Franz, Alexander, Rieck, Julia, and Zimmermann, Jürgen
OR Spectrum. Mar2020, Vol. 42 Issue 1, p235-259. 25p.
Renewable energy sources, Linear programming, Industrial costs, Emission control, and Electricity
The paper describes a long-term scheduling problem for thermal power plants and energy storages. In addition, renewable energy sources are integrated by considering the residual demand. Besides the classical minimization of the production costs, emission-related costs are taken into account. Thereby, emission costs are determined by market prices for CO 2 emission certificates (i.e., using the EU emissions trading system). For the proposed unit commitment problem with hydrothermal coordination for economic and emission control, an enhanced mixed-integer linear programming model is presented. Moreover, a new heuristic approach is developed, which consists of two solution stages. The heuristic first performs an isolated dispatching of thermal plants. Then, a re-optimization stage is included in order to embed activities of energy storages into the final solution schedule. The considered approach is able to find outstanding schedules for benchmark instances with a planning horizon of up to one year. Furthermore, promising results are also obtained for large-scale real-world electricity systems. For the German electricity market, the relationship of CO 2 certificate prices and the optimal thermal dispatch is illustrated by a comprehensive sensitivity analysis. [ABSTRACT FROM AUTHOR]
OR Spectrum. Jul2017, Vol. 39 Issue 3, p749-773. 25p.
Resource allocation, Decentralization in management, Energy management, Supply chain management, Management, and Electricity
Changes in our electricity supply chain are causing a paradigm shift from centralized control towards decentralized energy management. Within the framework of decentralized energy management, devices that offer flexibility in their load profile play an important role. These devices schedule their flexible load profile based on steering signals received from centralized controllers. The problem of finding optimal device schedules based on the received steering signals falls into the framework of resource allocation problems. We study an extension of the traditional problems studied within resource allocation and prove that a divide-and-conquer strategy gives an optimal solution for the considered extension. This leads to an efficient recursive algorithm, with quadratic complexity in the practically relevant case of quadratic objective functions. Furthermore, we study discrete variants of two problems common in decentralized energy management. We show that these problems are NP-hard and formulate natural relaxations of both considered discrete problems that we solve efficiently. Finally, we show that the solutions to the natural relaxations closely resemble solutions to the original, hard problems. [ABSTRACT FROM AUTHOR]
OR Spectrum. Jul2016, Vol. 38 Issue 3, p633-660. 28p.
Marketing consultants, Business consultants, Marketing personnel, Marketing agreements, and Marketing management
In deregulated markets, electricity is usually traded in advance, and the advance commitments have a time lag of several periods. For example, in the German intraday market, the seller commits to providing electricity 45 min before the 15-min interval in which delivery has to be made. We consider the problem of a producer that generates energy from stochastic, renewable sources, such as solar or wind and uses a storage device with conversion losses. We model the problem as a Markov Decision Process and consider lagged commitments for the first time in the literature. The problem is solved using an innovative approximate dynamic programming approach. Its key elements are the analytical derivation of the optimal action based on the value function approximation and a new combination of approximate policy iteration with classical backward induction. The new approach is quite general with regard to the stochastic processes describing the energy production and price evolution. We demonstrate the application of our approach by considering a wind farm/storage combination. A numerical study using real-world data shows the applicability and performance of the new approach and investigates how the storage device's parameters influence profit. [ABSTRACT FROM AUTHOR]
OR Spectrum. Jul2014, Vol. 36 Issue 3, p723-759. 37p.
Planning, Steam power plants, Stochastic models, Simulation methods & models, Prices, Electricity, and Brownian motion
In the present paper, we present a mid-term planning model for thermal power generation which is based on multistage stochastic optimization and involves stochastic electricity spot prices, a mixture of fuels with stochastic prices, the effect of CO $$_2$$ emission prices and various types of further operating costs. Going from data to decisions, the first goal was to estimate simulation models for various commodity prices. We apply Geometric Brownian motions with jumps to model gas, coal, oil and emission allowance spot prices. Electricity spot prices are modeled by a regime switching approach which takes into account seasonal effects and spikes. Given the estimated models, we simulate scenario paths and then use a multiperiod generalization of the Wasserstein distance for constructing the stochastic trees used in the optimization model. Finally, we solve a 1-year planning problem for a fictitious configuration of thermal units, producing against the markets. We use the implemented model to demonstrate the effect of CO $$_2$$ prices on cumulated emissions and to apply the indifference pricing principle to simple electricity delivery contracts. [ABSTRACT FROM AUTHOR]