Changing asset ownership models in the energy sector is spurring established companies and startups to implement customer-centric smart services. In this sense, startups are pioneers of innovative business models, and unbundle the energy value chain to provide various services to final customers. Although service business models have received large attention in the energy sector, the role of startups in service business model innovation (S-BMI) is not fully understood in the literature. To put this into perspective, the proposed work analyzes the six most practiced energy service categories, specifically, Comfort and Heating, Flexibility and Trading, Energy Efficiency and Management, Solar and Microgrid, Charging and Battery, and Energy Software Solutions are taken into account, accompanying service business model archetypes in the energy sector. Data from two different company databases are combined, and a list of 432 startups dealing with energy services are analyzed. The operating revenue, stakeholders, investors, and funding are considered as the main indicators to compare the service categories. The top two categories in terms of the number of startups are Solar and Microgrid (38.1%) alongside Energy Efficiency and Management (20.1%). The analysis suggests that X-as-a-service (XaaS) and platform-based business models are becoming the center-of-attention for investors and shareholders. Digital marketplaces are also evolving in the energy sector. In fact, the current study found that startups associated with XaaS, platforms, and marketplace activities are attracting the majority of investors and funding programs. From a theoretical point of view, the study has provided the main motivations and enablers behind the energy sector servitization. The findings could serve as an initial methodological framework to analyze services in the energy sector, putting service business models and startups into focus.

Fault diagnosis and maintenance of a whole-building system is a complex task to perform. A wide range of available building fault detection and diagnosis (FDD) tools are only capable of performing fault detection using behavioral constraints analysis. However, the validity of the detected symptom is always questionable. In this work, we introduce the concept of the contextual test with validity constraints, in the context of building fault diagnostics. Thanks to a common formalization of the proposed heterogeneous tests, rule-, range-, and model-based tests can be combined in the same diagnostic analysis that reduces the whole-building modeling effort. The proposed methodology comprises the minimum diagnostic explanation feature that can significantly improve the knowledge of the building facility manager. A bridge diagnosis approach is used to describe the multiple fault scenarios. The proposed methodology is validated on an experimental building called the center for studies and design of prototypes (CECP) building located in Angers, France.