Heikki Hämmäinen

The electric energy system is undergoing a major change due to the increasing requirements of dynamic performance. In distribution grids, this evolution will necessitate expanded automation, which in turn will require enhanced connectivity solutions. Strongly evolving communications technologies and architectures, particularly mobile communications as well as cloud and edge computing, will provide new opportunities and alternatives for connectivity solutions. This paper contributes by identifying potential technical and industry architectures for the connectivity solutions required to manage distribution grids in the early 2030s. The study utilizes a senior expert panel and a Delphi survey. Industry architectures are modelled as value networks. The paper uses the Finnish distribution grids as a case example. Regarding technical architectures, the results reveal skepticism concerning those emerging 5G mobile network features that target industrial applications and about the need for extensive distributed computing in the proximity of consumers and prosumers. The most probable industry architectures are found to be those that enable the Distribution System Operators (DSOs) to maintain direct control of critical technical components, or that enable Communications Service Providers (CSPs) to handle the operations of both communications solutions and distributed computing. CSPs are seen as well positioned for this task due to their existing networking and computing infrastructure. However, this may also involve business risks for both DSOs and CSPs.

The electricity sector has a central role in the efforts to meet climate targets. Consequently, efforts are taking place to electrify industry, heating, and transportation. The Finnish government has set the target to halve carbon dioxide traffic emissions by 2030 and achieve carbon neutrality by 2045. Due to this target, the currently small proportion of electric vehicles (EVs) in Finland could expand in a manner that is difficult to forecast but could be exponential. Amid already strained investment budgets, anticipating the alternative scenarios and impacts of such a transport electrification evolution is of high importance to distribution system operators in order to optimize network planning and enhancements during the coming 15–25 years. The novelty and contribution of this paper is in utilizing a formal scenario planning process to envision what the alternative scenarios are (i.e., possible futures) for the evolution of the electric car fleet in Finland until 2040 and how these alternative scenarios could impact distribution grids. The impact analysis is performed in terms of additional energy and additional power in order to gain an understanding of the high-level impacts and investment needs. The analysis utilizes a real distribution grid in southern Finland as a case example that enables quantification. The results indicate the electric vehicles will, depending the scenario, pose an essential additional load in terms of both energy and power and that the required investment levels and investment types will be heavily dependent on the scenario.

Network slicing is a key enabler for providing new services to industry verticals. In order to enable network slice provisioning, it is important to study the network slice type allocation for different device types in a real industrial case. Furthermore, the costs of the required virtualization infrastructure need to be analyzed for various cloud deployment scenarios. In this paper, a cost model for the virtualization infrastructure needed for network slice provisioning is developed and subsequently applied to a real smart factory. In the model, slice types and devices are mapped such that each factory device is provisioned with one or more slice types, as required. The number of devices to be supported per slice type is forecasted for 2021–2030, and the total costs of ownership, costs per slice type, and costs for every slice type, for each device are calculated. The results are analyzed for three cloud deployment scenarios: local, distributed, and centralized. The centralized scenario was found to have the lowest cost. Moreover, sensitivity analysis is conducted by varying the device growth, the number of factories, the level of isolation between network slices, and resource overbooking. The resulting evaluation and cost breakdown can help stakeholders select a suitable deployment scenario, gauge their investments, and exercise suitable pricing.

The multiplicity of targets of the 5G and further future technologies, set by the modern societies and industry, lacks the establishment of design methods for the highly multidisciplinary application of wireless platforms for small cells. Constraints are set by the overall energy concept, structural safety and sustainability. Various Smart poles and Light poles exist but it is challenging to define the design drivers especially for a composite load-carrying structure. In this study, the design drivers of a composite 5G smart pole are determined and the connecting design between finite element modelling (FEM), signal penetration and computational fluid dynamics (CFD) for thermal analysis are reported as an interdisciplinary process. The results emphasize the significant effects of thermal loading on the material selection. The physical architecture, including various cutouts, is manipulated by the needs of the mmW radios, structural safety and the societal preferences of sustainable city planning, i.e., heat management and aesthetic reasons. Finally, the paint thickness and paint type must be optimized due to radome-integrated radios. In the future, sustainability regulations and realized business models will define the cost-structure and the response by customers.

Radio spectrum is a scarce natural resource, whose efficient management calls for a thorough understanding of its value. A number of spectrum valuation approaches has emerged considering different elements, some with potentially high uncertainty as future profits, total cost of ownership and societal benefits. Spectrum valuation is important in regulators’ 5G spectrum decisions and will face a new situation, where location specific services and higher carrier frequencies give rise to local network operator models. This paper analyses the existing spectrum management and spectrum valuation approaches and identifies key elements to consider, when defining and assessing the value of spectrum especially in the context of future local 5G networks. The growing pressure to open the mobile market for location and vertical specific 5G networks promotes new sharing-based spectrum access models, to allow the emergence of local 5G operators. We characterize the identified spectrum valuation elements in the context of these new local 5G networks from the perspectives of the different stakeholder roles including regulators, mobile network operators (MNOs) and entrant local 5G operators. We further present a spectrum valuation case study of the recent 5G spectrum decisions in the 3.5 GHz band in different countries.

5G will change the mobile communication business ecosystem by introducing location specific high-quality wireless networks that can be operated by different stakeholders. This development will change the traditional business models and ecosystem roles, as well as open the market for new local mobile network operators. These operators, such as recently introduced micro operators, can target specific customers in different vertical sectors with closed 5G networks, serve mobile network operator’s (MNO) customers in high-demand areas on behalf of the MNO as a neutral host with open 5G networks, or mix different types of customers and offerings through various hybrid platform business models. This paper discusses business model options for local 5G micro operators, addressing also the different network deployment options and ecosystem constellations. Three generic 5G business models and respective value ecosystems are presented: Vertical business model and ecosystem, Horizontal business model and ecosystem, and Oblique business model and ecosystem. These business models are compared against the opportunities they address, drivers and boundaries of value they may generate, and sources and sustainability of advantages they represent. Finally, scalability, adaptability and sustainability of the business models and ecosystems are examined.