An efficient linear model for optimal day ahead scheduling of CHP units in active distribution networks considering load commitment programs
Creators
- 1. Faculty of Electrical Engineering, Shahid Beheshti University, A.C., Tehran (Iran, Islamic Republic of)
- 2. School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney (Australia)
- 3. Department of Industrial Engineering, University of Salerno, Fisciano, SA 84084 (Italy)
Description
The Optimal day-ahead Scheduling of Combined Heat and Power (OSCHP) units is a crucial problem in the energy management of Active Distribution Networks (ADNs), especially in the presence of Electrical and Thermal Energy Storages considering Load Commitment (LC) programs. The ADN operator may use Combined Heat and Power (CHP) units to supply its Industrial Customers (ICs) and can transact electricity with the upstream wholesale electricity market. The OSCHP problem is a Mixed Integer Non Linear Programming (MINLP) problem with many variables and constraints. However, the optimal operation of CHP units, Electrical and Thermal Energy Storages considering LC programs and contingency scenarios, may highly complicate this problem. In this paper, linearization techniques are adopted to linearize equations and a two-stage Stochastic Mixed-Integer Linear Programming (SMILP) model is utilized to solve the problem. The first stage models the behavior of operation parameters and minimizes the operation costs, verifies the feasibility of the ICs' requested power exchanges and the second stage considers LC programs and the system's stochastic contingency scenarios. The effectiveness of the proposed algorithm has been demonstrated considering 18-bus, 33-bus and 123-bus IEEE test systems. - Highlights: • Optimal day-ahead Scheduling of Combined Heat and Power units with Energy Storage systems. • Load Commitment Programs and inter-zonal power exchange on the operation scheduling scenarios. • A stochastic model to assess the uncertainty of system contingencies and upward wholesale market.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.energy.2017.08.008Additional details
Identifiers
- DOI
- 10.1016/j.energy.2017.08.008;
- PII
- S0360-5442(17)31383-X;
Publishing Information
- Journal Title
- Energy (Oxford)
- Journal Volume
- 139
- Journal Issue
- Complete
- Journal Page Range
- p. 798-817
- ISSN
- 0360-5442
- CODEN
- ENEYDS
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 49065451
- Subject category
- S29: ENERGY PLANNING, POLICY AND ECONOMY; S25: ENERGY STORAGE;
- Descriptors DEI
- COGENERATION; DUAL-PURPOSE POWER PLANTS; ELECTRIC POWER; ENERGY MANAGEMENT; ENERGY STORAGE SYSTEMS; LINEAR PROGRAMMING; NONLINEAR PROBLEMS; OPTIMIZATION; STOCHASTIC PROCESSES
- Descriptors DEC
- CALCULATION METHODS; ENERGY SYSTEMS; MANAGEMENT; POWER; POWER GENERATION; POWER PLANTS; STEAM GENERATION
Optional Information
- Copyright
- Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.