Wache, Holger

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Wache, Holger

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Publikation

Technoeconomic review of smart metering applications

2023, Efkarpidis, Nikolaos, Geidl, Martin, Wache, Holger, Peter, Marco, Adam, Marc, Ould Abdeslam, Djaffar

This chapter represents a brief version of the survey conducted in Efkarpidis et al. (Smart metering applications: main concepts and business models. Springer Nature Switzerland, Basel, pp. 1–164, 2022), where various smart metering applications are presented from the point of different stakeholders’ interests.

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Multi-agent based simulation of smart building cluster for electric grid stabilization

2019-11-21, Hall, Monika, Geissler, Achim, Wache, Holger

With the increasing number of photovoltaic systems and heat pumps in buildings existing substations of the electric grid could be overloaded. A multi-agent based simulation of a building cluster studies the impact of building flexibility in regard to the residual substation load. Each building announces its available flexibility, e.g. "heat pump can be switched off/on". A master coordinator evaluates all incoming offers and decides which offers are accepted. This reduces the residual load at the substation. This paper presents results from a study of the impact at the substation of a smart urban building cluster with different penetration scenarios of heat pumps, photovoltaic systems, batteries and electric vehicles. It is shown that a high penetration of heat pumps and photovoltaic systems violates the substation's limits for the studied building cluster. Batteries cannot reduce the peak utilization. The master coordinator's load shifting options are limited.

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Load management for idle capacity of power grids

2019, Layec, Vincent, Wache, Holger

A major issue hampering a rapid substitution of fossil fuels by electricity from sustainable sources is the fear of congestion of the power grid and of associated costs of their reinforcement. The conventional approach prevents any rapid raise of electricity demand by encouraging other energy carriers and sector coupling. However, no approach investigates the utilization of the full capacity of the power grid alone, which are kept idle to provide sufficient reserve for the case of a failure. Therefore, we test a load management approach designed to utilize this reserve capacity. We verify in this paper the correct functionality of the system made of a device manager for cost optimization of schedules and of a grid manager to enforce the respect of power limits of the grid. This novel approach contributes to reduce emission of greenhouse gases without grid reinforcement.

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Poster abstract: SmartStability. A multi-agent simulation environment for flexibility trading in households

2018-02-01, Wache, Holger, Künzli, Michael, Schulz, Nicola, Bichsel, Jürg, Hall, Monika

The increasing number of volatile energy sources, such as solar power plants, challenges the power network operators, the energy brokers as well as the electricity market actors. In this work, a multi-agent based approach will be introduced that allows multiple households to trade flexibilities, on top of the usual selling of produced energy to the paying consumer. Flexibility trading allows different optimisations for different actors. They can slightly shift their electricity consumption, e.g. by turning boilers on/off, to optimise the system (e.g. follow a predefined schedule). Simulation results indicate that a flexibility market consisting of only few households can already help to optimise the system.

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Publikation

Smart metering applications. Main concepts and business models

2022, Efkarpidis, Nikolaos, Geidl, Martin, Wache, Holger, Peter, Marco, Adam, Marc

This book presents a large number of smart metering applications from the points of view of different stakeholders. The applications are clustered with respect to three types of stakeholders: (a) end-customers, (b) energy service providers, and (c) authorities/research institutions or other organizations. The goal of the book is to examine the implementation potential for each application, considering the interests and benefits for the key stakeholders, main technical and regulatory requirements, as well as limitations and barriers. A business case for each application is created that can provide guidelines to the stakeholders involved in its realization. The book additionally investigates current business models for smart metering applications. A survey on the current techno-economic potential of such applications is conducted based on a questionnaire filled by various stakeholders. The book will be of interest to academic/research institutions, but also engineers in industry, authorities or other organizations.

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Technical Validation of the RLS Smart Grid Approach to increase Power Grid Capacity without Physical Grid Expansion

2019-05, Christen, Ramón, Layec, Vincent, Wilke, Gwendolin, Wache, Holger, Donnellan, Brian, Klein, Cornel, Helfert, Markus

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.

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A market-based smart grid approach to increasing power grid capacity without physical grid expansion

2018-02-01, Bagemihl, Joachim, Boesner, Frank, Riesinger, Jens, Künzli, Michael, Wilke, Gwendolin, Binder, Gabriela, Wache, Holger, Laager, Daniel, Breit, Jürgen, Wurzinger, Michael, Zapata, Juliana, Ulli-Beer, Silvia, Layec, Vincent, Stadler, Thomas, Stabauer, Franz

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.

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Impact of prosumers on the accuracy of load forecast with neural networks

2020, Muff, Roswitha, Wache, Holger

More and more prosumers will penetrate the power grid. But how do prosumers affect the accuracy of the day-ahead load forecast? In contrast to related research on prosumers and load forecast, this paper addresses the impact of different shares of prosumers on the load forecast for areas with several households. In order to answer this research question, the load forecast accuracies for a dataset without prosumers is compared to the ones of datasets with different shares of prosumers in an experimental setup using neural networks. A sliding window approach with lagged values up to seven days is applied. Apart from electricity consumption data weather and date data are considered. The conducted tests show, that the mean absolute percentage error increases from about 8% for a dataset without prosumers up to about 39% for a dataset with a share of prosumers of 80%. It can therefore be concluded that prosumers decrease the accuracy of the day-ahead load forecast with neural networks.

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Publikation

Flexible capacity addition case study at reduced grid tariff without security of supply

2019, Layec, Vincent, Wache, Holger

Energy intensive industries are sensitive both to the reliability and to the costs of their energy supply system. With renewable energy becoming more affordable, their weather dependent over- and under production will cause more volatile and higher spot price, but fees prevent the roll-out of Power- to-Gas. In this paper, we differentiate the new flexible loads of energy conversion and storage like Power-to-X or batteries from the regular loads of the core activity of industries and we design the tariff system of flexible loads in such a way to be financially attractive, by abandoning a security of supply that they actually do not need. In a previous work, the technical functionality of a load management system solving the grid congestion issues was described. Here we aggregate the yearly energy balance and the associated costs in six case studies to verify that the roll-out of the new flexible loads is economically viable. The financial attractiveness of the roll-out of new flexible loads with reduced tariff system and future drop in technology price is verified in all these customers and the tariff reduction for conditional loads is the decisive factor of the profitability in four of them.

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Shaping aggregated load profiles based on optimized local scheduling of home appliances

2018-02-01, Hunziker, Christoph, Schulz, Nicola, Wache, Holger

We present a new method to control an aggregated electric load profile by exploiting the flexibilities provided by residential homes. The method is based on a common energy price combined with inclining block rates, broadcasted to all households allowing them to minimize their energy provisioning cost. The distributed home energy management systems receive the price signal and use mixed integer linear programming for optimal scheduling of load, storage, and generation devices. The method provides excellent scalability as well as autonomy for home owners and avoids load synchronization effects. As proof of concept, an optimization algorithm for determining a day-ahead price is applied in two case studies. An excellent conformance between a given reference load profile and the resulting aggregated load profile of all households is demonstrated.