Forecasting electricity demand using generalized long memory

This paper studies the electricity hourly load demand in the area covered by a utility situated in the southeast of Brazil. We propose a stochastic model which employs generalized long memory (by means of Gegenbauer processes) to model the seasonal behavior of the load. The model is proposed for sectional data, that is, each hour’s load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is compared with a SARIMA benchmark using the years of 1999 and 2000 as the out-of-sample. The model clearly outperforms the benchmark. We conclude for general long memory in the series.

Development and evaluation of a range anxiety-reducing business model for connected full electric vehicles

This thesis develops and evaluates a business model for connected full electric vehicles (FEV) for the European market. Despite a promoting political environment, various barriers have thus far prevented the FEV from becoming a mass-market vehicle. Besides cost, the most noteworthy of these barriers is represented by range anxiety, a product of FEVs’ limited range, lacking availability of charging infrastructure, and long recharging times. Connected FEVs, which maintain a constant connection to the surrounding infrastructure, appear to be a promising element to overcome drivers’ range anxiety. Yet their successful application requires a well functioning FEV ecosystem which can only be created through the collaboration of various stakeholders such as original equipment manufacturers (OEM), first tier suppliers (FTS), charging infrastructure and service providers (CISP), utilities, communication enablers, and governments. This thesis explores and evaluates how a business model, jointly created by these stakeholders, could look like, i.e. how stakeholders could collaborate in the design of products, services, infrastructure, and advanced mobility management, to meet drivers with a sensible value proposition that is at least equivalent to that of internal combustion engine (ICE) cars. It suggests that this value proposition will be an end-2-end package provided by CISPs or OEMs that comprises mobility packages (incl. pay per mile plans, battery leasing, charging and battery swapping (BS) infrastructure) and FEVs equipped with an on-board unit (OBU) combined with additional services targeted at range anxiety reduction. From a theoretical point of view the thesis answers the question which business model framework is suitable for the development of a holistic, i.e. all stakeholder-comprising business model for connected FEVs and defines such a business model. In doing so the thesis provides the first comprehensive business model related research findings on connected FEVs, as prior works focused on the much less complex scenario featuring only “offline” FEVs.

The not so generalized effects of nonreciprocal trade agreements

This dissertation uses an empirical gravity equation approach to study the relationship between nonreciprocal trade agreements (NRTAs) and members’ trade flows. Estimations relate bilateral imports to trade policy variables using a very comprehensive dataset with over fifty years of data. Results show that meager average trade effects exist only if members are excluded from the world trading system or if they are very poor. As trade flows between NRTA members are already rising before their creation, results also suggest a strong endogeneity concerning their formation. Moreover, estimations show that uncertainty and discretion tend to critically hinder NRTA’s performance. On the other hand, reciprocal trade agreements show the opposite pattern regardless of members’ income status.Encouraging developing countries’ openness to trade through reciprocal liberalization emerges consequently as a possible policy implication.