At present,a life-cycle assessment of energy storage systems(ESSs)is not widely available in the literature.Such an assessment is increasingly vital nowadays as ESS is recognized as one of the important equipment in p...At present,a life-cycle assessment of energy storage systems(ESSs)is not widely available in the literature.Such an assessment is increasingly vital nowadays as ESS is recognized as one of the important equipment in power systems to reduce peak demands for deferring or avoiding augmentation in the network and power generation.As the battery cost is still very high at present,a comprehensive assessment is necessary to determine the optimum ESS capacity so that the maximum financial gain is achievable at the end of the batteries’lifespan.Therefore,an effective life-cycle assessment is proposed in this paper to show how the optimum ESS capacity can be determined such that the maximum net financial gain is achievable at the end of the batteries’lifespan when ESS is used to perform peak demand reductions for the customer or utility companies.The findings reveal the positive financial viability of ESS on the power grid,otherwise the projection of the financial viability is often seemingly poor due to the high battery cost with a short battery lifespan.An improved battery degradation model is used in this assessment,which can simulate the battery degradation accurately in a situation whereby the charging current,discharging current,and temperature of the batteries are intermittent on a site during peak demand reductions.This assessment is crucial to determine the maximum financial benefits brought by ESS.展开更多
Consider the task of tracking the energy use of an entire city while also working to reduce it by 50%in 17 years.How would you go about tracking and verifying such reductions?Further,how would this be accomplished in ...Consider the task of tracking the energy use of an entire city while also working to reduce it by 50%in 17 years.How would you go about tracking and verifying such reductions?Further,how would this be accomplished in a city without a database of building-specific characteristics and no energy reporting law?To begin,let’s consider what this task would look like for one building.Where to start?Let’s try with a performance metric and point of comparison.Just as cars gauge performance by MPG,and pitchers by ERA,buildings can use Energy Use Intensity(EUI)as a performance metric.Measured in Energy/ft2/year,EUI standardizes energy use per square foot,allowing for comparison between many buildings.EUI is a snapshot of building performance over one year’s time.It is relatively easy to calculate a building’s EUI if their energy usage is known,but in order to gauge performance over a longer period,a constant comparison point must be established so that evaluation is consistent.Called the baseline,this comparison point can be established as a past year,a future goal,or the average performance of similar buildings.This paper covers the work of the Pittsburgh 2030 District team in formulating an energy performance baseline for each building in Downtown Pittsburgh for purposes of tracking energy use reduction towards the 50%reduction goals of The 2030 Challenge.Pittsburgh is a city with a large stock of aging buildings,without mandatory benchmarking laws,and no single publicly accessible real estate profile by property.Thus,the energy baseline methods included in this paper summarize efforts to create such an aggregated property characteristic database and associated energy baseline for Downtown Pittsburgh;it is the hope of the authors that these efforts will assist similar cities in mirroring 2030 District goal setting and achievement for building energy.展开更多
文摘At present,a life-cycle assessment of energy storage systems(ESSs)is not widely available in the literature.Such an assessment is increasingly vital nowadays as ESS is recognized as one of the important equipment in power systems to reduce peak demands for deferring or avoiding augmentation in the network and power generation.As the battery cost is still very high at present,a comprehensive assessment is necessary to determine the optimum ESS capacity so that the maximum financial gain is achievable at the end of the batteries’lifespan.Therefore,an effective life-cycle assessment is proposed in this paper to show how the optimum ESS capacity can be determined such that the maximum net financial gain is achievable at the end of the batteries’lifespan when ESS is used to perform peak demand reductions for the customer or utility companies.The findings reveal the positive financial viability of ESS on the power grid,otherwise the projection of the financial viability is often seemingly poor due to the high battery cost with a short battery lifespan.An improved battery degradation model is used in this assessment,which can simulate the battery degradation accurately in a situation whereby the charging current,discharging current,and temperature of the batteries are intermittent on a site during peak demand reductions.This assessment is crucial to determine the maximum financial benefits brought by ESS.
文摘Consider the task of tracking the energy use of an entire city while also working to reduce it by 50%in 17 years.How would you go about tracking and verifying such reductions?Further,how would this be accomplished in a city without a database of building-specific characteristics and no energy reporting law?To begin,let’s consider what this task would look like for one building.Where to start?Let’s try with a performance metric and point of comparison.Just as cars gauge performance by MPG,and pitchers by ERA,buildings can use Energy Use Intensity(EUI)as a performance metric.Measured in Energy/ft2/year,EUI standardizes energy use per square foot,allowing for comparison between many buildings.EUI is a snapshot of building performance over one year’s time.It is relatively easy to calculate a building’s EUI if their energy usage is known,but in order to gauge performance over a longer period,a constant comparison point must be established so that evaluation is consistent.Called the baseline,this comparison point can be established as a past year,a future goal,or the average performance of similar buildings.This paper covers the work of the Pittsburgh 2030 District team in formulating an energy performance baseline for each building in Downtown Pittsburgh for purposes of tracking energy use reduction towards the 50%reduction goals of The 2030 Challenge.Pittsburgh is a city with a large stock of aging buildings,without mandatory benchmarking laws,and no single publicly accessible real estate profile by property.Thus,the energy baseline methods included in this paper summarize efforts to create such an aggregated property characteristic database and associated energy baseline for Downtown Pittsburgh;it is the hope of the authors that these efforts will assist similar cities in mirroring 2030 District goal setting and achievement for building energy.
