4.8 Review

Methods and tools for community energy planning: A review

Journal

RENEWABLE & SUSTAINABLE ENERGY REVIEWS
Volume 42, Issue -, Pages 1335-1348

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2014.11.042

Keywords

Community energy planning; Tools; Model Urban planning system; Energy-related indicators

Funding

  1. Chinese National Twelfth Five-Year Plan for Science and Technology Support [2013BAJ10B01-02]
  2. China Intelligent Urbanization Co-Creation Center for High Density Region [CIUC20130003]

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High consumption of fossil fuels in urban area leads to environmental pollution and energy shortages, which threaten to reverse human progress. Community energy system planning makes great contributions to reducing fossil energy consumption. This paper focused on the Community Energy Planning (CEP) method at the Community Master Plan (CMP), Community Regulatory Plan (CRP), Community Site Plan (CSP) and Architectural Design (AD) stages. Top-down and bottom-up models for CEP at different stages of community construction were introduced. The present situation and development of research on energy demand forecasting, renewable energy resource assessments and whole community energy system optimization, which are three highly important components of bottom-up models, were introduced. After surveying the methods and tools that have contributed to CEP, the framework of computer tools for community energy system simulation and design was outlined. The functions (particularly focused on the existence of the functions of energy demand prediction, renewable energy resource assessment and whole community energy system optimization) and characteristics of these computer tools for community energy system design (CESD) were listed and compared. One of the current challenges is predicting community energy demand. There is still a shortage of available tools for determining energy-related indictors at the CRP stage. A built Community Energy Consumption data Monitoring and Statistic System (CECMSS) may help to predict a community's secondary energy demand. Ultimately, a framework for a new community energy analysis model that determines energy-related indicators was introduced. (C) 2014 Elsevier Ltd. All rights reserved.

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