Intermediation in Future Energy Markets: Innovative Product Design and Pricing

In order to mitigate the impacts of climate change, the international community envisages significant investments in electricity generation from renewable energy sources (RES). The integration of this decentralized and fluctuating type electricity generation poses several challenges to planning, operation, and economics of power systems. The established energy systems were originally designed for a centralized electricity generation that follows the uncontrolled but well predictable demand. However, for large shares of RES, relying only on the flexibility of the generation side would be economically inefficient. Furthermore, the environmental benefits of using RES would be depleted by additional carbon emissions from ramping highly flexible fossil-fueled power plants. An appealing alternative to facilitate the efficient integration of large shares of RES is to exploit the so far mainly passive demand side as an additional source of flexibility. The established centralized approaches can hardly handle the fine-grained and decentralized nature of demand side flexibility. Therefore, the intermediation between centralized control and decentralized demand will play a major role in future energy markets, which constitutes the overarching topic of this dissertation. Typically electricity generation from RES is capital-intensive but has near zero marginal costs. On this account, novel services need to be offered in order to transmit the right economic signals. To this end, the concept of the differentiable good electricity is refined in this dissertation. Embedded into the so-called energy service, characteristics such as temporal and spatial price differentiation or the risk of interruption can be specified to differentiate the so far homogeneous good. Based on the morphological design theory a framework for the notion of energy services is established and subsequently implemented as a decision support system. This supports a systematic and structured product development process to design innovative energy services. Such an innovative energy service is, e.g., the charging of electric vehicles in car parks, where prices are differentiated by job completion deadline. This allows the car park operator to control the aggregated load of all charging jobs to follow local RES generation. Based on this energy service the downstream activity of an intermediary is formally modeled as an optimization problem and evaluated by means of an empirical simulation experiment. The results provide insights on pricing policy and the value of demand side flexibility with regard to both the integration of local RES generation and operative profit optimization. In order to illustrate another innovative energy service the presented model is extended by the upstream activity of the intermediary. Household consumers are offered monetary incentives if they allow the intermediary to control their appliances. The results indicate the cost saving potential from demand side flexibility for the intermediary\u27s procurement of electricity. Beyond that, this model formulation constitutes the foundation for further examinations, e.g., to study the strategic behavior of intermediaries on real-time electricity markets that are prone to market power abuse due to low market liquidity

EVALUATING TIME-OF-USE DESIGN OPTIONS

Information systems in future smart grids will expand the capabilities of the power system through new services and control options. In this context, dynamically updated time-of-use (TOU) rates can be a building block for creating effective and robust pricing schemes in future retail electricity markets: On the one hand, they are better suited to match market dynamics and uncertainties than static, linear tariffs; on the other hand they mitigate the complexity arising from hourly real-time prices. Hence, the proper design of these dynamic rates requires managing the trade-off between complexity and efficiency. \ \ To this end, careful tuning of the rate complexity with respect to variability (number of time zones) and dynamics (frequncy of rate adjustments) is necessary. This challenges calls for efficient decision support that allows energy retailers to identify and implement promising rate designs. A framework to determine, analyse and compare a set of rate designs featuring different structural and dynamic design options is presented in this paper. This approach is illustrated using an exemplary scenario based on empirical electricity price data