling Element Bearings Using ABC, AIA and PSO Technique","authors":"V. Savsani","doi":"10.4018/ijeoe.2013070107","DOIUrl":"https://doi.org/10.4018/ijeoe.2013070107","url":null,"abstract":"Rolling element bearings are widely used as important components in most of the mechanical engineering applications. These bearings find wide applications in automotive, manufacturing and aeronautical industries. The problem associated with rolling element bearings are that the design and selection are based on different operating conditions to reach their excellent performance, long life and high reliability. This leads to the requirement of optimal design of rolling element bearings. Optimization aspects of a rolling element bearing are presented in this paper considering three different objectives namely, dynamic capacity, static capacity and elastohydrodynamic minimum film thickness. The design parameters include mean diameter of rolling, ball diameter, number of balls, and inner and outer race groove curvature radii. Different constants associated with the constraints are given some ranges and are included as design variables. The optimization procedure is carried out using artificial bee colony (ABC) optimization technique, artificial immune algorithm (AIA), and particle swarm optimization (PSO) technique. Both single and multi-objective optimization aspects are considered. The results of the considered techniques are compared with the previously published results. The considered techniques have given much better results in comparison to the previously tried approaches.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115072319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-07-01DOI: 10.4018/IJEOE.2013070102
Vincent Anayochukwu Ani
Hybrid PV/Wind power system can be used to generate electricity consumed in household. This paper presents the design of a stand-alone Hybrid PV/Wind energy system for a household in University of Nigeria, Nsukka (UNN) in Eastern Nigeria with a daily load of 5.2kwh/d. Solar and wind resources for the design of the system were obtained from the NASA Surface Meteorology and solar energy website at a location of 6° 51' N latitude and 7° 24' E longitude, with annual average solar radiation of 4.92kWh/m2/d and annual average wind speed of 2.1m/s. The study is based on modeling, simulation and optimization of energy system in UNN. The model was designed to provide an optimal system configuration based on hour-by-hour data for energy availability and demands. Energy source, energy storage and their applicability in terms of cost and performance are discussed. The Hybrid Optimization Model for Electric Renewables (HOMER) software is used to study and design the proposed stand-alone Hybrid PV/Wind power system model. The designed Hybrid PV/Wind was compared to gasoline generator in order to choose the best energy system for the household. Total Net Present Cost (NPC) and impact on the environment are used as indices for measuring the optimization level of each energy solution. Simulation results show the Hybrid PV/Wind option ($317,907; 0 tonnes of CO2) to be superior to conventional solution ($374,237; 2.049 tonnes of CO2) whereby gasoline generators are currently used to power household around Nigeria.
{"title":"Optimal Energy System for Single Household in Nigeria","authors":"Vincent Anayochukwu Ani","doi":"10.4018/IJEOE.2013070102","DOIUrl":"https://doi.org/10.4018/IJEOE.2013070102","url":null,"abstract":"Hybrid PV/Wind power system can be used to generate electricity consumed in household. This paper presents the design of a stand-alone Hybrid PV/Wind energy system for a household in University of Nigeria, Nsukka (UNN) in Eastern Nigeria with a daily load of 5.2kwh/d. Solar and wind resources for the design of the system were obtained from the NASA Surface Meteorology and solar energy website at a location of 6° 51' N latitude and 7° 24' E longitude, with annual average solar radiation of 4.92kWh/m2/d and annual average wind speed of 2.1m/s. The study is based on modeling, simulation and optimization of energy system in UNN. The model was designed to provide an optimal system configuration based on hour-by-hour data for energy availability and demands. Energy source, energy storage and their applicability in terms of cost and performance are discussed. The Hybrid Optimization Model for Electric Renewables (HOMER) software is used to study and design the proposed stand-alone Hybrid PV/Wind power system model. The designed Hybrid PV/Wind was compared to gasoline generator in order to choose the best energy system for the household. Total Net Present Cost (NPC) and impact on the environment are used as indices for measuring the optimization level of each energy solution. Simulation results show the Hybrid PV/Wind option ($317,907; 0 tonnes of CO2) to be superior to conventional solution ($374,237; 2.049 tonnes of CO2) whereby gasoline generators are currently used to power household around Nigeria.","PeriodicalId":246250,"journal":{"name":"Int. J. Energy Optim. Eng.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127216819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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