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Optimizing biogas plants with excess power unit and storage capacity in electricity and control reserve markets
Affiliation:1. Fraunhofer-Institute for Wind Energy and Energy System Technology, Königstor 59, 34119 Kassel, Germany;2. University of Kassel, Germany;1. Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet, Building 115, DK-2800 Kgs. Lyngby, Denmark;2. Blueprinter, Esromgade 15, DK-2200 København N, Denmark;1. Goethe-University, Goethe-Center for Scientific Computing, Kettenhofweg 139, 60325 Frankfurt a.M., Germany;2. Potsdam-Bornim e.V. (ATB), Leibniz-Institut für Agrartechnik, Max-Eyth-Allee 100, 14469 Potsdam, Germany;1. Dipartimento di Ingegneria Elettrica, Gestionale e Meccanica, University of Udine, 33100 Udine, Italy;2. International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria;3. Mälardalen University, P.O. Box 883, SE – 72123 Västerås, Sweden
Abstract:Increasing shares of intermittent power sources such as solar and wind will require biomass fueled generation more variable to respond to the increasing volatility of supply and demand. Furthermore, renewable energy sources will need to provide ancillary services. Biogas plants with excess generator capacity and gas storages can adapt the unit commitment to the demand and the market prices, respectively. This work presents a method of day-ahead unit commitment of biogas plants with excess generator capacity and gas storage participating in short-term electricity and control reserve markets. A biogas plant with 0.6 MW annual average electric output is examined in a case study under German market conditions. For this biogas plant different sizes of the power units and the gas storage are compared in consideration of costs and benefits of installing excess capacity. For optimal decisions depending on prices, a mixed-integer linear programming (MILP) approach is presented.The results show that earnings of biogas plants in electricity markets are increased by additional supplying control reserve. Furthermore, increasing the installed capacity from 0.6 MW to 1 MW (factor 1.7) leads to the best cost–benefit-ratio in consideration of additional costs of excess capacity and additional market revenues. However, the result of the cost–benefit-analysis of installing excess capacity is still negative. Considering the EEG flexibility premium, introduced in 2012 in the German renewable energy sources act, the result of the cost–benefit-analysis is positive. The highest profit is achieved with an increase of the installed capacity from 0.6 MW to 2 MW (factor 3.3).
Keywords:Biogas plants  Gas storage  Unit commitment  Mixed-integer linear programming  Electricity market  Ancillary services
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