Estimation of the failure probability of an integrated energy system based on the first order reliability method
- 1. Department of Electrical Engineering, State Key Laboratory of Electricity Systems, Tsinghua University (China)
- 2. School of Electronics and Information Engineering, Beihang University (China)
- 3. Guangzhou Power Supply Co. Ltd. (China)
Description
In this paper, we investigate the impacts of intermittent renewable energy sources (RESs) and stochastic energy loads on the operation and uncertainties of an integrated energy system (IES). In our analysis, we use a first order reliability method (FORM) to estimate the failure probabilities, which are crucial for ensuring the reliability of the gas supply and surplus power absorption. The Hasofer Lind and Rackwitz Fiessler (HLRF) algorithm is introduced to solve the FORM optimization model while considering the stochastic behaviours and dependencies of multiple energy sources. A mathematical case is presented to demonstrate the use of the FORM in the estimation of failure probability, and the results are validated using the Latin hypercube sampling theories, including the Iman and Stein methods. The results of a failure probability analysis for an ideal IES are provided to illustrate the proposed technique. The failure probability can be used to improve IES operation and planning and ensure better reliability. - Highlights: • This paper presents the failure problems of an integrated energy system. • Practical engineering problems are investigated and analysed. • The stochastic behaviours of a limited gas supply are considered. • The dependencies between the surplus power and the ability of the grid to absorb it is modelled. • The application of the model is illustrated using an ideal IES.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.energy.2017.06.090Additional details
Identifiers
- DOI
- 10.1016/j.energy.2017.06.090;
- PII
- S0360-5442(17)31084-8;
Publishing Information
- Journal Title
- Energy (Oxford)
- Journal Volume
- 134
- Journal Page Range
- p. 1068-1078
- ISSN
- 0360-5442
- CODEN
- ENEYDS
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 49063294
- Subject category
- S29: ENERGY PLANNING, POLICY AND ECONOMY;
- Descriptors DEI
- ENERGY SYSTEMS; PROBABILITY; RELIABILITY; RENEWABLE ENERGY SOURCES; STOCHASTIC PROCESSES; SURPLUS POWER; SYSTEM FAILURE ANALYSIS
- Descriptors DEC
- ELECTRIC POWER; ENERGY SOURCES; POWER; SYSTEMS ANALYSIS
Optional Information
- Copyright
- Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.