Onsite Solar Generation Research Articles

도심 수목이 분산형 주거 태양광에너지 잠재량에 미치는 영향

본 연구는 미국 샌프란시스코시 수목 음영이 개별 건물 지붕 및 옥상에 입사되는 태양에너지 잠재량에 미치는 영향을 LiDAR를 이용한 고해상도 3차원 수치모델을 이용하여 공간적으로 정량화하였다. 최근 분산형 태양광 발전이 기후변화 대응에 중요한 부분으로 주목받고 있으나, 이러한 도심 태양광 발전은 주변부의 지형, 건물, 지붕모양, 수목 등의 음영에 의해 발전량이 제한되는 특성이 있다. 특히 건물 주변의 수목의 경우 도시열섬현상의 저감, 냉난방 에너지 수요량의 절감 등의 순기능과 태양광 발전량 감소의 역기능을 동시에 가지고 있어 두 가지 효용의 상충을 최소화하기 위해 해당 위치에 대한 공간적 분석이 요구된다. 샌프란시스코시 전체 건물 지붕면적의 태양에너지 총량은 년간 18,326,671 MWh으로, 수목의 음영에 의한 감소량은 326,406 MWh로 총량의 1.78%에 해당하였다. 건물지붕의 단위 면적당 일조량은 <TEX>$34.4kWh/m^2/year$</TEX>에서 <TEX>$1,348.4kWh/m^2/year$</TEX> 범위로 산출되었다. 본 연구를 통해 도심 수목에 의한 건물별 일조에너지 감소량의 공간자료가 구축되었으며, 개별 건물지붕에 일조량의 변이를 주변 수목의 밀도, 평균수고, 수고의 분산값을 이용한 회귀모델을 통해 설명하였다. 본 연구는 도심수목의 환경적 순기능을 유지함과 동시에 태양광 발전 감소량의 최소화 할 수 있는 방법을 제공함으로써 지속가능한 도시를 구축하는데 기여할 것으로 기대된다. This study spatially assesses the impact of trees on residential rooftop solar energy potential using urban three-dimensional models derived from Light Detection and Ranging(LiDAR) data in San Francisco, California. In recent years on-site solar energy generation in cities has become an essential agenda in municipal climate action plans. However, it can be limited by neighboring environments such as shade from topography, buildings and trees. Of all these effects, the impact of trees on rooftop photovoltaics(PVs) requires careful attention because improper situation of solar panels without considering trees can result in inefficient solar energy generation, tree removal, and/or increasing building energy demand and urban heat island effect. Using ArcMap 9.3.1, we calculated the incoming annual solar radiation on individual rooftops in San Francisco and the reduced insolation affected by trees. Furthermore, we performed a multiple regression analysis to see what attributes of trees in a neighborhood(tree density, tree heights, and the variance of tree heights) affect rooftop insolation. The result shows that annual total residential rooftops insolation in San Francisco is 18,326,671 MWh and annual total light-loss reduction caused by trees is 326,406 MWh, which is about 1.78%. The annual insolation shows a wide range of values from <TEX>$34.4kWh/m^2/year$</TEX> to <TEX>$1,348.4kWh/m^2/year$</TEX>. The result spatially maps the locations that show the various levels of impact from trees. The result from multiple regression shows that tree density, average tree heights and the variation of tree heights in a neighborhood have statistically significant effects on the rooftop solar potential. The results can be linked to municipal energy planning in order to manage potential conflicts as cities with low to medium population density begin implementing on-site solar energy generation. Rooftop solar energy generation makes the best contribution towards achieving sustainability when PVs are optimally located while pursuing the preservation of urban trees.

Impact of onsite solar generation on system load demand forecast

Net energy metering tariffs have encouraged the growth of solar PV in the distribution grid. The additional variability associated with weather-dependent renewable energy creates new challenges for power system operators that must maintain and operate ancillary services to balance the grid. To deal with these issues power operators mostly rely on demand load forecasts. Electric load forecast has been used in power industry for a long time and there are several well established load forecasting models. But the performance of these models for future scenario of high renewable energy penetration is unclear. In this work, the impact of onsite solar power generation on the demand load forecast is analyzed for a community that meets between 10% and 15% of its annual power demand and 3–54% of its daily power demand from a solar power plant. Short-Term Load Forecasts (STLF) using persistence, machine learning and regression-based forecasting models are presented for two cases: (1) high solar penetration and (2) no penetration. Results show that for 1-h and 15-min forecasts the accuracy of the models drops by 9% and 3% with high solar penetration. Statistical analysis of the forecast errors demonstrate that the error distribution is best characterized as a t-distribution for the high penetration scenario. Analysis of the error distribution as a function of daily solar penetration for different levels of variability revealed that the solar power variability drives the forecast error magnitude whereas increasing penetration level has a much smaller contribution. This work concludes that the demand forecast error distribution for a community with an onsite solar generation can be directly characterized based on the local solar irradiance variability.

Research and Solutions: Different Campuses, One Goal: Onsite Solar Generation

Sustainability: The Journal of RecordVol. 3, No. 1 Research and Solutions: Different Campuses, One Goal: Onsite Solar GenerationDavid OxtobyDavid OxtobySearch for more papers by this authorPublished Online:9 Mar 2010https://doi.org/10.1089/SUS.2009.9801AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail FiguresReferencesRelatedDetails Volume 3Issue 1Feb 2010 Information©2010 by Mary Ann Liebert, Inc.To cite this article:David Oxtoby.Research and Solutions: Different Campuses, One Goal: Onsite Solar Generation.Sustainability.Feb 2010.53-56.http://doi.org/10.1089/SUS.2009.9801Published in Volume: 3 Issue 1: March 9, 2010PDF download

A foggy notion [solar photovoltaic power system

When completed, the Bavarian Solarpark will count as one of the largest photovoltaic power plants in the world. With 57,600 solar panels covering a total of 25 hectares of farmland, the 10-megawatt peak station actually consists of three collector installations located within a 50 km radius. While the plant is expected to partially replace Germany's nuclear and fossil fuel power plants with homegrown solar PV plants, the losses due to transmission of central station solar power negate the benefits enjoyed by users of on-site solar generation. The ultimate goal, however, is to foster the growth of a global PV industry and to count on economies of scale to bring the price of PV down to levels that even developing countries can afford.

A foggy notion [solar photovoltaic power system

When completed, the Bavarian Solarpark will count as one of the largest photovoltaic power plants in the world. With 57,600 solar panels covering a total of 25 hectares of farmland, the 10-megawatt peak station actually consists of three collector installations located within a 50 km radius. While the plant is expected to partially replace Germany's nuclear and fossil fuel power plants with homegrown solar PV plants, the losses due to transmission of central station solar power negate the benefits enjoyed by users of on-site solar generation. The ultimate goal, however, is to foster the growth of a global PV industry and to count on economies of scale to bring the price of PV down to levels that even developing countries can afford.