Design, Planning and Control of Integrated Energy and Water Networks
By Hossam A.Gabbar, Ontario Tech University, Canada
This paper discusses integrated energy-water grids and the possible coupling in different regions and communities. The paper analyzes possible design and configuration of integrated energy-water grids in different hierarchical levels and as associated with possible decision parameters. Different energy and water load profiles are discussed in different situations and conditions, including sever weather conditions and emergencies. Planning framework is expressed in view of different energy-water integrated models and schemes. Control strategies are analyzed to meet performance measures with coordinated views and decision making. Energy-water integrated data centers are expressed to support operation in different regions and conditions.
Keywords: energy-water grids, energy-water networks, planning of energy-water grids
Energy and water networks are interconnected in number of ways. They are linked at different levels and applications. Fig. 1 shows a proposed regional infrastructure for energy-water integration with transportation networks. It shows possible levels of integration between thermal, fuel and electricity networks, including waste-to-energy (WTE), within each micro energy grid (MEG) and as interconnected among different MEGs. EG is electricity generation, GG is gas generation, TG is thermal generation, ES is electricity storage, GS is gas storage, TS is thermal storage, EL is electricity load, GL is gas load, and TL is thermal load nodes. ET is electricity transfer between MEGs. RT is transportation transfer between MEGs. GT is gas transfer between MEGs. TT is thermal transfer between MEGs. WT is water transfer between MEGs. TF is thermal transfer between MEG and transmission/distribution networks. GF is gas transfer between MEG and transmission/distribution networks. WF is water transfer. RF is transportation transfer between MEG and transmission/distribution networks. EF is electricity transfer between MEG and transmission/distribution networks.
Fig. 1. Smart Energy-Transportation-Water Infrastructures
Among the former was the speculation of long distance electricity transmission via low temperature superconducting cables by Garwin and Matissoo. Now it’s 1986. In late January of that year, Georg Bednorz and Alex Mueller performed a “rogue” experiment on several copper oxide compounds, an eventual Nobel Prize winning effort, followed within months by the discovery of Tc at 91 K by Paul Chu and his colleagues at UT-Houston in YBa2Cu3O4-y, which then ushered in our current era of “high temperature superconductivity.” Shortly thereafter, in July 1987, President Ronald Reagan announced the Superconductivity Partnership Initiative (SPI).
2. Water Production and Supply Chain
2.1 Water Cycle
Atmospheric rivers are relatively long, narrow regions in the atmosphere – like rivers in the sky – that transport most of the water vapor outside of the tropics.
2.2 Water Network Modeling
Water distribution network can be modeled as nodes and lines that connects water sources, distribution substations, with load end points. Fig. 2 shows one example of water network. Each node can represent storage, treatment, or load of water in any form. Each node could be linked with energy in any form as generation, storage, load, or transfer.
Fig. 2. Example of Water Distribution Network
3. Smart Energy Grids
In order to achieve resilient water networks, interconnected micro energy grids are proposed to offer distributed energy supply networks to support water networks in all hierarchical levels and regions. A generic model of a micro energy grid is shown in Fig. 3, which encompasses AC and DC power lines, AC and DC generation and load components, water lines, gas lines, hydrogen (H2) lines, waste-to-energy component, as well as transportation network integration, including compressed natural gas vehicle-CNGV, electric vehicle EV, and IC-internal combustion vehicle.
Fig. 3. Micro Energy Grid Generic Model
4. Energy-Water Grid Coupling
Energy-water grids coupling can be classified in terms of input and output integration, as shown in Table 2.
The energy-water networks can be integration can be achieved in different hierarchical levels, including equipment level, plant level, region level, city level, and the interconnection between them. The integration between energy and water can be linked to loads, storage, and generation in flexible and adaptive manner based on demand, weather, regulations, price, and technological factors. The integration between energy-water should include resilient features to support normal and abnormal as well as severe conditions with sustained operation. The presented hybrid integrated energy-water integration can be implemented in different regions and scales based on accurate evaluation of demand requirements, technological assessment, and life cycle analysis. Risk management framework is important to study different fault models among the different systems in energy-water and their integration with transportation. Control strategies and control systems should further developed to support the deployment of the proposed energy-water networks in different levels. Policies, standards, and regulations should be further developed to support the proposed integration of energy-water with transportation and other infrastructures in urban, rural, and remote regions.
Dr. Gabbar is Professor in Ontario Tech University (UOIT) in the Faculty of Energy Systems and Nuclear Science, and cross appointed in the Faculty of Engineering and Applied Science. He has established the Energy Safety and Control Lab (ESCL). He is the recipient of the Senior Research Excellence Aware for 2016 with more than 220 publications. He is leading national and international research in the areas of smart energy grids and resilient transportation electrification. Dr. Gabbar obtained his B.Sc. degree in 1988 with first class of honor from the Faculty of Engineering, Alexandria University (Egypt). In 2001, he obtained his Ph.D. degree from Okayama University (Japan). From 2001 till 2004, he joined Tokyo Institute of Technology, as a research associate. From 2004 till 2008, he joined Okayama University as a tenured Associate Professor. From 2007 till 2008, he was a Visiting Professor at the University of Toronto.