Consumers＇ electricity cost keeps increasing over the time in most countries across the world. The main reason is that importing electricity from generation plants far from a load center is relatively expensive, as c...Consumers＇ electricity cost keeps increasing over the time in most countries across the world. The main reason is that importing electricity from generation plants far from a load center is relatively expensive, as costs are paid not only for generation but also for energy loss and network use. To this end, it is more economi- cal to use electricity generated by local distributed generations. In order to reduce customers＇ electricity cost, a new economic dispatch of smart distribution networks is proposed. Economic dispatch of smart distribution network is to meet load demand with the least consumers＇ electricity cost considering distributed generators, while recognizing all operational limits of generation and transmission facilities in a distribution network. Case study shows that consumers＇ electricity cost can be reduced by about 200/o through economic dispatch of distri- bution network. Further, generation cost and emission of distribution network are reduced as well.展开更多
With the sky-rocketing development of Internet services, the power usage in data centers has been signifi- cantly increasing. This ever increasing energy consumption leads to negative environmental impact such as glob...With the sky-rocketing development of Internet services, the power usage in data centers has been signifi- cantly increasing. This ever increasing energy consumption leads to negative environmental impact such as global warming. To reduce their carbon footprints, large Internet service operators begin to utilize green energy. Since green energy is currently more expensive than the traditional brown one, it is important for the operators to maximize the green en- ergy usage subject to their desired long-term （e.g., a month） cost budget constraint. In this paper, we propose an online algorithm GreenBudget based on the Lyapunov optimization framework. We prove that our algorithm is able to achieve a delicate tradeoff between the green energy usage and the en- forcement of the cost budget constraint, and a control parameter V is the knob to arbitrarily tune such a tradeoff. We evaluate GreenBudget utilizing real-life traces of user requests, cooling efficiency, electricity price and green energy avail- ability. Experimental results demonstrate that under the same cost budget constraint, GreenBudget can increase the green energy usage by 11.55% compared with the state-of-the-art work, without incurring any performance violation of user requests.展开更多
Coal has been dominating the electricity supply in Indonesia,especially in long-term power generation from fossil energy.This dominance is due to lower production costs in coal-fired power plant generation.However,thi...Coal has been dominating the electricity supply in Indonesia,especially in long-term power generation from fossil energy.This dominance is due to lower production costs in coal-fired power plant generation.However,this low price is only based on monetary costs and ignores the social costs.Therefore,this study aims to quantify the social costs of coal-fired generation.Using QUERI-AirPacts modeling,the present study quantifies the social costs resulting from the Tenayan Raya coal-fired generation in Riau,Indonesia.It includes the levelized cost of electricity and health costs into the generation costs.After that,this study calculates the net present value,internal rate return,and project payback period.The study found that as much as$50.22/MWh was the levelized cost of electricity.While$15.978/MWh or$0.015978/kWh was the social cost that was not included in the generating cost.At the electricity production level of 1,380,171.69 MWh per year,there is an expected extra cost of$22,052,383.30 uncounted when externalities are included.For instance,the net present value(NPV)is lower and even negative when external costs are included(-$24,062,274.19)compared to$176,108,091.52 when externalities are not considered.The internal rate of return(IRR)is much higher when the social costs are not considered.The payback period is also shorter when the social costs are excluded than when the externalities are included.This global number indicates that the inclusion of external costs would impact NPV,IRR,and the payback period.This result implies that the government should internalize the external cost to stimulate the electricity producers to conduct cost-benefit analyses.The cost-benefit analysis mechanism would lead the producers to be more efficient.展开更多
In this paper, we present a novel cloud-based demand side management (DSM) optimization approach for the cost reduction of energy usage in heating, ventilation and air conditioning (HVAC) systems in residential homes ...In this paper, we present a novel cloud-based demand side management (DSM) optimization approach for the cost reduction of energy usage in heating, ventilation and air conditioning (HVAC) systems in residential homes at the district level. The proposed approach achieves optimization through scheduling of HVAC energy usage within permissible bounds set by house users. House smart home energy management (SHEM) devices are connected to the utility/aggregator via a dedicated communication network that is used to enable DSM. Each house SHEM can predict its own HVAC energy usage for the next 24 h using minimalistic deep learning (DL) prediction models. These predictions are communicated to the aggregator, which will then do day ahead optimizations using the proposed game theory (GT) algorithm. The GT model captures the interaction between aggregator and customers and identifies a solution to the GT problem that translates into HVAC energy peak shifting and peak reduction achieved by rescheduling HVAC energy usage. The found solution is communicated by the aggregator to houses SHEM devices in the form of offers via DSM signals. If customers’ SHEM devices accept the offer, then energy cost reduction will be achieved. To validate the proposed algorithm, we conduct extensive simulations with a custom simulation tool based on GridLab-D tool, which is integrated with DL prediction models and optimization libraries. Results show that HVAC energy cost can be reduced by up to 36% while indirectly also reducing the peak-to-average (PAR) and the aggregated net load by up to 9.97%.展开更多
The South African gold mining sector remains a significant contributor to the country’s economy.Facing several challenges that hinder the realisation of South Africa’s full mineral potential,the sector’s sustainabi...The South African gold mining sector remains a significant contributor to the country’s economy.Facing several challenges that hinder the realisation of South Africa’s full mineral potential,the sector’s sustainability and profitability can be enhanced through implementing operational improvement measures.Mobile cooling units(MCUs)were identified as a potential focus area for operational improvement.MCUs are used as tertiary or in-stope cooling in hot underground workings.In this paper,a method was presented to characterise the performance of existing MCUs based on three key performance indicators(KPIs),namely,the wet-bulb temperature ratio(WTR),efficiency and position.Optimisation strategies were then elected and implemented based on these KPIs.The implementation of this method in a South African gold mine attained a reduction in pumped water volumes,reduced operating costs through electricity cost savings and improvements in underground ventilation air temperatures.展开更多
North African countries generally have strategic demands for energy transformation and sustainable development.Renewable energy development is important to achieve this goal.Considering three typical types of renewabl...North African countries generally have strategic demands for energy transformation and sustainable development.Renewable energy development is important to achieve this goal.Considering three typical types of renewable energies—wind,photovoltaic(PV),and concentrating solar power(CSP)—an optimal planning model is established to minimize construction costs and power curtailment losses.The levelized cost of electricity is used as an index for assessing economic feasibility.In this study,wind and PV,wind/PV/CSP,and transnational interconnection modes are designed for Morocco,Egypt,and Tunisia.The installed capacities of renewable energy power generation are planned through the time sequence production simulation method for each country.The results show that renewable energy combined with power generation,including the CSP mode,can improve reliability of the power supply and reduce the power curtailment rate.The transnational interconnection mode can help realize mutual benefits of renewable energy power,while the apportionment of electricity prices and trading mechanisms are very important and are related to economic feasibility;thus,this mode is important for the future development of renewable energy in North Africa.展开更多
This paper outlines the barriers and potential benefits of using standby diesel generators in mitigating the peak demands for commercial and industrial customers. The feasibility of utilizing the standby diesel genera...This paper outlines the barriers and potential benefits of using standby diesel generators in mitigating the peak demands for commercial and industrial customers. The feasibility of utilizing the standby diesel generators to reduce the electricity bills for customers is carried out by using the hybrid optimization model for electric renewable(HOMER)software. The size of the standby diesel generator and its operational duration are determined based on the lowest cost of electricity obtained from the evaluations. The economic assessments demonstrate that there is potential to reduce the electricity bills for commercial and industrial customers under the existing fuel price and tariffs. The commercial customers under the tariff C2 have the highest potential to save their electricity bills with the use of standby diesel generators for peak reduction. This study demonstrates the potential of the standby diesel generators in peak reduction.展开更多
In order to make power price truly reflect the cost of electric power and a reasonable profit without making the price unaffordable to the public, the government would have to adopt measures including tax reduction, s...In order to make power price truly reflect the cost of electric power and a reasonable profit without making the price unaffordable to the public, the government would have to adopt measures including tax reduction, surcharge reduction, debt relief and coal price reduction.展开更多
1-year hourly wind speed data from two Burundian stations, namely Bujumbura and Muyinga, have been processed in this work to bring an efficient help for the planning and installation of wind energy conversion systems ...1-year hourly wind speed data from two Burundian stations, namely Bujumbura and Muyinga, have been processed in this work to bring an efficient help for the planning and installation of wind energy conversion systems (WECS) at those localities. Mean seasonal and diurnal variations of wind direction and wind shear exponent have been derived. Two-parameter Weibull probability density functions (PDFs) fitting the observed monthly and annual wind speed relative frequency distributions have been implemented. As shown through three complementary statistical tests, the fitting technique was very satisfactory. A wind resource analysis at 10 m above ground level (AGL) has led to a mean power density at Bujumbura which is almost thirteen fold higher than at Muyinga. The use of the empirical power law to extrapolate wind characteristics at heights from 150 to 350 m AGL has shown that energy potential of hilltops around Muyinga was only suitable for small, individual scale wind energy applications. At the opposite, wind energy potential of ridge-tops and hilltops around Bujumbura has been found suitable for medium and large scale electricity production. For that locality and at those heights, energy outputs and capacity factors (CF or C<sub>f</sub>) have been computed for ten selected wind turbines (WTs), together with costs of electricity (COE) using the present value of cost (PVC) method. Amongst those WTs, YDF-1500-87 and S95-2.1 MW have emerged as the best options for installation owing to their highest CF and lowest COE. Moreover, an analysis of those two quantities at monthly basis for YDF-1500-87 WT has led to its best performance in the dry season. Compared to the average present COE of household hydroelectricity consumption, results of this study have evidenced economical feasibility and benefit of WECS setting in selected Burundian sites in order to supplement traditional electricity sources.展开更多
The main objective of this paper is to select the optimal model of a hybrid renewable-energy microgrid(MG)system for a village in India.The MG comprises solar photovoltaic(PV)modules,a wind turbine generator,a biomass...The main objective of this paper is to select the optimal model of a hybrid renewable-energy microgrid(MG)system for a village in India.The MG comprises solar photovoltaic(PV)modules,a wind turbine generator,a biomass generator,a battery bank,a diesel generator and an electric vehicle.The optimal model selection is based on technical,economic,environmental,social and reliability parameters.A novel spoonbill swarm optimization algorithm is proposed to select the best hybrid MG system.The optimization results are compared with particle swarm optimization,the genetic algorithm and the grasshopper optimization algorithm.The number or size of components of the optimized MG system is 215 PV modules,92 kW of wind turbine generation,25 kW of biomass generation,267 batteries,22 kW of electric vehicles and 30 kW of diesel generation.The optimized system was selected based on technical factors such as renewable dispersion(93.5%),the duty factor(5.85)and excess energy(15975 kWh/year)as well as eco-nomic considerations including the net present cost(Rs.34686622)and the cost of energy(9.3 Rs./kWh).Furthermore,environ-mental factors such as carbon emissions(396348 kg/year)and atmospheric particulate matter(22.686 kg/year);social factors such as the human progress index(0.68411),the employment generation factor(0.0389)and local employment generation(15.64643);and reliability parameters including loss of power supply probability(0.01%)and availability index(99.99%)were considered during the selection process.The spoonbill swarm optimization algorithm has reduced the convergence time by 1.2 times and decreased the number of iterations by 0.83 times compared with other algorithms.The performance of the MG system is validated in the MATLAB®environment.The results show that the MG system is the optimal system considering technical,economic,environmental,social and reliability parameters.Additionally,the spoonbill swarm optimization algorithm is found to be more efficient than the other algo-rithms in terms of iteration time and convergence time.展开更多
Perovskite solar cells(PSCs)have shown remarkable advancements and achieved impressive power conversion efficiencies since their initial introduction in 2012.However,challenges regarding stability,quality,and sustaina...Perovskite solar cells(PSCs)have shown remarkable advancements and achieved impressive power conversion efficiencies since their initial introduction in 2012.However,challenges regarding stability,quality,and sustainability must be addressed for their successful commercial use.This review analyses the recent studies and challenges related to the operating life and end-of-life utilization of PSCs.Strategies to enhance the stability and mitigate the toxic Pb leakage in operational and recycling approaches of discarded PSCs post their end-of-life are examined to establish a viable and sustainable PSC industry.Additionally,future research directions are proposed for the advancements in the PSC industry.The goal is to ensure high efficiency as well as economic and environmental sustainability throughout the lifecycle of PSCs.展开更多
To optimally control the energy storage system of the battery exposed to the volatile daily cycling load and electricity tariffs,a novel modification of a conventional model predictive control is proposed.The uncertai...To optimally control the energy storage system of the battery exposed to the volatile daily cycling load and electricity tariffs,a novel modification of a conventional model predictive control is proposed.The uncertainty of daily cycling load prompts the need to design a new cost function which is able to quantify the associated uncertainty.By modelling a probabilistic dependence among flow,load,and electricity tariffs,the expected cost function is obtained and used in the constrained optimization.The proposed control strategy explicitly incorporates the cycling nature of customer load.Furthermore,for daily cycling load,a fixed-end time and a fixed-end output problem are addressed.It is demonstrated that the proposed control strategy is a convex optimization problem.While stochastic and robust model predictive controllers evaluate the cost concerning model constraints and parameter variations.Also,the expected cost across the flow variations is considered.The density function of load probability improves load prediction over a progressive prediction horizon,and a nonlinear battery model is utilized.展开更多
With the development of smart meters,a realtime pricing(RTP)demand response is becoming possible for households in distribution networks.The power flow can be bidirectional in distribution networks which become smarte...With the development of smart meters,a realtime pricing(RTP)demand response is becoming possible for households in distribution networks.The power flow can be bidirectional in distribution networks which become smarter with distributed generators(DGs).It is expensive to import electricity from the generation far from load centers because of the cost of power loss and network use,so that it is more economical to use electricity generated by local distributed generators.Therefore,in order to curtail operating costs of distribution networks,this paper proposes a model of economic optimization conducted by distribution network operators.The electricity purchasing costs for distribution network operators are minimized by optimizing electric power from transmission systems and local distributed generators.Further,based on price elasticity,the formulations of load demand considering RTP are proposed with economic optimization of distribution networks.The economic optimization problems are resolved by an interior point method.The case study shows that peak load demand can be reduced about 3.5%because the household RTP and electricity purchasing costs of distribution network operators can save 28.86£every hour.展开更多
Concentrating solar power(CSP)technology has received increasing attention in recent years because of its distinct advantage for dispatchable power generation from solar energy.However,owing to its highly levelized co...Concentrating solar power(CSP)technology has received increasing attention in recent years because of its distinct advantage for dispatchable power generation from solar energy.However,owing to its highly levelized costs of electricity,CSP plants are less competitive than photovoltaic(PV)power plants.To overcome this drawback and suppress PV power fluctuations,the concept of a hybrid CSP/PV power plant is proposed and developed.A capacity configuration method based on filtering and checking is proposed to seek a relationship between the capacity configuration of a hybrid CSP/PV system and the cost of solar energy.Co-content hybrid systems with different ratios of CSP capacity and PV capacity are modeled,and their comprehensive performance is investigated.Simulations and comparisons with a standalone CSP system focused on annual energy generation,capacity factor,levelized cost of electricity,and possibility for loss of power supply show that the hybrid CSP/PV systems possess different features depending on their capacity configurations.The results indicate that the proposed method can supply a convenient and simple operation pattern that favors engineering utilization and extension.展开更多
In this study,energetic,economic,and environmental analysis of solid oxide fuel cell-based combined cooling,heating,and power(SOFC-CCHP)system is proposed for a cancer care hospital building.The energy required for th...In this study,energetic,economic,and environmental analysis of solid oxide fuel cell-based combined cooling,heating,and power(SOFC-CCHP)system is proposed for a cancer care hospital building.The energy required for the hospital power,cooling,and heating demands was obtained based on real and detailed field data,which could serve as a reference for future works in the field.These data with a 3D model for the hospital building are constructed and created in eQUEST software to precisely calculate the energy demands of the existing system(baseline case).Then,energetic,economic,and environmental models were developed to compare and assess the performance of the proposed SOFC-CCHP system.The results show that the proposed system can cover about 49% to 77% of the power demand of the hospital with an overall efficiency of 78.3%.Also,the results show that the levelized cost of electricity of the system and its payback period at the designed capacity of the SOFC is 0.087S/kWh and 10 years,respectively.Furthermore,compared to the baseline system of the hospital,the SOFC-CCHP reduces the CO_(2) emission by 89% over the year.The sensitivity analysis showed that a maximum SOFC efficiency of 52%and overall efficiency of 80%are achieved at cell operating temperature of 1027℃ and fuel utilization factor of 0.85.展开更多
During the past few years,Egypt has increased the share of electricity generation from renewable energy sources to achieve the renewable-energy strategy.The Egyptian Ministry of Electricity and Renewable Energy has se...During the past few years,Egypt has increased the share of electricity generation from renewable energy sources to achieve the renewable-energy strategy.The Egyptian Ministry of Electricity and Renewable Energy has set an ambitious target to increase the share of renewable energy among the total energy mix to be 20%by 2022 and 42%by 2035.This target will be achieved using several approved policies such as feed-in tariffs,build-own-operate and independent power producers under a merchant scheme.This paper presents a full analysis of wind-potential characteristics at Elkharga Oasis in Egypt based on an actual wind-measurement campaign taken by a met mast at two height levels of 10 and 25 m,respectively.The measurements show an average annual wind speed of 5.72 m/s at 10-m height and 6.53 m/s at>25-m height.The estimated wind speed,however,is 8.38 m/s at 120 m,which is technically convenient to generate electricity from wind energy.In this paper,the wind potential in the area is assessed using the statistical method of the Weibull probability density function.The different methods to estimate the Weibull distribution parameters are presented and the relevant accuracy is verified based on the root mean square error.A techno-economic assessment and selection of the optimal wind-turbine size with ideal micro-sitings are performed using the software package windPRO.Different cases of study for three typical wind-turbine models with various rotor diameters,power capacity,layout configuration and annual yield are assessed at the site.The selection of the most convenient wind turbine is determined based on the IEC 61400 standard criteria and the turbine that produces the lowest levelized cost of electricity.展开更多
To solve the problem energy deficit encountered in developing countries,Hybrid Renewable Energy System(HRES)appears to be a very good solution.The paper presents the optimal design of a hybrid renewable energy system ...To solve the problem energy deficit encountered in developing countries,Hybrid Renewable Energy System(HRES)appears to be a very good solution.The paper presents the optimal design of a hybrid renewable energy system considering the technical i.e Loss of Power Supply Probability(LPSP),economic i.e Cost of Electricity(COE)and Net Present Cost(NPC)and environmental i.e Total Greenhouse gases emission(TGE)aspects using Particle Swarm Optimization(PSO),hybrid Particle Swarm Optimization-Grey Wolf Optimization(PSOGWO),hybrid Grey-Wolf Optimization-Cuckoo Search(GWOCS)and Sine-Cosine Algorithm(SCA)for a Community multimedia center in MAKENENE,Cameroon;where inhabitants have to spend at times 3 to 4 days of blackout.Seven configurations(Scenarios)of hybrid energy systems including PV,WT,Battery and Diesel generator are analyzed considering an average daily energy load of 50.22 kWh with a peak load of 5.6 kW.Four values of the derating factor i.e 0.6,0.7,0.8 and 0.9 are used in this analysis and the best value is 0.9.Scenario 3 with LPSP,COE,NPC,TGE and RF of 0.003%,0.15913$/kWh,46953.0485$,2.3406 kg/year and 99.8%respectively when using GWOCS is found to be the most appropriate for the Community multimedia center.The optimal Scenario is obtained for a system comprising of 18 kW of P_(pv-rated)corresponding to 69 solar panels,3 days of AD corresponding to a total battery capacity of 241 kWh and 1 of N_(dg).展开更多
Edge data centers(EDCs)have been widely developed recently to supply delay-sensitive computing services,which impose prohibitively increasing electricity costs for EDC operators.This paper presents a new spatiotempora...Edge data centers(EDCs)have been widely developed recently to supply delay-sensitive computing services,which impose prohibitively increasing electricity costs for EDC operators.This paper presents a new spatiotemporal reallocation(STR)method for energy management in EDCs.This method uses spare resources,including servers and energy storage systems(ESSs)within EDCs to reduce energy costs based on both spatial and temporal features of spare resources.This solution:1)reallocates flexible workload between EDCs within one cluster;and 2)coordinates the electricity load of data processing,ESSs and distributed energy resources(DERs)within one EDC cluster to gain benefits from flexible electricity tariffs.In addition,this paper for the first time develops a Bit-Watt transformation to simplify the STR method and represent the relationship between data workload and electricity consumption of EDCs.Case studies justifying the developed STR method delivers satisfying cost reductions with robustness.The STR method fully utilized both spatial and temporal features of spare resources in EDCs to gain benefits from 1)varying electricity tariffs,and 2)maximumly consuming DER generation.展开更多
基金supported in part by The National High Technology Research and Development of China 863 Program(2012AA050201)
文摘Consumers＇ electricity cost keeps increasing over the time in most countries across the world. The main reason is that importing electricity from generation plants far from a load center is relatively expensive, as costs are paid not only for generation but also for energy loss and network use. To this end, it is more economi- cal to use electricity generated by local distributed generations. In order to reduce customers＇ electricity cost, a new economic dispatch of smart distribution networks is proposed. Economic dispatch of smart distribution network is to meet load demand with the least consumers＇ electricity cost considering distributed generators, while recognizing all operational limits of generation and transmission facilities in a distribution network. Case study shows that consumers＇ electricity cost can be reduced by about 200/o through economic dispatch of distri- bution network. Further, generation cost and emission of distribution network are reduced as well.
文摘With the sky-rocketing development of Internet services, the power usage in data centers has been signifi- cantly increasing. This ever increasing energy consumption leads to negative environmental impact such as global warming. To reduce their carbon footprints, large Internet service operators begin to utilize green energy. Since green energy is currently more expensive than the traditional brown one, it is important for the operators to maximize the green en- ergy usage subject to their desired long-term （e.g., a month） cost budget constraint. In this paper, we propose an online algorithm GreenBudget based on the Lyapunov optimization framework. We prove that our algorithm is able to achieve a delicate tradeoff between the green energy usage and the en- forcement of the cost budget constraint, and a control parameter V is the knob to arbitrarily tune such a tradeoff. We evaluate GreenBudget utilizing real-life traces of user requests, cooling efficiency, electricity price and green energy avail- ability. Experimental results demonstrate that under the same cost budget constraint, GreenBudget can increase the green energy usage by 11.55% compared with the state-of-the-art work, without incurring any performance violation of user requests.
文摘Coal has been dominating the electricity supply in Indonesia,especially in long-term power generation from fossil energy.This dominance is due to lower production costs in coal-fired power plant generation.However,this low price is only based on monetary costs and ignores the social costs.Therefore,this study aims to quantify the social costs of coal-fired generation.Using QUERI-AirPacts modeling,the present study quantifies the social costs resulting from the Tenayan Raya coal-fired generation in Riau,Indonesia.It includes the levelized cost of electricity and health costs into the generation costs.After that,this study calculates the net present value,internal rate return,and project payback period.The study found that as much as$50.22/MWh was the levelized cost of electricity.While$15.978/MWh or$0.015978/kWh was the social cost that was not included in the generating cost.At the electricity production level of 1,380,171.69 MWh per year,there is an expected extra cost of$22,052,383.30 uncounted when externalities are included.For instance,the net present value(NPV)is lower and even negative when external costs are included(-$24,062,274.19)compared to$176,108,091.52 when externalities are not considered.The internal rate of return(IRR)is much higher when the social costs are not considered.The payback period is also shorter when the social costs are excluded than when the externalities are included.This global number indicates that the inclusion of external costs would impact NPV,IRR,and the payback period.This result implies that the government should internalize the external cost to stimulate the electricity producers to conduct cost-benefit analyses.The cost-benefit analysis mechanism would lead the producers to be more efficient.
基金supported by the National Science Foundation(NSF)grant ECCF 1936494.
文摘In this paper, we present a novel cloud-based demand side management (DSM) optimization approach for the cost reduction of energy usage in heating, ventilation and air conditioning (HVAC) systems in residential homes at the district level. The proposed approach achieves optimization through scheduling of HVAC energy usage within permissible bounds set by house users. House smart home energy management (SHEM) devices are connected to the utility/aggregator via a dedicated communication network that is used to enable DSM. Each house SHEM can predict its own HVAC energy usage for the next 24 h using minimalistic deep learning (DL) prediction models. These predictions are communicated to the aggregator, which will then do day ahead optimizations using the proposed game theory (GT) algorithm. The GT model captures the interaction between aggregator and customers and identifies a solution to the GT problem that translates into HVAC energy peak shifting and peak reduction achieved by rescheduling HVAC energy usage. The found solution is communicated by the aggregator to houses SHEM devices in the form of offers via DSM signals. If customers’ SHEM devices accept the offer, then energy cost reduction will be achieved. To validate the proposed algorithm, we conduct extensive simulations with a custom simulation tool based on GridLab-D tool, which is integrated with DL prediction models and optimization libraries. Results show that HVAC energy cost can be reduced by up to 36% while indirectly also reducing the peak-to-average (PAR) and the aggregated net load by up to 9.97%.
基金This work was sponsored by ETA Operations(Pty)Ltd.
文摘The South African gold mining sector remains a significant contributor to the country’s economy.Facing several challenges that hinder the realisation of South Africa’s full mineral potential,the sector’s sustainability and profitability can be enhanced through implementing operational improvement measures.Mobile cooling units(MCUs)were identified as a potential focus area for operational improvement.MCUs are used as tertiary or in-stope cooling in hot underground workings.In this paper,a method was presented to characterise the performance of existing MCUs based on three key performance indicators(KPIs),namely,the wet-bulb temperature ratio(WTR),efficiency and position.Optimisation strategies were then elected and implemented based on these KPIs.The implementation of this method in a South African gold mine attained a reduction in pumped water volumes,reduced operating costs through electricity cost savings and improvements in underground ventilation air temperatures.
基金Supported by the Science and Technology Foundation of SGCC(Large-scale development and utilization mode of solar energy in North Africa under the condition of transcontinental grid interconnection:NY71-18-004)the Science and Technology Foundation of GEI(Research on Large-scale Solar Energy Development in West-Asia and North-Africa:NYN11201805034)
文摘North African countries generally have strategic demands for energy transformation and sustainable development.Renewable energy development is important to achieve this goal.Considering three typical types of renewable energies—wind,photovoltaic(PV),and concentrating solar power(CSP)—an optimal planning model is established to minimize construction costs and power curtailment losses.The levelized cost of electricity is used as an index for assessing economic feasibility.In this study,wind and PV,wind/PV/CSP,and transnational interconnection modes are designed for Morocco,Egypt,and Tunisia.The installed capacities of renewable energy power generation are planned through the time sequence production simulation method for each country.The results show that renewable energy combined with power generation,including the CSP mode,can improve reliability of the power supply and reduce the power curtailment rate.The transnational interconnection mode can help realize mutual benefits of renewable energy power,while the apportionment of electricity prices and trading mechanisms are very important and are related to economic feasibility;thus,this mode is important for the future development of renewable energy in North Africa.
文摘This paper outlines the barriers and potential benefits of using standby diesel generators in mitigating the peak demands for commercial and industrial customers. The feasibility of utilizing the standby diesel generators to reduce the electricity bills for customers is carried out by using the hybrid optimization model for electric renewable(HOMER)software. The size of the standby diesel generator and its operational duration are determined based on the lowest cost of electricity obtained from the evaluations. The economic assessments demonstrate that there is potential to reduce the electricity bills for commercial and industrial customers under the existing fuel price and tariffs. The commercial customers under the tariff C2 have the highest potential to save their electricity bills with the use of standby diesel generators for peak reduction. This study demonstrates the potential of the standby diesel generators in peak reduction.
文摘In order to make power price truly reflect the cost of electric power and a reasonable profit without making the price unaffordable to the public, the government would have to adopt measures including tax reduction, surcharge reduction, debt relief and coal price reduction.
文摘1-year hourly wind speed data from two Burundian stations, namely Bujumbura and Muyinga, have been processed in this work to bring an efficient help for the planning and installation of wind energy conversion systems (WECS) at those localities. Mean seasonal and diurnal variations of wind direction and wind shear exponent have been derived. Two-parameter Weibull probability density functions (PDFs) fitting the observed monthly and annual wind speed relative frequency distributions have been implemented. As shown through three complementary statistical tests, the fitting technique was very satisfactory. A wind resource analysis at 10 m above ground level (AGL) has led to a mean power density at Bujumbura which is almost thirteen fold higher than at Muyinga. The use of the empirical power law to extrapolate wind characteristics at heights from 150 to 350 m AGL has shown that energy potential of hilltops around Muyinga was only suitable for small, individual scale wind energy applications. At the opposite, wind energy potential of ridge-tops and hilltops around Bujumbura has been found suitable for medium and large scale electricity production. For that locality and at those heights, energy outputs and capacity factors (CF or C<sub>f</sub>) have been computed for ten selected wind turbines (WTs), together with costs of electricity (COE) using the present value of cost (PVC) method. Amongst those WTs, YDF-1500-87 and S95-2.1 MW have emerged as the best options for installation owing to their highest CF and lowest COE. Moreover, an analysis of those two quantities at monthly basis for YDF-1500-87 WT has led to its best performance in the dry season. Compared to the average present COE of household hydroelectricity consumption, results of this study have evidenced economical feasibility and benefit of WECS setting in selected Burundian sites in order to supplement traditional electricity sources.
文摘The main objective of this paper is to select the optimal model of a hybrid renewable-energy microgrid(MG)system for a village in India.The MG comprises solar photovoltaic(PV)modules,a wind turbine generator,a biomass generator,a battery bank,a diesel generator and an electric vehicle.The optimal model selection is based on technical,economic,environmental,social and reliability parameters.A novel spoonbill swarm optimization algorithm is proposed to select the best hybrid MG system.The optimization results are compared with particle swarm optimization,the genetic algorithm and the grasshopper optimization algorithm.The number or size of components of the optimized MG system is 215 PV modules,92 kW of wind turbine generation,25 kW of biomass generation,267 batteries,22 kW of electric vehicles and 30 kW of diesel generation.The optimized system was selected based on technical factors such as renewable dispersion(93.5%),the duty factor(5.85)and excess energy(15975 kWh/year)as well as eco-nomic considerations including the net present cost(Rs.34686622)and the cost of energy(9.3 Rs./kWh).Furthermore,environ-mental factors such as carbon emissions(396348 kg/year)and atmospheric particulate matter(22.686 kg/year);social factors such as the human progress index(0.68411),the employment generation factor(0.0389)and local employment generation(15.64643);and reliability parameters including loss of power supply probability(0.01%)and availability index(99.99%)were considered during the selection process.The spoonbill swarm optimization algorithm has reduced the convergence time by 1.2 times and decreased the number of iterations by 0.83 times compared with other algorithms.The performance of the MG system is validated in the MATLAB®environment.The results show that the MG system is the optimal system considering technical,economic,environmental,social and reliability parameters.Additionally,the spoonbill swarm optimization algorithm is found to be more efficient than the other algo-rithms in terms of iteration time and convergence time.
基金supported by SKKU Excellence in Research Award Research Fund,Sungkyunkwan University,2023.
文摘Perovskite solar cells(PSCs)have shown remarkable advancements and achieved impressive power conversion efficiencies since their initial introduction in 2012.However,challenges regarding stability,quality,and sustainability must be addressed for their successful commercial use.This review analyses the recent studies and challenges related to the operating life and end-of-life utilization of PSCs.Strategies to enhance the stability and mitigate the toxic Pb leakage in operational and recycling approaches of discarded PSCs post their end-of-life are examined to establish a viable and sustainable PSC industry.Additionally,future research directions are proposed for the advancements in the PSC industry.The goal is to ensure high efficiency as well as economic and environmental sustainability throughout the lifecycle of PSCs.
基金This work was supported by Australian Research Council(ARC)Discovery Project(No.160102571).
文摘To optimally control the energy storage system of the battery exposed to the volatile daily cycling load and electricity tariffs,a novel modification of a conventional model predictive control is proposed.The uncertainty of daily cycling load prompts the need to design a new cost function which is able to quantify the associated uncertainty.By modelling a probabilistic dependence among flow,load,and electricity tariffs,the expected cost function is obtained and used in the constrained optimization.The proposed control strategy explicitly incorporates the cycling nature of customer load.Furthermore,for daily cycling load,a fixed-end time and a fixed-end output problem are addressed.It is demonstrated that the proposed control strategy is a convex optimization problem.While stochastic and robust model predictive controllers evaluate the cost concerning model constraints and parameter variations.Also,the expected cost across the flow variations is considered.The density function of load probability improves load prediction over a progressive prediction horizon,and a nonlinear battery model is utilized.
文摘With the development of smart meters,a realtime pricing(RTP)demand response is becoming possible for households in distribution networks.The power flow can be bidirectional in distribution networks which become smarter with distributed generators(DGs).It is expensive to import electricity from the generation far from load centers because of the cost of power loss and network use,so that it is more economical to use electricity generated by local distributed generators.Therefore,in order to curtail operating costs of distribution networks,this paper proposes a model of economic optimization conducted by distribution network operators.The electricity purchasing costs for distribution network operators are minimized by optimizing electric power from transmission systems and local distributed generators.Further,based on price elasticity,the formulations of load demand considering RTP are proposed with economic optimization of distribution networks.The economic optimization problems are resolved by an interior point method.The case study shows that peak load demand can be reduced about 3.5%because the household RTP and electricity purchasing costs of distribution network operators can save 28.86£every hour.
基金Supported by the National Key Research and Development Program(2016YFE0102600)the Key Project of National Natural Science Foundation of China(61733010).
文摘Concentrating solar power(CSP)technology has received increasing attention in recent years because of its distinct advantage for dispatchable power generation from solar energy.However,owing to its highly levelized costs of electricity,CSP plants are less competitive than photovoltaic(PV)power plants.To overcome this drawback and suppress PV power fluctuations,the concept of a hybrid CSP/PV power plant is proposed and developed.A capacity configuration method based on filtering and checking is proposed to seek a relationship between the capacity configuration of a hybrid CSP/PV system and the cost of solar energy.Co-content hybrid systems with different ratios of CSP capacity and PV capacity are modeled,and their comprehensive performance is investigated.Simulations and comparisons with a standalone CSP system focused on annual energy generation,capacity factor,levelized cost of electricity,and possibility for loss of power supply show that the hybrid CSP/PV systems possess different features depending on their capacity configurations.The results indicate that the proposed method can supply a convenient and simple operation pattern that favors engineering utilization and extension.
基金The work presented in this publication was made possible by NPRP-S grant#[11S-1231-170155]from the Qatar National Research Fund(a member of Qatar Foundation)。
文摘In this study,energetic,economic,and environmental analysis of solid oxide fuel cell-based combined cooling,heating,and power(SOFC-CCHP)system is proposed for a cancer care hospital building.The energy required for the hospital power,cooling,and heating demands was obtained based on real and detailed field data,which could serve as a reference for future works in the field.These data with a 3D model for the hospital building are constructed and created in eQUEST software to precisely calculate the energy demands of the existing system(baseline case).Then,energetic,economic,and environmental models were developed to compare and assess the performance of the proposed SOFC-CCHP system.The results show that the proposed system can cover about 49% to 77% of the power demand of the hospital with an overall efficiency of 78.3%.Also,the results show that the levelized cost of electricity of the system and its payback period at the designed capacity of the SOFC is 0.087S/kWh and 10 years,respectively.Furthermore,compared to the baseline system of the hospital,the SOFC-CCHP reduces the CO_(2) emission by 89% over the year.The sensitivity analysis showed that a maximum SOFC efficiency of 52%and overall efficiency of 80%are achieved at cell operating temperature of 1027℃ and fuel utilization factor of 0.85.
文摘During the past few years,Egypt has increased the share of electricity generation from renewable energy sources to achieve the renewable-energy strategy.The Egyptian Ministry of Electricity and Renewable Energy has set an ambitious target to increase the share of renewable energy among the total energy mix to be 20%by 2022 and 42%by 2035.This target will be achieved using several approved policies such as feed-in tariffs,build-own-operate and independent power producers under a merchant scheme.This paper presents a full analysis of wind-potential characteristics at Elkharga Oasis in Egypt based on an actual wind-measurement campaign taken by a met mast at two height levels of 10 and 25 m,respectively.The measurements show an average annual wind speed of 5.72 m/s at 10-m height and 6.53 m/s at>25-m height.The estimated wind speed,however,is 8.38 m/s at 120 m,which is technically convenient to generate electricity from wind energy.In this paper,the wind potential in the area is assessed using the statistical method of the Weibull probability density function.The different methods to estimate the Weibull distribution parameters are presented and the relevant accuracy is verified based on the root mean square error.A techno-economic assessment and selection of the optimal wind-turbine size with ideal micro-sitings are performed using the software package windPRO.Different cases of study for three typical wind-turbine models with various rotor diameters,power capacity,layout configuration and annual yield are assessed at the site.The selection of the most convenient wind turbine is determined based on the IEC 61400 standard criteria and the turbine that produces the lowest levelized cost of electricity.
文摘To solve the problem energy deficit encountered in developing countries,Hybrid Renewable Energy System(HRES)appears to be a very good solution.The paper presents the optimal design of a hybrid renewable energy system considering the technical i.e Loss of Power Supply Probability(LPSP),economic i.e Cost of Electricity(COE)and Net Present Cost(NPC)and environmental i.e Total Greenhouse gases emission(TGE)aspects using Particle Swarm Optimization(PSO),hybrid Particle Swarm Optimization-Grey Wolf Optimization(PSOGWO),hybrid Grey-Wolf Optimization-Cuckoo Search(GWOCS)and Sine-Cosine Algorithm(SCA)for a Community multimedia center in MAKENENE,Cameroon;where inhabitants have to spend at times 3 to 4 days of blackout.Seven configurations(Scenarios)of hybrid energy systems including PV,WT,Battery and Diesel generator are analyzed considering an average daily energy load of 50.22 kWh with a peak load of 5.6 kW.Four values of the derating factor i.e 0.6,0.7,0.8 and 0.9 are used in this analysis and the best value is 0.9.Scenario 3 with LPSP,COE,NPC,TGE and RF of 0.003%,0.15913$/kWh,46953.0485$,2.3406 kg/year and 99.8%respectively when using GWOCS is found to be the most appropriate for the Community multimedia center.The optimal Scenario is obtained for a system comprising of 18 kW of P_(pv-rated)corresponding to 69 solar panels,3 days of AD corresponding to a total battery capacity of 241 kWh and 1 of N_(dg).
文摘Edge data centers(EDCs)have been widely developed recently to supply delay-sensitive computing services,which impose prohibitively increasing electricity costs for EDC operators.This paper presents a new spatiotemporal reallocation(STR)method for energy management in EDCs.This method uses spare resources,including servers and energy storage systems(ESSs)within EDCs to reduce energy costs based on both spatial and temporal features of spare resources.This solution:1)reallocates flexible workload between EDCs within one cluster;and 2)coordinates the electricity load of data processing,ESSs and distributed energy resources(DERs)within one EDC cluster to gain benefits from flexible electricity tariffs.In addition,this paper for the first time develops a Bit-Watt transformation to simplify the STR method and represent the relationship between data workload and electricity consumption of EDCs.Case studies justifying the developed STR method delivers satisfying cost reductions with robustness.The STR method fully utilized both spatial and temporal features of spare resources in EDCs to gain benefits from 1)varying electricity tariffs,and 2)maximumly consuming DER generation.
