A Smart Energy Management System for Cross-sectoral Coupling

and Water-energy Nexus

Venkatesh Pampana, Pragya Kirti Gupta and Markus Duchon

fortiss GmbH, Guerickestr. 25, 80805 Munich, Germany

Keywords: Energy Management System, Water-energy Nexus, Cross-sectoral Coupling, Software Architecture, IoT,

Smart City.

Abstract: Cross-sectoral coupling is one of the newly emerging research topics that refers to the idea of interconnecting

and integrating the energy consuming sectors like buildings (heating and cooling), transport, water supply

systems and other energy intensive process with the power-producing sector. The cross-sectoral integration

of the water-energy nexus and the sustainability issues surrounding the availability of clean water and energy

has drawn the attention to the problem from all around the globe. Smart decision-making and control systems

can improve the efficiency of the overall operation of both water and energy systems. At a technological level,

there have been attempts to optimize coupling points between the electricity and water systems to increase

efficiency of both. Most of the optimization and smart decision-making systems focus on energy system and

consider heterogeneous infrastructure in the form of energy consumption devices. In the scope of water-

energy nexus, energy efficient decisions would have implications on water infrastructure. Tools and platforms

for water-energy nexus are required, such that planning and executing the decisions and their implications on

both energy and water infrastructure can be seen. Most of the existing controllers are specifically designed to

efficiently serve either energy or water systems. In this paper, we propose a software architecture for the

platform that is capable of monitoring, controlling, decision making and analysing the effect of decisions for

water and energy nexus.

1 INTRODUCTION

Water-energy nexus is the concept that refers to the

relationship between the water used for energy

production, including both electricity and fuel sources

such as oil and natural gas, and the energy consumed

to extract, purify, deliver, heat/cool, and dispose of

water and wastewater (Spang et al., 2014). It is

inextricably linked to the core of environmentally

sustainable smart cities as shown in Figure 1. Clean

and sustainable water supplies and low carbon energy

access are the essential building blocks for

economies, health and quality of life.

Present day energy and water systems are

interdependent and have to be addressed together

(Olsson, 2012). Extraction, treatment, carriage and

management of drinking water and treatment of

wastewater are both dependent on a substantial

amount of electrical energy. Huge volumes of water

are drawn and consumed from water bodies every day

for electricity generation. Rapid population growth,

increased per capita demand, distortion of availability

of fresh water due to climate change is driving up the

demand for both electricity and water. These trends

raise concerns about the robustness and sustainability

of today's electricity and water systems over the

coming decades.

Scarcity in either water or energy will create

aggravated shortages in both. An appreciation of the

scale of the challenge presented by the energy-water

nexus can be acquired by a consideration of the

degree of coupling between the two systems.

The demand on water resources in the urban

environment requires more efficient water

management to deal with urbanization and population

growth, more complex water facilities in new

buildings, and the deterioration of existing water

infrastructure. There is an urgent need to (a) reduce

the water extracted for use in buildings, (b) promote

water savings, and (c) stop wastage. The ability to

provide appropriate means to intelligently monitor

the water network and analyze real time information

with the help of smart technologies will provide

optimized alternatives to take better actions to

Pampana, V., Gupta, P. and Duchon, M.

A Smart Energy Management System for Cross-sectoral Coupling and Water-energy Nexus.

DOI: 10.5220/0009361901070113

In Proceedings of the 9th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS 2020), pages 107-113

ISBN: 978-989-758-418-3

107

balance the conflict between water demand and

provision.

Figure 1: Water-energy nexus: Building blocks for a

sustainable smart city.

The present day water management and energy

management are primarily centrally controlled

without any interlinking between both of them. The

central control is usually susceptible to downtimes

due to latency, connection loss, damage etc. Current

management systems, often, pose water quality

concerns, complex coordination issues between

energy savings, and operational and maintenance

issues (Cherchi et al., 2015). A loosely coupled,

distributed control and monitoring environment is

needed for betterment in both water and energy

management. A distributed control with central

coordination can produce a localized and robust

control with a platform that collects and analyzes

more data.

It is possible to address the water-energy nexus by

advanced energy efficiency and water management

algorithms, distributed monitoring and control

strategies, state-of-the-art metering infrastructure,

and optimal utilization of distributed energy

resources. Through the pervasive deployment of the

Internet of Things (IoT), and advanced Information

and Communication Technologies (ICT), big energy

data will be generated in terms of volume, speed, and

variety. Smart data analysis of this data can bring

enormous benefits to the energy efficiency and

management (Pindoriya et al., 2018). However, it

must be processed and communicated in an energy

efficient manner.

It is important to note that the challenges

presented by the energy-water nexus and sector

coupling are location specific. The mix of available

water sources, electricity generation options, local

effects of climate change, and societal requirements

together determine the sustainability and robustness

concerns associated with the nexus. This paper

presents an architecture for the platform that is

capable of monitoring, controlling, decision making

and analyzing the effect of decisions for water and

energy nexus through sector coupling. Section II

presents a brief review of issues covered in various

publications on or related to the energy-water nexus

and sector coupling. In Section III, system context,

application area, requirements and proposed system

architecture. Section IV offers some insights of the

proposed platform. Section V concludes the work and

presents potential directions for future work.

2 BACKGROUND

Water management primarily focuses on the

following aspects 1) Improving allocation through

quicker decision-making and control. 2)

Conservation of the resources (energy, water, and

other natural resources) available by improving the

efficiency and recycling the wastewater. Energy

management focuses on 1) Saving energy by

metering the energy consumption and collecting the

data. 2) Reducing dependence on the fossil fuels that

are becoming increasingly limited in supply. 3)

Optimal utilization of Renewable and distributed

energy resources (BizEE Energy Lens, 2019).

Literatures (Public Utilities Board Singapore,

2016; Diniz et al., 2015) discuss the strategies to

improve the energy efficiency of the water supply

systems. Energy management strategies using short-

term water consumption forecasting and computer

modelling to minimize cost of pumping operations

has been explored in (Jentgen et al., 2007; Bagirov et

al., 2015) respectively. Studies have successfully

demonstrated that integrated energy and water

management system provides a number of economic,

environmental and operational benefits, without

compromising on water quality and energy supply

objectives (Cherchi et al., 2015; Jentgen et al., 2007;

Douville & Macknick, 2011).

However, there are limited studies addressing the

water-energy nexus using sector coupling (Green et

al., 2017; Vakilifard et al., 2018). Most of the

approaches highlight the challenges and the need for

integration of renewable energy usage for multiple

sectors like food, water, agriculture etc. None of the

approaches proposed suitable platform architecture

for an integrated energy and water management

system.

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In this work, we propose an approach where we

address the integrated energy and water management

system by linking various branches of the energy

sector (sector coupling) and utilizing the ICT,

distributed monitoring and optimal utilization and

control of distributed energy resources (renewable

energies and energy storage) for water infrastructure.

Additionally, we propose a software architecture for

the platform that is capable of monitoring,

controlling, decision making and analyzing the effect

of decisions for water and energy nexus.

3 ARCHITECTURE OVERVIEW

A Smart Energy Management System for cross-

sectoral coupling and water-energy nexus should

meet following requirements:

 Real-time monitoring support: collecting and

analyzing data from various sensors.

 Support multi-communication protocol: In

order to seamlessly integrate with various field

devices and sensors irrespective of their

communication protocol.

 Smart decisions based on collected data:

Making smart decisions based on the advanced

optimization techniques and data analysis.

 Distributed controlling: To control complex

processes that can be geographically

disseminated using networked control elements

that are distributed throughout the system.

 Modular in nature: Easy to maintain, deploy,

update, and develop the software code

components.

 Flexible and Scalable: Scalable from building

level to city/municipality level

A service-oriented architecture with open

standard protocols, event-driven programming

model, service bus, and integrative computational and

data infrastructure is well suited for building robust

smart energy management system for water-energy

nexus (Mora et al., 2012; Berres et al., 2017) [11, 12].

We propose a generic architecture for such Energy

Management System presented in the Figure 2.

The bottom layer has software components

interfacing with the physical hardware devices such

as advanced metering, SCADA devices, IoT sensors

connected at the major process equipment in the

critical infrastructures like Water Treatment Plant

(WTP), Sewage Treatment Plant (STP), street

lighting system etc. that are spread spatially across the

field. This layer is primarily intended for realtime

monitoring and controlling of the field devices.

Custom monitoring and local control logic are

embedded in the interfaces that can exchange data in

device specific protocol (such as MODBUS, REST

API, OPC UA, MBUS, MQTT etc.). It is distributed

in nature with each interfacing component act

standalone. So malfunctioning of any of the

components does not affect the rest of the

components. It is also capable of local decision

making in case of communication

interruption/failures with higher level components or

in emergency situations. These components act as

controllers for respective field devices with which

they communicate. Due to this semi-autonomous

capability of this layer, distributed controlling is

made possible.

Figure 2: Proposed architecture for Energy Management

System for cross-sectoral coupling and water-energy nexus.

Middle layer consists of business logic

components. It receives the inputs from bottom layer

components and forwards it to higher level

components for preliminary decision making.

Though it usually follows the decisions from higher-

level components, during exceptional situations, it

has the final say over how the field devices should

behave. This would help in handling the exceptional

flow of events. One business logic component may

interact with multiple device interfacing components

in the bottom layer.

The improvement of energy efficiency and

effectiveness of water management and optimal

utilization of energy/water can be achieved by

A Smart Energy Management System for Cross-sectoral Coupling and Water-energy Nexus

109

incorporating advanced optimization algorithms and

techniques. Top layer has forecasting and

optimization components based on advanced data

analytics, machine learning techniques, and multi-

dimensional statistical tools. For example,

implementation of optimization components for an

array of energy cost reduction strategies operating

within designated constraints.

4 CASE STUDY

The testbed is located in GIFT City – Gujarat

International Finance Tech City of Gujarat, India. The

GIFT city envisions a smart city infrastructure with

efficient water and energy distribution networks in a

distributed manner. The testbed comprises of a WTP

and street lighting cluster (which is also located close

to WTP) as shown in the Figure 3. Water

infrastructure in GIFT is designed to provide

“potable-water-in-all-taps” with the total water

requirement of over 60 Million Litters per day

(MLD). The present process of WTP consists mainly

of the filtration process, dual media filters (made up

of sand and gravel) and micro cartridge filters. Dosing

is one of the main tasks in chemical and process

engineering in water treatment and as a result, hypo

dosing pumps (HDPs) and air compressors are used

in WTP.

The energy intensive loads like Hypo dosing

pump, Air compressor, etc. are connected to Water

treatment plant (WTP) feeder. Along with the WTP

loads, Solar Photovoltaic (PV) panels with Inverters

and Batteries are also connected to the feeder.

Similarly, Streetlights, Solar PV panels with inverter

and battery are connected to Street lighting feeder.

Additionally, there are interconnecting switches

connected to both feeders that facilitate switching of

batteries from one feeder to the other.

It has been observed that electricity generation

from renewable sources can be used to operate

processes like water supply, sewage plant, street

lighting etc. whereas in case of oversupply of

electricity from renewable sources, water pump or

other city processes can be made operational, thus

making the balance of supply and demand in the

system. This can be achieved by developing an

intelligent optimization framework and integrated

into the system. To check viability and feasibility,

couple of use cases were identified at the Testbed

based on load demand, operating duration, and

switching on-off pattern.

Figure 3: Testbed and use cases at GIFT city.

4.1 Use Cases

4.1.1 Use Case-1

Solar PV and Battery Energy Storage System (BESS)

installations will be utilized effectively to fulfil the

energy demand of the HDP at WTP in GIFT city.

Therefore, it can be anticipated that, by automating

the process control and energy flow to HDP, the

dosing process at WTP is well maintained. At the

same time, by effectively utilizing the solar PV and

BESS systems, the power drawn from the utility grid

can be reduced considerably which will eventually

reduce the operating cost. Similarly, Intelligent street

lighting also has significant potential in energy saving

for smart cities. An additional solar PV and BESS

system installations at GIFT city will be utilized to

supply power to the street light cluster. By automating

the process of energy flow and switching of street

lighting systems, a significant reduction in operating

cost and power drawn from the utility can be

achieved.

The main objective of this use case is to maximize

the use of solar PV system and battery to support the

load of HDP and air compressor in WTP and

minimize the overall cost of energy purchased from

the grid.

4.1.2 Use Case-2

Intelligent sharing of energy between multiple

batteries can further enhance the efficient utilization

of Battery storage systems. This can be achieved by

switching the batteries between the feeder lines (WTP

and Street lighting feeders) based on certain

optimization criteria and reducing the energy utilized

from the power grid. By this way, operation costs and

dependency towards the grid can be further reduced.

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4.2 System Architecture

A flexible, extensible, lightweight and self-similar

architecture has been deployed at the testbed in order

to implement the identified use cases that were

mentioned above. It follows a layered and

component-based approach to ensure scalability,

flexibility and extensibility with state-of-the-art

communication protocols. An overview of the system

is illustrated in Figure 4.

Figure 4: Software architecture of proposed integrated

water and energy management platform at the Testbed.

The Layer-1 and Layer-2 components are

developed based on an in-house energy management

tool called iEMS. The intelligent Energy

Management System (iEMS) is a decentralized and

distributed energy management system developed in

JAVA programming language. It can be used in micro

grid networks to intelligently manage the energy

resources and connected loads. The iEMS software

application is based on the OSGi framework, which

provides ease of development and deployment of

isolated services. These services or bundles can be

added, removed, or replaced at runtime without

interfering with the overall system at runtime. By

using a modular and component-based approach, we

ensure a highly flexible deployment of the system.

Hence, iEMS can be deployed across several

machines as a distributed system. It supports

numerous hardware. For example, Raspberry Pi,

Beagle Bone, Desktop computers, laptops, embedded

servers etc.

The iEMS core components include library

bundles responsible for information exchange,

database management, message bus interfacing

components, user management, and overall system

health check monitoring components. All the

components exchange information and data through

RabbitMQ message bus.

The bottom layer (Layer-1) has iEMS instances

along with interfacing components (Modbus client

and OPC UA client) that can communicate with field

devices at the water treatment plant and street lighting

cluster. The data is exchanged with aeration blower,

hypo dosing pump, air compressor, and energy meters

over MODBUS protocol, street lighting using REST

protocol and batteries through the OPC UA protocol.

Plant. WTP bundle measures the energy consumption

of hypo dosing pumps, compressor and monitor the

battery parameters (like State-of-Charge, voltage,

temperature, etc) from battery management system

(BMS). The IEC 61499 standard compliant 4DIAC

application is deployed in batteries, which interacts

with battery management system and helps in

monitoring and controlling of batteries over OPC UA

interface. Plant. Streetlight software bundle monitors

the energy consumption of streetlight and battery’s

SOC. Instances of iEMS and other components in this

layer are deployed on Raspberry PIs and are located

close to the field devices.

Layer-2 also consists of instances of iEMS along

with additional components. It receives the measured

data as inputs and forwards it to Optimizer

component for decision-making. The business logic

and flow of events are embedded in this layer. The

business logic components with respect to identified

use cases (BusinessLogic.Usecase1 and

BusinessLogic.Usecase2) are included in this layer.

They act as coordinators. The control signals are sent

to field devices via the components at Layer-1.

Further use cases, which would be identified in the

future, would also be included in this layer.

Decision making involves planning capabilities,

which are provided by the top most layer (Layer-3).

Optimization and forecasting algorithms are

implemented (Generation. Forecast, Demand.

Forecast and Optimizer) using machine learning

algorithms and optimization tools. The energy

optimization algorithms are implemented in GAMS

(General Algebraic Modeling System) and MATLAB

tools. A special interfacing tool has been developed

to integrate and communicate GAMS and MATLAB

tools with the OPC UA server.

The communication channels and protocols at the

testbed are chosen based on various considerations

such as distance between the plants, physical location

of field devices, support to the protocol by different

hardware and data latency requirements. Most of the

A Smart Energy Management System for Cross-sectoral Coupling and Water-energy Nexus

111

installed hardware supports MODBUS or OPC UA

communication protocol. The bottom level software

components (Layer-1) are deployed on Raspberry Pis

and higher level components (Layer-2 and Layer-3)

are deployed in Windows operating system based

workstations. The Raspberry Pis and workstations are

connected through Ethernet/LAN cables. Information

exchange between all the three layers would happen

through the OPC UA protocol.

5 CONCLUSIONS

Coupling of cross-commodity infrastructure and

optimal integration of distributed energy resources is

a challenge for smart cities. In this paper, we

presented an integrated water and energy

management platform architecture to manage the

water and energy infrastructures at GIFT city using

ICT. The testbed identified for this study are STP,

WTP, and street light clusters attached to WTP which

are energized by solar PV, BES, and utility grid. A

detailed description of the testbed is also presented

and then the use cases with their functional

requirements from the test bed have been identified.

A three layered component based architecture has

been proposed to address the energy management and

real time control of the use cases where a multilevel

controlling and monitoring system is proposed. The

proposed platform has the advantage of supporting

heterogeneous device protocols, flexible deployment

of the system, eliminating the latency and interruption

in management of infrastructure. Therefore, an

efficient and uninterrupted water and energy

distribution is possible at the testbed.

As a future step, the implementation will be

carried out in the real environment to test the data

collection and the controlling based on the

optimization values. Furthermore, new use cases will

be identified and proposed platform will be evaluated

through further research work in the future.

ACKNOWLEDGEMENTS

This work is being carried out for on-going research

project called ECO-WET (FKZ 01DQ17020A),

under the flagship of IGSTC (Indo-German Science

and Technology Centre). The Authors would like to

thank Federal Ministry of Education and Research

(BMBF, Germany) and Department of Science and

Technology (DST, India) for funding the research and

development activities of the project.

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