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Bauprojekte sind in der Regel komplexe Vorhaben. Sie werden mit Hilfe des Projektmanagements und dessen Verfahren, Prozessen und Techniken bewältigt. Dennoch sind deutsche Bauprojekte nicht selten von Kosten- und Terminüberschreitungen betroffen. Ziel dieser Arbeit ist es, mögliche Optimierungsfelder im Planungs- und Steuerungsprozess eines Unternehmens für Industriebauprojekte zu identifizieren und darauf aufbauende Verbesserungsansätze zu erarbeiten. Um die Ziele verfolgen zu können, wurde eine qualitative Sozialforschung mittels Experteninterviews durchgeführt. Die Expertenaussagen verdeutlichen weiterhin Optimierungspotenzial, sowohl im Planungs- als auch im Steuerungsprozess. Ausgewählte Techniken (hauptsächlich aus dem klassischen Projektmanagement) dienen indessen dazu, die Effektivität und Effizienz des Planungsprozesses zu erhöhen. Innerhalb des Steuerungsprozesses zeigt sich, dass viele Optimierungsbereiche der Steuerung auf den Defiziten der Planung beruhen.
Driven by decreasing PV and energy storage prices, increasing electricity costs and policy supports from Thai government (self-consumption era), rooftop PV and energy storage systems are going to be deployed in the country rapidly that may disrupt existing business models structure of Thai distribution utilities due to revenue erosion and lost earnings opportunities. The retail rates that directly affect ratepayers (non-solar customers) are expected to increase. This paper focuses on a framework for evaluating impacts of PV with and without energy storage systems on Thai distribution utilities and ratepayers by using cost-benefit analysis (CBA). Prior to calculation of cost/benefit components, changes in energy sales need to be addressed. Government policies for the support of PV generation will also help in accelerating the rooftop PV installation. Benefit components include avoided costs due to transmission losses and deferring distribution capacity with appropriate PV penetration level, while cost components consist of losses in revenue, program costs, integration costs and unrecovered fixed costs. It is necessary for Thailand to compare total costs and total benefits of rooftop PV and energy storage systems in order to adopt policy supports and mitigation approaches, such as business model innovation and regulatory reform, effectively.
Driven by falling photovoltaic (PV) installation costs and potential support policies, rooftop PV is expected to expand rapidly in Thailand. As a result, the relevant stakeholders, especially utilities, have concerns about the net economic impacts of high PV adoption. Using a cost–benefit analysis, this study quantifies the net economic impacts of rooftop PV systems on three utilities and on ratepayers in Thailand by applying nine different PV adoption scenarios with various buyback rates and annual percentages of PV cost reduction. Under Thailand’s current electricity tariff structure, Thai utilities are well-protected and able to pass all costs due to PV onto the ratepayers in terms of changes in retail rates. We find that when PV adoption is low, the net economic impacts on both the utilities and retail rates are small and the impacts on each utility depend on its specific characteristics. On the other hand, when PV adoption ranges from 9–14% in energy basis, five-year retail rate impacts become noticeable and are between 6% and 11% as compared to the projected retail rates in 2036 depending on the PV adoption level. Thus, it is necessary for Thailand to make tradeoffs among the stakeholders and maximize the benefits of rooftop PV adoption.
In the last decades, there has been a widespread implementation of Green Infrastructures worldwide. Among these, green roofs appear to be particularly flexible sustainable drainage facilities. To predict their effectiveness for planning purposes, a tool is required that provides information as a function of local meteorological variables. Thus, a relatively simple daily scale, one-dimensional water balance approach has been proposed. The crucial evapotranspiration process, usually considered as a water balance dependent variable, is replaced here by empirical relationships providing an a-priori assessment of soil water losses through actual evapotranspiration. The modelling scheme, which under some simplification can be used without a calibration process, has been applied to experimental runoff data monitored at a green roof located near Bernkastel (Germany), between April 2005 and December 2006. Two different empirical relationships have been used to model actual evapotranspiration, considering a water availability limited and an energy limited scheme. Model errors quantification, ranging from 2% to 40% on the long-term scale and from 1% to 36% at the event scale, appear strongly related to the particularly considered relationship.
