Contents lists available at ScienceDirect Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser Exploring the impact space of different technologies using a portfolio constraint based approach for multi-objective optimization of integrated urban energy systems Rui Jing a,b,1 , Kamal Kuriyan b,1 , Qingyuan Kong b , Zhihui Zhang a , Nilay Shah b , Ning Li a , Yingru Zhao a,* a College of Energy, Xiamen University, Xiamen, China b Department of Chemical Engineering, Imperial College London, London, UK ARTICLE INFO Keywords: Impact space Modelling to generate alternatives Eps-constraint Portfolio constraint Integrated urban energy system Multi-objective optimization ABSTRACT Optimization-based modelling provides valuable guidance for designing integrated urban energy systems. However, modelers have to make certain assumptions and they may lack awareness of realistic conditions such as decision-makers’ preferences on certain technology, which can easily lead the obtained optimal solution to be invalid. Therefore, instead of focusing on one “fragile” optimal solution, this paper provides a systematic overview of the contribution each technology can bring to the whole system design so as to achieve the op- timum. To achieve this, a portfolio constraint based approach is proposed, which is inspired by the modelling to generate alternatives (MGA) method as well as the eps-constraint method for multi-objective optimization. By varying the threshold values of portfolio constraints, a series of solutions can be gathered as an “impact space” representing the economic and environmental contributions of each technology for the whole system design. A practical Fitting of Ellipses method is further applied to quantify the size of the impact space. Through observing the formation of the impact space, more valuable insights on system design can be obtained. The proposed approach is applied to a case study of an urban district in Shanghai, China, where a generalized urban energy system model involving commonly used energy supply technologies is established. Various tech- nologies and design options lead to significantly different impact spaces, where CHP is found to have the largest impact on system design. Overall, instead of merely providing decision-maker a very specific solution, this paper introduces a new approach to evaluate multiple technologies when designing integrated urban energy systems. 1. Introduction Integrated energy systems are a promising solution for energizing urban areas in an efficient and low-cost manner [1]. The design of such systems is complex since multiple highly integrated energy sectors are involved [2]. Thanks to improvements in mathematical optimization and computational capability, the problem can be formulated and solved as an optimization model. The model evaluates the possible design and dispatch of integrated energy systems based on certain as- sumptions on input parameters. Deterministic models in which all input parameters are pre-determined have been widely studied, see e.g., Li et al. [3], Wang et al. [4], and Wu et al. [5]. 1.1. Review of approaches to modelling with uncertainty Different sources of uncertainties exist in the evaluation of future scenarios and corresponding approaches have been developed to ad- dress these. The two main categories of methods are reviewed below. 1.1.1. Modelling with parametric uncertainty Much research addresses parametric uncertainty which considers factors such as variations in future energy prices, the stochastic nature of renewables and fluctuating energy demand. Zheng et al. [6] utilized Monte Carlo simulation to convert a stochastic problem into a de- terministic problem, so as to analyze the sensitivity of demand to pro- ject cost when planning a solar-biomass micro-grid with demand re- sponse capability. Hocine et al. [7] proposed a multi-segment fuzzy goal https://doi.org/10.1016/j.rser.2019.109249 Received 15 February 2019; Received in revised form 25 June 2019; Accepted 25 June 2019 * Corresponding author. E-mail addresses: fafujingrui@126.com (R. Jing), yrzhao@xmu.edu.cn (Y. Zhao). 1 The first and second authors make equally contribution to this work. Renewable and Sustainable Energy Reviews 113 (2019) 109249 1364-0321/ © 2019 Published by Elsevier Ltd. T