Energy and Environmental Systems Planning with Recourse: Inexact Stochastic Programming Model Containing Fuzzy Boundary Intervals in Objectives and Constraints-Reference-Cited by-同舟云学术

Energy and Environmental Systems Planning with Recourse: Inexact Stochastic Programming Model Containing Fuzzy Boundary Intervals in Objectives and Constraints

Published:2013-09 Issue:3 Volume:139 Page:169-189
ISSN:0733-9402
Container-title:Journal of Energy Engineering
language:en
Short-container-title:J. Energy Eng.

Author:

Hu Qing¹,Huang Guohe²,Cai Yanpeng³,Xu Ye⁴

Affiliation:

1. MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power Univ., Beijing 102206, China.

2. MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Resources and Environmental Research Academy, North China Electric Power Univ., Beijing 102206, China; formerly, Institute for Energy, Environment and Sustainable Communities—Environment Canada, Univ. of Regina, Regina, SK S4S 7H9, Canada (corresponding author).

3. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal Univ., Beijing 100875, China; and Institute for Energy, Environment and Sustainable Communities—Environment Canada, Univ. of Regina, Regina, Saskatchewan S4S 7H9, Canada.

4. Resources and Environmental Research Academy, North China Electric Power Univ., Beijing 102206, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Waste Management and Disposal,Energy Engineering and Power Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29EY.1943-7897.0000116

Reference45 articles.

1. A two-stage stochastic integer programming model for a thermal power system expansion

2. Future Environmental Regulation Issues to Promote Energy Efficiency

3. An inexact optimization model for regional energy systems planning in the mixed stochastic and fuzzy environment

4. Planning of community-scale renewable energy management systems in a mixed stochastic and fuzzy environment

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