383858 Optimal Design of Microgrids with Innovative CHP Systems: Integration of Process Optimisation and Life Cycle Assessment

Monday, November 17, 2014: 1:21 PM
M303 (Marriott Marquis Atlanta)
Di Zhang1, Sara Evangelisti1, Lazaros G. Papageorgiou2 and Paola Lettieri3, (1)Chemical Engineering, UCL, London, United Kingdom, (2)Centre for Process Systems Engineering, UCL (University College London), London, United Kingdom, (3)Department of Chemical Engineering, University College London - Torrington Place, London WC1E 7JE, United Kingdom

Optimal design of microgrids with innovative CHP systems: integration of process optimisation and life cycle assessment

Di Zhang, Sara Evangelisti, Paola Lettieri, Lazaros G. Papageorgiou


Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, UK

As an alternative to current centralised energy generation, microgrids are adopted to provide local energy with lower energy expenses and gas emissions by utilising distributed energy resources (DER). DER is defined as local resources related to the energy system, such as generators, boilers and energy storage devices. Micro Combined Heat and Power (micro CHP) units simultaneously produce heat and power for a single building. In order to meet renewable energy target in the UK, the installation of CHP units is considered because of their flexibility, reliability and safer operating conditions with high overall efficiencies. Several micro CHP technologies have been developed recently for applications at domestic scale, including fuel cell, micro turbine, internal combustion engine and sterling engine. The optimal design of DERs within microgrid plays an important role in promoting the penetration of microgrid. It attracts money research attentions from the economic view.

Different tools exist to evaluate the environmental impacts of a process or a service. Life Cycle Assessment (LCA) is recognised as one of the best tools available. Moreover, LCA is one of the most developed and widely used environmental assessment tools for comparing alternative technologies when the location of the activity is defined. Studies have been published on carbon footprint of micro – CHP units rather than a holistic environmental appraisal. A few studies have focused on the environmental impacts of different micro-CHP technologies analysing the functioning of single units rather than microgrids.

Limited studies in the literature have been focused on coupling environmental and economic sustainability in a multi-objective optimisation model: the majority of them focused on the operation of a single unit. To our knowledge, no studies have been published on the optimal design of microgrids considering environmental and economic metrics. In this work, the optimal design of microgrids with innovative CHP units is addressed while involving both concerns. A multi-objective modelling framework for the optimal design is presented. The trade-off between the two conflicting objectives is obtained by solving the proposed model using the ε-constraint method.

This work considers a general microgrid, which involves several participant sites of different building types. Macrogrid is available to provide electricity to the participant in the microgrid and extra electricity can also be sold back to the macrogrid when it benefits. The candidate technologies include CHP generators (with different capacities and heat-to-power ratios), boilers, thermal storage and a macrogrid power connection. Micro CHP technologies considered in this work are Proton exchange membrane (PEM) Fuel Cell, Solid Oxide Fuel Cell (SOFC), Internal Combustion Engine (ICE) and Stirling Engine (SE). Turn-key costs of CHP generators are based on the CHP types as well as the capacity range. The microgrid and the macrogrid are interacted and constrained through exporting or importing electricity.

The goal of the LCA in this work is to estimate the environmental impacts of four different CHP systems with additional thermal energy storage (TES) working in a distributed generation network. The life span considered is 15 years. The impact categories considered in this study are global warming potential (GWP) and acidification potential (AP). The output of LCA is used as the input for the optimisation model. A multi-objective mixed-integer linear programming (MILP) approach is developed for this problem. The key decision variables include unit capacities and resources utilised. They are determined by minimise the total equivalent annualised cost (EAC), GWP and AP of all participants, subject to equipment capacity constraints, CHP ramp limit constraints, energy demand constraints, CHP selection constraints, thermal storage constraints and transfer price level constraints.

The proposed model is implemented for different microgrid modes. For each mode, optimal design of the microgrid is obtained with (a) the candidate technologies selected and their capacities, (b) energy resources consumed, (c) energy production plan, (d) thermal energy storage plan. The trade-off between the economic and environmental objectives is analysed with a set of Pareto-optimal solutions.

Keywords: microgrids; life cycle assessment; multi-objective optimisation; ε-constraint method

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See more of this Session: Advances in Life Cycle Optimization for Process Development
See more of this Group/Topical: Environmental Division