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Development of Operator-oriented Peer-to-peer Energy Trading Model for integration into the Existing Distribution System
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 정재성 | - |
| dc.contributor.author | 허강준 | - |
| dc.date.accessioned | 2022-11-29T02:32:17Z | - |
| dc.date.available | 2022-11-29T02:32:17Z | - |
| dc.date.issued | 2020-08 | - |
| dc.identifier.other | 30101 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/19798 | - |
| dc.description | 학위논문(석사)--아주대학교 일반대학원 :에너지시스템학과,2020. 8 | - |
| dc.description.tableofcontents | I. Introduction 1 II. Modellingthe marginal price and electric bill 5 II.A. Marginal buying price model 6 II.A.1. Cumulative rate (Block rate pricing) 6 II.A.2. Time of use (TOU) and other tariffs 8 II.B. Marginal selling price model 10 II.B.1. Net metering system 10 II.B.2. DERs sales system 11 II.C. Service charges model 13 II.C.1. Platform service charge (PSC) 13 II.C.2. Network usage charge (NUC) 16 II.D. The transition of the electric bill before/after P2P trading 19 III. Modelling P2P energy trading and its algorithm formulation 21 III.A. Trade price determination 22 III.B. Matching algorithm formulation 23 III.C. Overall trading process and price modulation 27 IV. Case study 31 IV.A. Simulation assumption 31 IV.A.1. Input data description 32 IV.A.2. Tariff description 34 IV.B. Service charge calculation results 37 IV.C. Simulation results for a day 38 IV.C.1. Price determination results 38 IV.C.2. Matching results 40 IV.D. Simulation results for the month 43 IV.D.1. Price modulation results for block rate pricing 43 IV.D.2. Matching results for the month 45 IV.D.3. Service charge calculation results for the month 49 V. Conclusion 51 References 52 | - |
| dc.language.iso | eng | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | Development of Operator-oriented Peer-to-peer Energy Trading Model for integration into the Existing Distribution System | - |
| dc.title.alternative | Kang-Joon Heo | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 일반대학원 | - |
| dc.contributor.alternativeName | Kang-Joon Heo | - |
| dc.contributor.department | 일반대학원 에너지시스템학과 | - |
| dc.date.awarded | 2020. 8 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 1151709 | - |
| dc.identifier.uci | I804:41038-000000030101 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/common/orgView/000000030101 | - |
| dc.subject.keyword | Marginal price | - |
| dc.subject.keyword | Matching algorithm | - |
| dc.subject.keyword | Operator-oriented | - |
| dc.subject.keyword | Peer-to-peer Energy Trading | - |
| dc.subject.keyword | Price modulation | - |
| dc.description.alternativeAbstract | This paper proposes a peer-to-peer (P2P) energy trading model to be integrated in the existing distribution system. For this, the operator-oriented trading scheme is developed to lower the barriers to entry into the P2P trading. Under this, the operator, rather than each participant, decides the trading price and trading schedules. To determine the trading price, the marginal price that accommodates various electric tariffs and sales systems are derived. The analysis for the wide range of tariffs and sales system has been conducted to be a trading model that accommodate a variety of current customers in the trading. Furthermore, to be a feasible trading model, service charges that include network usage charge and platform service charge are also derived. The former targets to compensate the utility company’s support that allows participants to trade energy and the latter ensures the platform operator’s economic benefit. Both service charges model draws the relevant entities’ participations to P2P trading. Based on the derived elements mentioned above, a matching algorithm is finally formulated. For this, a constrained optimization problem is derived, and Lagrange multiplier method is applied to make optimal trading schedule that results in maximizing social welfare while preventing imbalances in revenue between sellers and buyers. To verify the performance of the proposed P2P trading scheme, actual data for various types of load and distributed energy resources is applied on the IEEE 18 bus distribution system. | - |
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- Graduate School of Ajou University > Department of Energy Systems > 3. Theses(Master)
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