Highlights

We developed a novel framework for the optimal planning of urban renewable systems.

Systems’ emissions and economic considerations are included for planning.

Impact of different load profiles on the systems’ life-cycle cost is studied.

Cost-benefit analysis of integrating natural gas with urban renewables is assessed.

The developed approach is applied to a model city (Victoria, Canada).

02摘要

可再生能源的城市電氣化是實現(xiàn)低碳和氣候適應(yīng)性社區(qū)的關(guān)鍵戰(zhàn)略。考慮到不同類型的電力用戶(例如住宅、商業(yè)和工業(yè))，這項工作開發(fā)了一個系統(tǒng)和直截了當?shù)目蚣埽员憷脤嶋H的實時每小時電力負荷，對城市太陽能/風能/生物質(zhì)(/天然氣)系統(tǒng)進行社區(qū)規(guī)模的優(yōu)化規(guī)劃。為了達到這一目標，我們確定了三種電力方案：(i)100%天然氣；(ii)天然氣和可再生能源；(iii)100%可再生能源(例如太陽能/風能/生物量)，并確定了三種能源方案中每一種情況下具有最少NPC的混合系統(tǒng)。我們的結(jié)果表明，向工業(yè)部門提供每千瓦時可再生電力(0.385?/千瓦時)的成本比商業(yè)部門(0.399?/千瓦時)低4%，比居民區(qū)(0.418?/千瓦時)低約5%。住宅系統(tǒng)的更大的電費(COE)主要是由于太陽能光伏組分的電池更大。此外，太陽能/風能/生物質(zhì)發(fā)電廠的COE比等效太陽能/風能發(fā)電系統(tǒng)低三倍。同樣，通過將一臺低排放天然氣(Ng)發(fā)電機集成到太陽能/風能/生物質(zhì)混合工廠中，該系統(tǒng)的COE降低了30%，從而使每年溫室氣體排放量增加了近三個數(shù)量級。為了解決與輸入變量相關(guān)的不確定性和變化的模型精度問題，我們進一步對系統(tǒng)的COE地址進行了靈敏度分析，通過對光伏電池板和電池的折現(xiàn)率和資本成本的變化，對不確定度和與輸入變量相關(guān)的變化進行了模型精度分析。因此，系統(tǒng)的COE被檢測到比太陽能電池板對電池的資本成本更敏感。這項研究可以幫助決策者制定更有效的政策和機制，以支持城市混合可再生能源系統(tǒng)。

03

Abstract

Urban electrification with renewables is a crucial strategy for achieving low-carbon and climate-resilient communities. Given the different types of power customers (e.g., residential, commercial and industrial), this work develops a systematic and straightforward framework for the optimal planning of urban solar/wind/biomass (/natural gas) systems at neighbourhood scale using the actual real-time hourly electric loads. In achieving this objective, we defined three power scenarios (i) 100% natural gas; (ii) natural gas and renewables; (iii) 100% renewables (e.g., solar/wind/biomass) and identified the hybrid systems with the least NPC for each of the three power scenarios. Our results indicate that providing per kilowatt-hour renewable electricity to the industrial sector (0.385?USD/kWh) costs 4% less than the commercial (0.399?USD/kWh) and about 5% less than the residential sector (0.418?USD/kWh) at neighbourhood scales. The more significant cost of electricity (COE) of the residential system is primarily due to the greater batteries to solar PV fractions. Also, COE of solar/wind/biomass plant showed to be three times less than the equivalent solar/wind power system. Likewise, by integrating a low-emission natural gas (NG) generator to the hybrid solar/wind/biomass plant, the system's COE reduced by 30% while resulting in close to three order-of-magnitude higher annual greenhouse gas (GHG) emissions. To address the model accuracy concerning the uncertainty and variations associated with input variables, we further conducted the sensitivity analysis of the systems' COE address the model accuracy concerning the uncertainty and variations associated with input variables by changes in the discount rate and capital cost of the PV panels and batteries. As a result, systems’ COE was detected to be more sensitive to the capital cost of batteries than solar panels. This study can help decision-makers in developing more effective policies and mechanisms to support the urban hybrid renewable energy systems.

Keywords：

Urban electrification

Hybrid renewable power system

Load patterns

Neighborhood scales

City of Victoria

Fig. 1. A schematic plot of the three proposed power scenarios (a) 100% natural gas, (b) natural gas and renewables (c) 100% renewables.

Fig. 2. Daily radiation and clearness index profile (a), wind speed (b) profiles for Victoria.

Fig. 7. Sectoral cost breakdown by (a) types (b) components of 100% renewables (scenario iii).