Guenter Conzelmann

Wind power forecasting : state-of-the-art 2009.

Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

Multi-agent power market simulation using EMCAS

Countries around the world continue to restructure their electricity markets and open them up to competition and private investors in pursuit of economic efficiency and new capital investment. However, the recent volatility exhibited by many restructured power markets, in combination with several prominent market failures, have highlighted the need for a better understanding of the complex interactions between the various market participants and the emerging overall market behavior. Advanced modeling approaches are needed that simulate the behavior of electricity markets over time and model how market participants may act and react to changes in the underlying economic, financial, and regulatory environments. This is particularly useful for developing sound market rules that will allow these markets to function properly. A new and promising approach is to model electricity markets as complex adaptive systems using an agent-based modeling and simulation approach, such as is implemented in the electricity market complex adaptive system (EMCAS) software. EMCAS provides an agent-based framework to capture and investigate the complex interactions between the physical infrastructures and the economic behavior of market participants that are a trademark of the newly emerging markets. This paper describes the EMCAS agents, their interactions, the unique insights obtained from agent-based models, and discusses current model applications in several U.S., Asian, and European markets.

System-Wide Emissions Implications of Increased Wind Power Penetration

This paper discusses the environmental effects of incorporating wind energy into the electric power system. We present a detailed emissions analysis based on comprehensive modeling of power system operations with unit commitment and economic dispatch for different wind penetration levels. First, by minimizing cost, the unit commitment model decides which thermal power plants will be utilized based on a wind power forecast, and then, the economic dispatch model dictates the level of production for each unit as a function of the realized wind power generation. Finally, knowing the power production from each power plant, the emissions are calculated. The emissions model incorporates the effects of both cycling and start-ups of thermal power plants in analyzing emissions from an electric power system with increasing levels of wind power. Our results for the power system in the state of Illinois show significant emissions effects from increased cycling and particularly start-ups of thermal power plants. However, we conclude that as the wind power penetration increases, pollutant emissions decrease overall due to the replacement of fossil fuels.

Incorporating environmental concerns into electric system expansion planning using a multi–criteria decision support system

A methodology is described for incorporating environmental externalities into electric system expansion planning. It combines a conventional least–cost optimisation tool, an environmental model, and a multi–criteria interval decision analysis system. The methodology can be used to analyse trade–offs between technical, economic, and environmental concerns. A case study in support of an international lending decision is used to analyse eleven power–sector expansion scenarios in terms of total system cost and environmental residuals. The scenarios are then compared by using a decision analysis tool. A brief comparison of interval and traditional decision analysis methodologies is also provided.

Market power analysis in the EEX electricity market: An agent-based simulation approach

In this paper, an agent-based modeling and simulation (ABMS) approach is used to model the German wholesale electricity market. The spot market prices in the European Energy Exchange (EEX) are studied as the wholesale market prices. Each participant in the market is modeled as an individual rationality-bounded agent whose objective is to maximize its own profit. By simulating the market clearing process, the interaction among agents is captured. The market clearing price formed by agentspsila production cost bidding is regarded as the reference marginal cost. The gap between the marginal cost and the real market price is measured as an indicator of possible market power exertion. Various bidding strategies such as physical withholding and economic withholding can be simulated to represent strategic bidding behaviors of the market participants. The preliminary simulation results show that some generation companies (GenCos) are in the position of exerting market power by strategic bidding.

Survey of U.S. Ancillary Services Markets

In addition to providing energy to end-consumers, power system operators are also responsible for ensuring system reliability. To this end, power markets maintain an array of ancillary services to ensure it is always possible to balance the supply and demand for energy in real-time. A subset of these ancillary services are commonly procured through market-based mechanisms: namely, Regulation, Spinning, and Non-spinning Reserves.

Actuator Line Aerodynamics Model with Spectral Elements

Actuator line aerodynamics (AL) model is becoming increasingly popular for characterization of the flow field and the turbulent wakes created by the rotated turbines. AL model does not require boundary layer resolution and is thus significantly more efficient than the fully-resolved computations. Potential of this model to be applied to the simulation of really large wind plants creates the need of exploring its applicability and performance with highly-scalable computation codes. In this paper, we present the details of implementation and validation of the actuator line aerodynamics model in a high-order spectral-element code which is known to scale efficiently to hundreds of thousands of processors.

Multi-agent simulation of generation capacity expansion decisions

In this paper, we use a multi-agent simulation model, EMCAS, to analyze generation expansion in the Iberian electricity market. The expansion model simulates generation investment decisions of decentralized generating companies (GenCos) interacting in a complex, multidimensional environment. A probabilistic dispatch algorithm calculates prices and profits for new candidate units in different future states of the system. Uncertainties in future load, hydropower conditions, and competitorspsila actions are represented in a scenario tree, and decision analysis is used to identify the optimal expansion decision for each individual GenCo. We run the model using detailed data for the Iberian market. In a scenario analysis, we look at the impact of market design variables, such as the energy price cap and carbon emission prices. We also analyze how market concentration and GenCospsila risk preferences influence the timing and choice of new generating capacity.

On Usage Context of Hybrid Electric Vehicles in Choice Studies

Considering usage context attributes in choice modeling has been shown to be important when product performance highly depends on the usage context. To build a reliable choice model, it is critical to first understand the relationship between usage context attributes and customer profile attributes, then to identify the market segmentation characterized by both sets of attributes, and finally to construct a choice model by integrating data from multiple sources. This is a complex procedure especially when a large number of customer attributes are potentially influential to the product choice. Using the hybrid electric vehicle (HEV) as an example, this paper presents a systematic procedure and the associated data analysis techniques for implementing each of the above steps. Usage context and customer profile attributes extracted from both National Household Travel Survey (NHTS) and Vehicle Quality Survey (VQS) data are first analyzed to understand the relationship between usage context attributes and customer profile attributes. Next the principal component analysis is utilized to identify the key characteristics of hybrid vehicle drivers, and to determine the market segmentations of HEV and the critical attributes to include in choice models. Before the two sets of data are combined for choice modeling, statistical analysis is used to test the compatibility of the two datasets. A pooled choice model created by incorporating usage context attributes illustrates the benefits of context-based choice modeling using data from multiple sources. Even though NHTS and VQS have been used in the literature to study transportation patterns and vehicle quality ratings, respectively, this work is the first to explore how they may be used together to benefit the study of customer preference for HEVs.© 2011 ASME

Using multi-agent simulation to test European electricity markets

We discuss examples of implementations of agent-based simulation models in several European countries. Agent-based modeling and simulation (ABMS) is increasingly used as a tool to analyze power markets around the world and test the robustness of electricity markets and their underlying rules. The diversity of market designs, the complexities in their configurations with multitudes of participants, and their coupling with the underlying infrastructure require simulation approaches that allow a better representation of these real-world constraints. The power of ABMS tools lies in the flexibility they provide to merge and address these requirements in a single modeling framework.