Carsten Block

A Market Mechanism for Energy Allocation in Micro-CHP Grids

Achieving a sustainable level of energy production and consumption is one of the major challenges in our society. This paper contributes to the objective of increasing energy efficiency by introducing a market mechanism that facilitates the efficient matching of energy (i.e. electricity and heat) demand and supply in micro energy grids. More precisely we propose a combinatorial double auction mechanism for the allocation and pricing of energy resources that especially takes the specific requirements of energy producers and consumers into account. We describe the potential role of decentralized micro energy grids and their coupling to the large scale power grid. Furthermore we introduce an emergency fail over procedure that keeps the micro energy grid stable even in cases where the auction mechanism fails. As the underlying energy allocation problem itself is NP-hard, we derive a fast heuristic for finding efficient supply and demand allocations. In addition we show the applicability of this approach through numerica.

Load Shifting Agents for Automated Demand Side Management in Micro Energy Grids

This paper describes a novel approach for the automated management of micro energy grids. In particular a market based resource allocation mechanism is used to control energy generators and consumers within a micro energy grid. This approach requires energy consumers (producers) to buy (sell) their energy demands (supplies) through a specialized electronic auction platform. But as manually negotiating all energy demands and supplies on such a market is a tedious task, its automation is highly desirable and thus leads to the main contribution of this paper: The automation of the demand side bidding process through electronic bidding agents, which are equipped with an intelligent buying strategy that allows them to dynamically react to market changes and adapt their bidding behavior accordingly. More precisely, the agents are able to shift energy demand within certain boundaries from (expensive) peak hours to those times of the day where energy demand and thus energy prices are lower in order to minimize their cost. Moreover, as our results show, this behavior leads to a smoothed load curve for the whole system, i.e. demand peaks are reduced while base load increases.

Assessing the Impact of Price Forecast Errors on the Economics of Distributed Storage Systems

This article analyzes the economic impact of price forecast errors on the optimal operation schedules of distributed (battery) storage systems.The presented simulation model extends a linear optimization model that achieves up to 17% annual savings for a storage system in an environment with dynamically changing electricity prices and under the assumptions of ex-ante known load and price data. The main contribution of this paper is to replace the deterministic load and price curves by imperfect forecasts of which the effect of price forecast errors is systematically analyzed. All results are benchmarked against the optimal result of the basic model.The main finding is that the underlying storage optimization model performs with a high robustness against price forecast errors. E.g., up to 10% Mean Absolute Percentage Error (MAPE) for day-ahead price forecasts lead to less than 10% deviation from the optimal result. I.e., the storage model yields up to 15% annual savings vs. 17% in the optimal case.

A Decision Support System for Choosing Market Mechanisms in e-Procurement

The variety of procurement mechanisms present in the today’s e-procurement landscape ranging from electronic catalogue systems over e-negotiations to e-auctions, points at the fact that there exists no single best solution for all sourcing activities. Each mechanism rather has certain advantages and disadvantages. From economic theory, especially from mechanism design theory, it is well known that even small changes in the design of exchange mechanisms can have considerable impact on the outcome. In this paper we address this issue and present a solution that is aimed at supporting mechanism designers in their decision making process on which mechanism to choose best in a specific situation. In particular we describe a knowledge based system that was designed to help procurement staff in choosing an optimal mechanism for a particular sourcing scenario.

Simulations in the Smart Grid Field Study MeRegio Simulationen im MeRegio Smart Grid Feldtest

Abstract The aim of the research project MeRegio is to meet the claim for more efficient decentralized energy systems by integrating advanced information and communication technologies (ICT) into all stages of the energy supply chain. Several marketplaces — in particular for power and for ancillary services — which are coupled to the technical energy infrastructure through a powerful and lawful ICT infrastructure should serve as a basis for an efficient and transparent coordination of energy supply, energy demand, and services. The developed concepts will be both validated by simulations and tested within a model region.

Driving Profile Generator

The driving profile generator is a tool to generate an arbitrary number of car driving profiles such that the resulting profiles are in the same form as those reported in the latest German Mobility Panel (MOP), a large field study that reports car mobility for about 12.000 individuals in Germany. The profile generator described in this report is able to generate simulated driving patterns for four different groups of persons: employees, part time employees, retired people, and unemployed people. Each generated profile comprises all car movements of an individual within one week. For each of these trips several different pieces of information are provided, in particular the start of the trip, the duration of the trip, and the kilometers driven throughout the trip. To make the generated driving profiles follow patterns similar to those in the empirically observed driving profiles of the MOP, the panels database has been statistically analyzed and the results are used as the basis for the profile generator.

A Meta-Framework for Agile Development of SOA Market Platforms

Markets – and in particular auction markets – are usually known to be efficient mechanisms for information aggregation and for the allocation of goods and services. But a fundamental lesson learned from Economics is that market design matters. Even small changes in market rules may lead to significantly different outcomes. Thus a good design, implementation, and validation of a market mechanism poses a big challenge to market engineers, which cannot be mastered without appropriate engineering approach accompanied by appropriate supporting tools. In this paper we describe the tools available in the area of Market Engineering and analyze their strengths and weaknesses. Also we propose a new approach towards building market mechanisms that offers market engineers a new degree of agility and freedom during the design and implementation phases. The new approach follows the principles of service-oriented architectures and agile model driven development. Furthermore, we present three different case studies where the new framework was successfully applied for the fast implementation of new electronic market platforms and we present results from a complexity analysis as well as from a preliminary technology acceptance survey among a small group of market engineers.