Wilke, Gwendolin
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A market-based smart grid approach to increasing power grid capacity without physical grid expansion
The continuous increase of competitiveness of renewable energy in combination with the necessity of fossil fuel substitution leads to further electrification of the global energy system and therefore a need for large-scale power grid capacity increase. While physical grid expansion is not feasible for many countries, grid-driven energy management in the Smart Grid often interferes in customer processes and free access to the energy market. The paper solves this dilemma by proposing a market-based load schedule management approach that increases power grid capacity without physical grid expansion. This is achieved by allocating for a certain class of non-critical flexible loads called “conditional loads” the currently unused grid capacity dedicated to ensuring N−1 security of supply whereas this security level remains untouched for all critical processes. The paper discusses the necessary processes and technical and operational requirements to operate such a system.
Fuzzy Logic with Evaluated Syntax for Sound Geometric Reasoning with Geographic Information
Integrating an Enterprise Architecture Ontology in a Case-Based Reasoning Approach for Project Knowledge
Technical Validation of the RLS Smart Grid Approach to increase Power Grid Capacity without Physical Grid Expansion
The electrification of the global energy system and the shift towards distributed power production from sus- tainable sources triggers an increased network capacity demand at times of high production or consumption. Existing energy management solutions can help mitigate resulting high costs of large-scale physical grid rein- forcement, but often interfere in customer processes or restrict free access to the energy market. In a preceding paper, we proposed the RLS regional load shaping approach as a novel business model and load management solution in middle voltage grid to resolve this dilemma: market-based incentives for all stakeholders are pro- vided to allow for flexible loads that are non-critical in customer processes to be allocated to the unused grid capacity traditionally reserved for N-1 security of supply. We provide a validation of the technical aspects of the approach, with an evaluation of the day-ahead load forecasting method for industry customers and a load optimization heuristics. The latter is tested by a simulation run on a scenario of network branch with provoked capacity bottlenecks. The method handles all provoked critical network capacity situations as expected.
Revenue optimization of telecom marketing campaigns for prepaid customers
The design and optimization of marketing campaigns today usually still includes a high level of manual expert in- volvement. This applies particularly to the prepaid mobile phone sector of the highly competitive telecommunication industry. Since prepaid telecom customers are characterized by highly volatile and sparse usage data their future behavior is hard to predict, and marketers often rely mainly on experience and gut feeling when designing marketing campaigns, using only simple data analysis tools. The project developed a methodology and software prototype that helps marketers in this area to exploit the full potential of real-time big data-driven analytics for microtargeting, allowing them to make fact-based and informed decisions. Specifically, it provides an interactive solution for the semi-automated visual support of the design and optimization of single-channel marketing campaigns. The developed solutions brings a huge step towards the automation of the whole process of optimizing marketing campai
Technical validation of the RLS smart grid approach to increase power grid capacity without physical grid expansion
The electrification of the global energy system and the shift towards distributed power production from sus- tainable sources triggers an increased network capacity demand at times of high production or consumption. Existing energy management solutions can help mitigate resulting high costs of large-scale physical grid rein- forcement, but often interfere in customer processes or restrict free access to the energy market. In a preceding paper, we proposed the RLS regional load shaping approach as a novel business model and load management solution in middle voltage grid to resolve this dilemma: market-based incentives for all stakeholders are pro- vided to allow for flexible loads that are non-critical in customer processes to be allocated to the unused grid capacity traditionally reserved for N-1 security of supply. We provide a validation of the technical aspects of the approach, with an evaluation of the day-ahead load forecasting method for industry customers and a load optimization heuristics. The latter