Anke Weidlich

Simulating the dynamics in two-settlement electricity markets via an agent-based approach

Abstract This paper studies the dynamics in two-settlement electricity markets. In these markets, energy producers sign strategic forward contracts in the forward market, and engage in spatial oligopolistic competition in the spot market. We develop an agent-based model for simulating the outcomes of such markets. Numerical simulations imply that the access to the forward market leads to more competitive behaviors of the suppliers in the spot market, and thus to lower spot energy prices.

Monitoring and Control for Energy Efficiency in the Smart House

The high heterogeneity in smart house infrastructures as well as in the smart grid poses several challenges when it comes into developing approaches for energy efficiency. Consequently, several monitoring and control approaches are underway, and although they share the common goal of optimizing energy usage, they are fundamentally different at design and operational level. Therefore, we consider of high importance to investigate if they can be integrated and, more importantly, we provide common services to emerging enterprise applications that seek to hide the existing heterogeneity. We present here our motivation and efforts in bringing together the PowerMatcher, BEMI and the Magic system.

Analyzing interrelated markets in the electricity sector — The case of wholesale power trading in Germany

This paper reports on results from an agent-based simulation model that comprises three interrelated markets in the electricity sector: a day-ahead electricity market, a market for balancing power, and a carbon exchange for CO2 emission allowances. Agents seek to optimize trading strategies over the two electricity markets through reinforcement learning; they also integrate market results from emissions trading into their reasoning. Simulation outcomes show that the model is able to closely reproduce observed prices at the German power markets for the analysis period of 2006. The model is thus applicable for analyzing different market designs in order to derive evidence for policy advice; one example for such an analysis is given in this contribution.

Smart Houses in the Smart Grid: Developing an interactive network.

Private households constitute a considerable share of Europes electricity consumption. The current electricity distribution system treats them as effectively passive individual units. In the future, however, users of the electricity grid will be involved more actively in the grid operation and can become part of intelligent networked collaborations. They can then contribute the demand and supply flexibility that they dispose of and, as a result, help to better integrate renewable energy in-feed into the distribution grids.

Studying the effects of CO2 emissions trading on the electricity market: A multi-agent-based approach

In this paper, we present a basic approach for modeling electricity and emissions markets under the paradigm of agent-based computational economics (ACE). Different market players will be modeled as independent entities using autonomous software agents; they operate and communicate independently on power markets and on markets for emission allowances. The agent types involved and their relationships are described. The aim of the model is to investigate the interplay between the market players, with a focus lying on the dynamics in a market for CO2 emission allowances and its effects on the electricity markets. Simulations with this model will enable us to draw conclusions about the economic performance of different possible emissions trading design options

Decentralized Intelligence in Energy Efficient Power Systems

Power systems are increasingly built from distributed generation units and smart consumers that are able to react to grid conditions. Managing this large number of decentralized electricity sources and flexible loads represent a very huge optimization problem. Both from the regulatory and the computational perspective, no one central coordinator can optimize this overall system. Decentralized control mechanisms can, however, distribute the optimization task through price signals or market-based mechanisms. This chapter presents the concepts that enable a decentralized control of demand and supply while enhancing overall efficiency of the electricity system. It highlights both technological and business challenges that result from the realization of these concepts, and presents the state-of-the-art in the respective domains.

Agent-Based Simulations for Electricity Market Regulation Advice: Procedures and an Example

Summary This paper discusses the use of agent-based simulation models for regulatory advice in electricity market regulation. It briefly introduces the necessary procedures and the state-of-the-art of the methodology, and outlines its possible range of application. In a second part, the paper presents an agent-based simulation model developed by the authors. The model can be applied for analyzing different market designs and market structures in order to derive evidence for regulatory advice. This is exemplified through the analysis of two settlement rules in the balancing power market and of several divestiture scenarios of the German electricity sector.

Field Trials towards Integrating Smart Houses with the Smart Grid

Treating homes, offices and commercial buildings as intelligently networked collaborations can contribute to enhancing the efficient use of energy. When smart houses are able to communicate, interact and negotiate with both customers and energy devices in the local grid, the energy consumption can be better adapted to the available energy supply, especially when the proportion of variable renewable generation is high. Several efforts focus on integrating the smart houses and the emerging smart grids. We consider that a highly heterogeneous infrastructure will be in place and no one-size-fits-all solution will prevail. Therefore, we present here our efforts focusing not only on designing a framework that will enable the gluing of various approaches via a service-enabled architecture, but also discuss on the trials of these.

Emissions trading and innovation in the German electricity industry — impact of possible design options for an emissions trading scheme on innovation strategies in the German electricity industry

The paper examines what impact different design options of emissions trading have on the innovation process in the electric power industry. Recent concepts of innovation research in evolutionary economics are reviewed and investment cycles in the German power sector are examined before taking a closer look at different emissions trading design options and their respective impact on power generation costs.

Bidding Strategies for Flexible and Inflexible Generation in a Power Market Simulation Model: Model Description and Findings

This paper presents an electricity market simulation model that focuses on the distinction between flexible and inflexible generation, and formulates bidding strategies for capacities of either type. Bid formulation for flexible power plants, storage and demand response units at a control reserve market and an energy exchange market are described, and exemplary results from the simulation model are presented. It is shown that the simulation model can realistically reproduce market outcomes for the example of the German market zone, even for negative market prices. Results reveal that power plants could be deployed in a more flexible manner than it is actually done, where larger variations of output are avoided especially for nuclear and lignite-fired power plants. The model can be used for analyzing future energy scenarios of high shares of variable renewable energy (VRE), and help answering research questions related to the required system flexibility for balancing out VRE fluctuations.