In this work, a comparative study on emissions and cost implications of diesel <span style="font-family:Verdana;">powered and solar photovoltaic-diesel hybrid systems was carried out for th</span>...In this work, a comparative study on emissions and cost implications of diesel <span style="font-family:Verdana;">powered and solar photovoltaic-diesel hybrid systems was carried out for th</span><span style="font-family:Verdana;">ree commercial banks. With the aid of HOMER Pro software, meteorological data, energy demand, system component data, capital and operating costs were used for analysis of the two systems. The results showed that in Bank A, the diesel generator alone releases 111,618 kg/yr of Carbon dioxide while the hybrid system releases 41,618 kg/yr of Carbon dioxide. For Bank B the quantity of carbon dioxide emissions released from the diesel generator in Bank B is 53,830 kg/yr, while the carbon dioxide released from the hybrid energy system is 24,082 kg/yr. For Bank C, the diesel generator alone released 177,799 kg/yr of Carbon dioxide and 129,060 kg/yr of carbon dioxide was released from the hybrid system. This suggests that the diesel generator alone releases more emissions when compared with the hybrid system in all the three banks. The Net present cost of energy and levelized cost of energy were used to find out the cost effectiveness of hybrid systems. The results showed that the levelized cost of energy for the generator alone and hybrid system, respectively in Bank A is $0.713 and $0.343. While for Bank B, it is $0.568 and $0.2553. Finally for Bank C, it was $0.731 and $0.556. Therefore, solar-diesel hybrid system has a comparatively low emission and can be considered as a more economical option for electricity generation.</span>展开更多
In view of the high cost of solar thermal power generation in China,it is difficult to realize large-scale production in engineering and industrialization.Non-dominated sorting genetic algorithm II(NSGA-II)is applied ...In view of the high cost of solar thermal power generation in China,it is difficult to realize large-scale production in engineering and industrialization.Non-dominated sorting genetic algorithm II(NSGA-II)is applied to optimize the levelling cost of energy(LCOE)of the solar thermal power generation system in this paper.Firstly,the capacity and generation cost of the solar thermal power generation system are modeled according to the data of several sets of solar thermal power stations which have been put into production abroad.Secondly,the NSGA-II genetic algorithm and particle swarm algorithm are applied to the optimization of the solar thermal power station LCOE respectively.Finally,for the linear Fresnel solar thermal power system,the simulation experiments are conducted to analyze the effects of different solar energy generation capacities,different heat transfer mediums and loan interest rates on the generation price.The results show that due to the existence of scale effect,the greater the capacity of the power station,the lower the cost of leveling and electricity,and the influence of the types of heat storage medium and the loan on the cost of leveling electricity are relatively high.展开更多
There is an increase in annual waste generation due to urbanization,industrialization,and population growth.The waste management crisis in developing countries and its complexity from region to region has inspired ext...There is an increase in annual waste generation due to urbanization,industrialization,and population growth.The waste management crisis in developing countries and its complexity from region to region has inspired extensive research work in this area.Poor management not only results in environmental hazards,but it also causes significant socio-economic losses.Due to the absence of comprehensive studies on waste to energy(WTE)assessment,this study assesses and reports the merits of alternative technologies for converting WTE in small and medium-size districts.Quantitative analysis for waste collection data in this study uses a pilot study approach to provide useful insights and waste classification.A cantonment district of Pakistan(Wah Cantt)has been used as a case study for performing a technological and economic assessment of energy generation through the use of thermal and biological treatment processes.A mathematical modeling approach has been adopted for generating an economic value of each technology through which this waste can be processed.Further,the levelized cost of energy(LCOE)based assessment has been performed to provide a methodological framework for selecting the most feasible WTE technology in a small or medium-size district.Based on the model results,anaerobic digestion appears to be the most sustainable technology due to the organic nature of waste in Wah Cantt,land legislation,and availability of area to install a waste plant.Considering all the waste collected,the district can generate approximately 14.4 MW of energy through thermal treatment,19,110 m^(3) of daily biogas through anaerobic digestion,and 5 million tons of fertilizer through composting.Hence,if a proper supply chain is established for converting a portion of Pakistan’s annual waste generation,a significant amount of waste energy potential can be restored.展开更多
<div style="text-align:left;"> Rural households represent, by far, the greater percentage of dwellings globally without access to the electricity supply. For reasons of low loads, distance from the gri...<div style="text-align:left;"> Rural households represent, by far, the greater percentage of dwellings globally without access to the electricity supply. For reasons of low loads, distance from the grid and speed of deployment, distributed energy systems are now considered viable options for rural electrification. This paper presents the status of solar Photovoltaic (PV) in Nigeria and discusses the way forward for aggressive PV penetration in Nigeria’s energy mix, especially in rural communities. At present, distributed PV penetration in Nigeria is comparatively low based on the International Energy Association’s recommended PV market potential. This shows that there is a gap between the government’s <span>policy targets and reality. The solar resource potential across the six</span><span> geo-political zones in Nigeria is also presented, which ranges from 3.393 - 6.669 kWh/</span><span>m<sup></sup></span><span><sup>2</sup></span><span>/day, with the Northern zones exhibiting better potentials over the Southern zones. It is shown that the levelised cost of electricity from PV system ranges from 0.387 - 0.475 $/kWh, whereas it is 0.947 US$/kWh and 0.559 US$/kWh for the diesel generator and glass-covered kerosene lamp, respectively. While this study shows that PV for rural household lighting is more affordable as compared to glass-covered kerosene lamps and fossil-fuelled generators for lighting, fiscal and energy policies for market creation are critical if PV systems are to deliver on their promise for rural electrification and climate change mitigation.</span> </div>展开更多
Many U.S.utilities incentivize residential energy reduction through rebates,often in response to state mandates for energy reduction or from a desire to reduce demand to mitigate the need to grow generating assets.The...Many U.S.utilities incentivize residential energy reduction through rebates,often in response to state mandates for energy reduction or from a desire to reduce demand to mitigate the need to grow generating assets.The assumption built into incentive programs is that the least efficient residences will be more likely take advantage of the rebates.This,however,is not always the case.The main goal of this study was to determine the potential for prioritized incentivization,i.e.,prioritizing incentives that deliver the greatest energy savings per invest-ment through an entire community.It uses a data mining approach that leverages known building and energy characteristics for predicting energy consumption of houses that collectively can be considered representative of all residences within an entire community.From this model,it estimates natural gas consumption and savings,and corresponding implementation costs associated with the adoption of the most impactful energy reduction measures.The resulting savings and cost estimates allow us to develop a sequential energy reduction strategy whereby the most economic measures within the whole utility district are addressed.The results show that an energy reduction of 36%can be achieved at a levelized cost of less than$14 per mmBTU($14,780 per MJ),demonstrating the strong potential of this approach.A corresponding Economic Input–Output Analysis captures the cascading community economic impacts of this strategy.The results show that for the roughly 45,000 single-family residences in the studied region,an initial energy efficiency investment of$26M could result in a total cascading multiplier economic impact of$41M and additional economic impacts of$2.2M for the lifetime of the considered energy efficiency measures.展开更多
Distributed photovoltaic(PV)systems have constantly been the key to achieve a low-carbon economy in China.However,the development of Chinese distributed PV systems has failed to meet expectations because of their irra...Distributed photovoltaic(PV)systems have constantly been the key to achieve a low-carbon economy in China.However,the development of Chinese distributed PV systems has failed to meet expectations because of their irrational profit and cost allocations.In this study,the methodology for calculating the levelized cost of energy(LCOE)for PV is thoroughly discussed to address this issue.A mixed-integer linear programming model is built to determine the optimal system operation strategy with a benefit analysis.An externality-corrected mathematical model based on Shapley value is established to allocate the cost of distributed PV systems in 15 Chinese cities between the government,utility grid and residents.Results show that(i)an inverse relationship exists between the LCOEs and solar radiation levels;(ii)the government and residents gain extra benefits from the utility grid through net metering policies,and the utility grid should be the highly subsidized participant;(iii)the percentage of cost assigned to the utility grid and government should increase with the expansion of battery bank to weaken the impact of demand response on increasing theoretical subsidies;and(iv)apart from the LCOE,the local residential electricity prices remarkably impact the subsidy calculation results.展开更多
文摘In this work, a comparative study on emissions and cost implications of diesel <span style="font-family:Verdana;">powered and solar photovoltaic-diesel hybrid systems was carried out for th</span><span style="font-family:Verdana;">ree commercial banks. With the aid of HOMER Pro software, meteorological data, energy demand, system component data, capital and operating costs were used for analysis of the two systems. The results showed that in Bank A, the diesel generator alone releases 111,618 kg/yr of Carbon dioxide while the hybrid system releases 41,618 kg/yr of Carbon dioxide. For Bank B the quantity of carbon dioxide emissions released from the diesel generator in Bank B is 53,830 kg/yr, while the carbon dioxide released from the hybrid energy system is 24,082 kg/yr. For Bank C, the diesel generator alone released 177,799 kg/yr of Carbon dioxide and 129,060 kg/yr of carbon dioxide was released from the hybrid system. This suggests that the diesel generator alone releases more emissions when compared with the hybrid system in all the three banks. The Net present cost of energy and levelized cost of energy were used to find out the cost effectiveness of hybrid systems. The results showed that the levelized cost of energy for the generator alone and hybrid system, respectively in Bank A is $0.713 and $0.343. While for Bank B, it is $0.568 and $0.2553. Finally for Bank C, it was $0.731 and $0.556. Therefore, solar-diesel hybrid system has a comparatively low emission and can be considered as a more economical option for electricity generation.</span>
基金National Natural Science Foundation of China(No.519667013)
文摘In view of the high cost of solar thermal power generation in China,it is difficult to realize large-scale production in engineering and industrialization.Non-dominated sorting genetic algorithm II(NSGA-II)is applied to optimize the levelling cost of energy(LCOE)of the solar thermal power generation system in this paper.Firstly,the capacity and generation cost of the solar thermal power generation system are modeled according to the data of several sets of solar thermal power stations which have been put into production abroad.Secondly,the NSGA-II genetic algorithm and particle swarm algorithm are applied to the optimization of the solar thermal power station LCOE respectively.Finally,for the linear Fresnel solar thermal power system,the simulation experiments are conducted to analyze the effects of different solar energy generation capacities,different heat transfer mediums and loan interest rates on the generation price.The results show that due to the existence of scale effect,the greater the capacity of the power station,the lower the cost of leveling and electricity,and the influence of the types of heat storage medium and the loan on the cost of leveling electricity are relatively high.
文摘There is an increase in annual waste generation due to urbanization,industrialization,and population growth.The waste management crisis in developing countries and its complexity from region to region has inspired extensive research work in this area.Poor management not only results in environmental hazards,but it also causes significant socio-economic losses.Due to the absence of comprehensive studies on waste to energy(WTE)assessment,this study assesses and reports the merits of alternative technologies for converting WTE in small and medium-size districts.Quantitative analysis for waste collection data in this study uses a pilot study approach to provide useful insights and waste classification.A cantonment district of Pakistan(Wah Cantt)has been used as a case study for performing a technological and economic assessment of energy generation through the use of thermal and biological treatment processes.A mathematical modeling approach has been adopted for generating an economic value of each technology through which this waste can be processed.Further,the levelized cost of energy(LCOE)based assessment has been performed to provide a methodological framework for selecting the most feasible WTE technology in a small or medium-size district.Based on the model results,anaerobic digestion appears to be the most sustainable technology due to the organic nature of waste in Wah Cantt,land legislation,and availability of area to install a waste plant.Considering all the waste collected,the district can generate approximately 14.4 MW of energy through thermal treatment,19,110 m^(3) of daily biogas through anaerobic digestion,and 5 million tons of fertilizer through composting.Hence,if a proper supply chain is established for converting a portion of Pakistan’s annual waste generation,a significant amount of waste energy potential can be restored.
文摘<div style="text-align:left;"> Rural households represent, by far, the greater percentage of dwellings globally without access to the electricity supply. For reasons of low loads, distance from the grid and speed of deployment, distributed energy systems are now considered viable options for rural electrification. This paper presents the status of solar Photovoltaic (PV) in Nigeria and discusses the way forward for aggressive PV penetration in Nigeria’s energy mix, especially in rural communities. At present, distributed PV penetration in Nigeria is comparatively low based on the International Energy Association’s recommended PV market potential. This shows that there is a gap between the government’s <span>policy targets and reality. The solar resource potential across the six</span><span> geo-political zones in Nigeria is also presented, which ranges from 3.393 - 6.669 kWh/</span><span>m<sup></sup></span><span><sup>2</sup></span><span>/day, with the Northern zones exhibiting better potentials over the Southern zones. It is shown that the levelised cost of electricity from PV system ranges from 0.387 - 0.475 $/kWh, whereas it is 0.947 US$/kWh and 0.559 US$/kWh for the diesel generator and glass-covered kerosene lamp, respectively. While this study shows that PV for rural household lighting is more affordable as compared to glass-covered kerosene lamps and fossil-fuelled generators for lighting, fiscal and energy policies for market creation are critical if PV systems are to deliver on their promise for rural electrification and climate change mitigation.</span> </div>
文摘Many U.S.utilities incentivize residential energy reduction through rebates,often in response to state mandates for energy reduction or from a desire to reduce demand to mitigate the need to grow generating assets.The assumption built into incentive programs is that the least efficient residences will be more likely take advantage of the rebates.This,however,is not always the case.The main goal of this study was to determine the potential for prioritized incentivization,i.e.,prioritizing incentives that deliver the greatest energy savings per invest-ment through an entire community.It uses a data mining approach that leverages known building and energy characteristics for predicting energy consumption of houses that collectively can be considered representative of all residences within an entire community.From this model,it estimates natural gas consumption and savings,and corresponding implementation costs associated with the adoption of the most impactful energy reduction measures.The resulting savings and cost estimates allow us to develop a sequential energy reduction strategy whereby the most economic measures within the whole utility district are addressed.The results show that an energy reduction of 36%can be achieved at a levelized cost of less than$14 per mmBTU($14,780 per MJ),demonstrating the strong potential of this approach.A corresponding Economic Input–Output Analysis captures the cascading community economic impacts of this strategy.The results show that for the roughly 45,000 single-family residences in the studied region,an initial energy efficiency investment of$26M could result in a total cascading multiplier economic impact of$41M and additional economic impacts of$2.2M for the lifetime of the considered energy efficiency measures.
基金This study was sponsored by the National Key R&D Program of China(Grant No.2018YFD1100202)China Postdoctoral Science Foundation(Grant No.2018M643807XB)and Education Department of Shaanxi(Grant No.19JS041).
文摘Distributed photovoltaic(PV)systems have constantly been the key to achieve a low-carbon economy in China.However,the development of Chinese distributed PV systems has failed to meet expectations because of their irrational profit and cost allocations.In this study,the methodology for calculating the levelized cost of energy(LCOE)for PV is thoroughly discussed to address this issue.A mixed-integer linear programming model is built to determine the optimal system operation strategy with a benefit analysis.An externality-corrected mathematical model based on Shapley value is established to allocate the cost of distributed PV systems in 15 Chinese cities between the government,utility grid and residents.Results show that(i)an inverse relationship exists between the LCOEs and solar radiation levels;(ii)the government and residents gain extra benefits from the utility grid through net metering policies,and the utility grid should be the highly subsidized participant;(iii)the percentage of cost assigned to the utility grid and government should increase with the expansion of battery bank to weaken the impact of demand response on increasing theoretical subsidies;and(iv)apart from the LCOE,the local residential electricity prices remarkably impact the subsidy calculation results.