Schreck, Sebastian (2023)
Local Energy Markets - Simulative Evaluation and Field Test Application of Energy Markets on Distribution Grid Level.
Technische Universität Darmstadt
doi: 10.26083/tuprints-00023674
Ph.D. Thesis, Primary publication, Publisher's Version
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Item Type: | Ph.D. Thesis | ||||
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Type of entry: | Primary publication | ||||
Title: | Local Energy Markets - Simulative Evaluation and Field Test Application of Energy Markets on Distribution Grid Level | ||||
Language: | English | ||||
Referees: | Niessen, Prof. Dr. Stefan ; Steinke, Prof. Dr. Florian | ||||
Date: | 2023 | ||||
Place of Publication: | Darmstadt | ||||
Collation: | xxvii, 149 Seiten | ||||
Date of oral examination: | 24 February 2023 | ||||
DOI: | 10.26083/tuprints-00023674 | ||||
Abstract: | Widespread introduction of Distributed Energy Resources (DERs) such as volatile renewable generation, electric vehicles, heat-pumps and battery storages causes a paradigm shift of the power system. Traditional power systems with few large-scale power plants are expanded or replaced by millions of small- to medium-size DERs. Local Energy Markets (LEMs) are a promising approach to facilitate the optimal operation and dispatch of DERs and enhance grid-integration on regional grid levels. In this Thesis, a novel linear-optimization-based market model for LEMs is developed. The market matching problem aims to maximize the social welfare of participants while considering technical and financial aspects of participants’ assets and the distribution grid. A simulative framework is set-up to evaluate the model with regards to its capabilities to foster the optimal use of flexibilities, to provide sufficient financial incentives for participants and to improve grid-integration. Yearly simulations of LEMs and a benchmark case are carried out for three different grid types (rural, semiurban, urban) and scenario years ranging from 2020 until 2035 in 5 year steps. The simulation results reveal that self-consumption and self-sufficiency of the local energy system can be increased by 4 ... 23 and 1 ... 9 percentage points depending on the grid type when compared to a business as usual benchmark case. An analysis of possible designs for regulated electricity price components in LEMs shows that a reduction of feed-in and load peaks of 30 ... 64 % can be achieved when considering power fees in the market matching problem. The simulative evaluation also shows that the market model is able to generate temporal, spatial, and asset-specific prices signals. Depending on the grid type and its load-generation ratio, participants with generation assets have higher benefits in urban, load-dominated grids whereas consumers have higher benefits in generation-dominated rural and semiurban grids. Load forecast uncertainty is identified as one of the major challenges in LEMs. Compared to simulations with perfect foresight, benefits of market participants are substantially decreased taking into account typical electric load forecast errors on the level of individual households. The application of the market model in a six months field-test in Southern Germany demonstrates the real world applicability of the developed approach. The field-test confirms findings from the simulative evaluation regarding the implication of forecast errors and generated price signals. It additionally shows that market interfaces to the Distribution System Operator (DSO) might further increase grid-integration capabilities of LEMs. By taking into account active power constraints of the DSO, 1499 events of critical grid load could be avoided. |
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Status: | Publisher's Version | ||||
URN: | urn:nbn:de:tuda-tuprints-236747 | ||||
Classification DDC: | 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering | ||||
Divisions: | 18 Department of Electrical Engineering and Information Technology > Technology and Economics of Multimodal Energy Systems (MMES) | ||||
Date Deposited: | 27 Apr 2023 12:10 | ||||
Last Modified: | 19 Jun 2023 09:29 | ||||
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/23674 | ||||
PPN: | 507318293 | ||||
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