Follow-up project on its way

mercredi 21 Oct 2020

We had the pleasure to welcome French colleagues from the UTBM (Université de Technologie de Belfort-Montbéliard) at the HEG Arc. They have a longstanding expertise in AI applied to Smart Cities, human-computer interaction, intelligent transport systems, and so forth. UTBM and HEG Arc have been cooperating for many years.

We discussed the possibility of submitting a follow-up project to Smart CityZens, starting in 2021. The project would include academic, public and private partners from different countries, as it was the case this year. We worked on the project objectives and discussed which topics would be relevant for Smart Cities of tomorrow.

We will see our colleagues again in Belfort and in Neuchâtel, with the support of the Communauté du Savoir, and will meet with potential project partners from France and Switzerland. Let us hope that Smart CityZens will live further!

Post: G. Chappuis. Photos: J. Wirth.

New research paper

mercredi 07 Oct 2020

Two of our professors and one of our students from Samara have just published a research paper based on the results of Smart CityZens: “Issues of ensuring economic and energy security in the “smart city” system”, by Anna Zotova, Irina Svetkina and Dinara Gilmanova.

The full version of the article is available here for download. For those who do not read Russian, here is the English version of the abstract.

The publication reflects the results of research on economic security issues at the level of administrative center of the subject of the Russian Federation in the context of the development of the “smart city” system. Cutting-edge technologies are becoming a powerful engine of transformation, including the energy sector. Development of smart cities and digitalization of services require reorganization of the energy business, search of new innovative opportunities and the development of new strategies, the final result of which will be the creation of new business models for energy suppliers. As a result of largescale statistics and practical cases analysis the main (specific) smart risks, smart challenges and smart threats for the economic security system of the largest city have been classified, recommendations to modify existing business models for Russian energetic industry have been offered.

Post: G. Chappuis

Quay in Samara. Adobe Stock

Ensuring Economic Security of Administrative Center of the Russian Entity

jeudi 30 Juil 2020

A really interesting article entitled « Ensuring Economic Security of Administrative Center of the Russian Entity » and written by I. A. Svetkina has been published recently. It talks about the « smart risks », « smart threats » and « smart challenges » for the economic security of smart cities. Go check it out!

2nd intensive week

vendredi 10 Juil 2020
Screenshot of the Zoom session

Today marks the last day of our second intensive week for the Smart CityZens project. Swiss and russian students met virtually to finalize their work and present it to experts on Thursday (09.07). Their projects include : smart stations for public transportation (bus, tramways, etc.), an app (Cleverly) fostering the reduction of energy consumption, a business model to take advantage of the blockchain technology in the energy sector, and finally, an app which calculates the most efficient energy mix when planning the development of city areas or real estate projects.

We would like to thank the experts from Swiss Federal Railways SBB, the Cities of Basel, Neuchâtel and Samara, for their support, as well as their interesting comments and feedback. We sincerely hope that the student projects will find their way into the cities of tomorrow! Many thanks also to our sponsor Movetia, the Swiss agency for exchange and mobility.

Despite its main part being achieved, the project will continue to live on, as well as this blog. Publications and other articles are still coming up! Moreover, students and professors will have the chance to finally meet in Russia for a study trip in 2021, if the Covid-19 situation allows it. We are looking forward to meeting with our Russian partners and discovering the city of Samara!


mercredi 01 Juil 2020

Ophélie Bouverat, Jason Choufani, Ksenia Kramarenko, Vladislav Unchuris, Audrey Voltz

Supervising Professor:
Anna Zotova

Crise COVID-19 et le secteur automobile, [no date]. [online]. [Viewed 24 June 2020]. Available from:
D’Incà et al. – Mobility 2040. The Quest for Smart Mobility.pdf, [no date]. [online]. [Viewed 24 June 2020]. Available from:
D’INCÀ, Joris, LORTIE, Patrick, CHAN, Wai-Chan and PRUVOT, Anne, [no date]. Mobility 2040. The Quest for Smart Mobility. . P. 14.
DUP_1027_Smart-Mobility_MASTER1.pdf, [no date]. [online]. [Viewed 24 June 2020]. Available from:
How COVID-19 pushes mobility innovations, [no date]. [online]. [Viewed 24 June 2020 a]. Available from:
How COVID-19 pushes mobility innovations, [no date]. [online]. [Viewed 24 June 2020 b]. Available from:
How COVID-19 will redesign urban mobility | Greenbiz, [no date]. [online]. [Viewed 24 June 2020]. Available from:
How has COVID-19 impacted 2020’s mobility trends?, [no date]. Intelligent Transport [online]. [Viewed 24 June 2020]. Available from:
Kamal et al. – 2019 – IoT Based Smart City Bus Stops.pdf, [no date]. [online]. [Viewed 24 June 2020]. Available from:
KAMAL, Miraal, ATIF, Manal, MUJAHID, Hafsa, SHANABLEH, Tamer, AL-ALI, A. R. and AL NABULSI, Ahmad, 2019. IoT Based Smart City Bus Stops. Future Internet. 26 October 2019. Vol. 11, no. 11, p. 227. DOI 10.3390/fi11110227.
NAKARMI, Nistha and SINGH, Sangeeta, 2019. Smart Infrastructure for Sustainable Public Transportation. In: . 2 November 2019.
On Demand Public Transport, [no date]. [online]. [Viewed 24 June 2020]. Available from:
Smart mobility, [no date]. Chief Investment Office [online]. [Viewed 24 June 2020]. Available from:
Smart Mobility in the Smart Cities of Tomorrow, [no date]. RideAmigos [online]. [Viewed 24 June 2020]. Available from:
The COVID-19 outbreak and implications to sustainable urban mobility – some observations, [no date]. Transformative Urban Mobility Initiative (TUMI) [online]. [Viewed 24 June 2020]. Available from:
Zicla Blog | Smart bus stops. What is it and why is it so important., 2017. Zicla [online]. [Viewed 24 June 2020]. Available from:

Energy providers

vendredi 26 Juin 2020

Who are we ?

“My name is Esther and I am thankful that I got the chance to participate in this SmartCityZen project. I have obtained plenty of knowledge about the energy sector in general and have learned the Russian culture through interaction with Russian students. Further on, the intensive discussion with specialists from public utilities and professors from different universities elevated my perspective in the energy sector. In light of the evolving new technologies which give rise tremendous impact on our daily life both on how do we consume energy and how do we as a consumer can engage in energy production. The energy sector is in the era of change, it’s unavoidable and at the pace that we cannot imagine. The first project week in Basel and Ligerz was fruitful and I look forward to the second project week which will be conducted online in July due to COVID.” 

“I am Laetitia Sudan and I am currently studying at Haute école de gestion Arc in Neuchâtel. During my previous year I had to choose my option for the last year. Smart Cityzens convinced me due to the fact that it is an experience in practice. In addition to that Smart Cityzens offers to all participants the chance to work with students from foreign country. Our topic was related to Energy providers, which I found tough because I am studying Business Administration and not Energy in concrete terms. Our task involves in improving the business model from this kind of companies. Indeed, we can propose what we want owing to new technologies. However, I am curious to discover how will be the world of tomorrow and I am proud to “work” a bit on it.”

“My name is Dinara Gilmanova. This year I am graduating Samara State University of economics where I’ve been studying the world economy for 4 years. I am lucky to be a part of the Smart CityZens project and our international team. Although I had some experience in project development before, the topic of «Smart Energy» was definitely new for me. After the first intensive week in Switzerland I’ve realized that the energy sector is in the era of global transformation. With the development of smart cities and digitalization of services it is required to reorganize the energy business, develop new innovative opportunities and implement cutting-edge strategies in order to create new business models for energy providers. So, these are the aspects that our team is working on. Anyway, we can not only see how smart technologies are changing the world for the better, but also make our contribution to the global transformation.”

« My name is Denis Liubitsky and I am a computer security specialist. I like everything about cutting-edge technologies, so I didn’t hesitate a second when I knew I could be a part of the Smart CityZens project. The main component in smart cities is the energy that feeds a lot of smart devices in smart homes. In the future, under the influence of digitalization, energy will take on a completely different form for consumers. Together with my team, I had the chance to rethink the business models of energy providers in this market transformation. This is very useful experience for me and I look forward to seeing the world of the future that we are working on. »

Our first week in Switzerland

Firstly, we met each other the first time in Switzerland in February 2020. Moreover, we met our teacher Alexander, who will be following us during all the project. He explained us the needs from the energy providers from Omsk. In Siberia, companies related to this field are totally different from Switzerland owing to the way of thinking and culture mostly.

In Siberia particularly energy providers lives from natural gas and oil. Instead of Russia, in Switzerland we mostly live with renewable energy. Omsk got the chance to take advantage of 300 sunny days, what an opportunity for solar panels ? In comparison to Switzerland, they did not introduce smart meters. It could be very useful for energy providers against “cheating”.

Our energy consumption is different as we explained it before. In Switzerland to satisfy our needs we use the exportation from foreign countries, 30% come from foreign countries. Moreover, we can improve our production of solar power and wind turbine. Indeed, Switzerland has much to learn from other European countries.

As a matter of fact, the battlefield of providing energy will continue to have radical change in the upcoming years. Energy providers are facing challenges like climate change and the reduction of polluted energy already. It’s the start of the battle and we believe that companies will focus more on a holistic solution instead of providing a single solution. Energy providers should be in partnership with other participants in the ecosystem in order to diversify their service. You will find below some examples of new business models.

New Business models at a glance

The energy provider has influence over almost every aspect of the supply chain but the least understanding of the customer. Considering the new regulatory environment providing collaborative innovation and business opportunity, offering bundled services can enable energy provider to prevent newcomers to step in and avoid splitting services off from their traditional services provided. (Mcmahon, 2020). The below picture depicts the business models which will be deployed in the next 24 months in a survey done in 2018 by Capgemini (Bigliani, Segalotto, & Skalidis, 2018). A combination of different business models with Energy as a service and Comfort as a service as the top margin contributors is the most promising way for the energy provider to survive.

Source: IDC Utilities’ New Business Model Survey 2018; Commissioned by Capgemini

The business model “Energy as a service” describes an energy provider is not only required to sell energy but also provide technology, analytics, personalised services and even access to the grid. Likewise, the “Comfort as a Service”, a model focus on providing comfort to residential customers which considers various elements that affect energy consumption and associated costs, and occupants’ behaviors to generate optimal control strategies for the domestic equipment automatically. Both business model concepts proof that energy providers are required to take further steps to accommodate the end client’s needs. Exploiting the potential of the smart meter which addresses the commercial and industrial (C&I) clients and residential customer’s needs. Within the next two years, three-quarters of the market players will move to this model. The decisive way of success is what will be the depth of the services and the capability to take the risk of deploying the appropriate use case.

Prosumer concept

Below two trends have proved the « prosumer concept ».  Firstly, apart from saving on energy bills, C&I clients are envisaged to take hold of not only the electricity user role but searching for the best possible offer in the market. Powering by the rise of the Energy marketplace which facilitates the development of energy optimization by combining the client’s energy consumption pattern and saving potential, C&I should be able to reduce their electricity bill enormously. 

Secondly, Generation and storage at home are other clear trends due to the significant drop in storage price of energy and the rise of the role of solar PV. Pertinent to the report (International Renewable Energy Agency, 2019), scaling up electricity from solar PV is crucial for decarbonization of the world’s energy system. Follow the wind energy which will be counted for one-third of the major electricity generation source, solar energy would supply up to ten folds by 2050. It’s a huge market for an energy provider in Switzerland who mainly provides the implementation of the solar panels for clients.

The potential of the margin from the innovative business model is currently underestimated especially in organizations from not liberalized countries due to limited competition. As such, defensive acquisitions and active involvement in new disruptive business models, for instance, Local P2P energy exchange platform via blockchain technology could help to adapt to disruptive chain, for instance, wholesale energy trading services on industry-level.

Technological change has facilitated small-scale implementation as well as independent transformation change in cities. As a matter of fact, except lighting, water, and waste management, there are still huge potential or development in water and sanitation investment

Digital transformation elevated the bar of data value with the help of the emergence of urban data platforms which solve the various problem and harnessing value from it. Whereby only limited investment has been made in these areas, they provide huge business opportunities in which energy providers can take advantage of their presence in the territory and the exploitation of existing physical infrastructures.

In opposite is the Microgrid as a service which deemed to be very difficult due to the high specificity of infrastructure from clients (e.g. hospitals, universities, corporate campuses, data centers) and missing standards in the industry.

In the below section, we will depict further insight on the blockchain’s impact on energy provider’s service.

Blockchain is a database in the form of a dispersed register that is distributed among the various players in the electricity retail market connected to a blockchain network. The blockchain properties such as data immutability, transparency, decentralisation and manipulation resistance are highly relevant today for the retail market of electrical energy.

What is the benefit of using blockchain for the company?

Blockchain makes it possible to create a single trusted information space that favourably influences the organization of the payment system.

The consumer pays the electric bills according to the fixed and reliable data recorded in the blockchain. Electricity payments are « splitted » between generating and electricity distribution companies by means of smart contracts, which are digital analogues of a power supply contract. A smart contract also allows the consumer to instantly change the energy tariff. And the power provider cannot change rates without notice, retroactively.

The introduction of blockchain is an urgent requirement dictated by the global transformation of the industry. In December 2019 the Russian energy company «Rossetti» reported about the launch of a pilot project for automatic power accounting: the cities of Yekaterinburg and Kaliningrad became pilot sites. The company’s plans are to completely exclude the manipulation of information in the energy market, including power accounting and payments for electricity. The solution is directly integrated with smart meters as well as with the bank, thanks to which the payment chain from the end-user to the generator of electricity is organized. Data on the electricity consumption of a specific household are transmitted directly from a smart-meter to the blockchain and are displayed in a mobile application. The consumer can monitor electricity consumption in real time. Moreover, the application analyses energy consumption and can, for example, recommend that the user switch to a more advantageous tariff.

In the future, the platform will be able to provide easy access to the energy market for new customers who not only take power from the electricity grid but, at certain times, can provide generated or previously accumulated electricity (prosumers). Also, the demand response technology project is being actively developed: at peak times, when electricity becomes expensive, the system operator can apply to the energy market for a reduction in demand, paying consumers the difference. Another perspective is the work with green certificates of renewable energy consumption, which is now gaining in importance in Europe and is beginning to develop in Russia.

So far, the use of blockchain alone does not generate savings compared to the use of traditional databases. But once the blockchain is universally applied, the savings will be significant. It is formed by transparency of payments between sales and electricity grid companies, rapid detection of unauthorized connections and elimination of non-payment bills.

Dinara Gilmanova, Esther Höhne, Denis Liubitskii, Laeticia Sudan

Supervising Professor:
Alexander Kabanov


Sadov A.V. (2019). Blockchain technologies on the electricity market. Rosseti Ural.

Rosseti. (2018). Digital transformation of 2030.

Waves Enterprise. (2019). Waves Enterprise’s solution: a new approach to recording electricity consumption Waves Enterprise.

Asma Khatoon, Piyush Verma, Jo Southernwood, Beth Massey and Peter Corcoran. (2019). Blockchain in Energy Efficiency: Potential Applications and Benefits.

Merlinda Andoni, Valentin Robu, David Flynn, Simone Abram, Dale Geach, David Jenkins, Peter McCallum, Andrew Peacock. (2019). Blockchain technology in the energy sector: A systematic review of challenges and opportunities. Renewable and Sustainable Energy Reviews. Volume 100. Pages 143-174.

Energy consumption and price reduction

mercredi 24 Juin 2020

We’ve been researching how to monitor individual appliances consumption in order to decrease peak and energy prices for end-user. That’s what we’ve found.

The first method to separate the appliance’s consumption is obvious and that is Intrusive Load Monitoring (ILM): use a metering device for each individual appliance that you need.

Opposite, Non-Intrusive Load Monitoring (NILM) is the energy disaggregation technique that provides a method to separate the individual consumption for certain appliances, respecting consumers’ privacy and often using already-deployed smart meters [1].

ILM is more precise than NILM but it is more expensive. NILM, on the other hand, is much cheaper, often it only needs smart meter. Let’s focus on NILM.

Main stages in NILM are [1]:

  1. Data collection: electrical data, including current, voltage, and power data, are obtained from smart meters, acquisition boards or by using specific hardware;
  2. Event detection: an event is any change in the state of an appliance over time. An event implies variations in power and current, which can be detected in the electrical data previously collected by means of thresholds;
  3. Feature extraction: appliances provide load signature information or features that can be used to distinguish one from another;
  4. Load identification: using the features previously identified, a classification procedure takes place to determine which appliances are operating at a specified time or period, and/or their states

So, the input of NILM is consumption characteristics, e.g. current, voltage, and the output is which appliances are turned on/off at a given time and/or their state.

There are appliances that have different load profiles at a different state, that’s what state in fourth stage means. It adds complexity to the algorithm. Another problem is that the house can have multiple appliances of the same type. Also, there are appliances with low consumption, for example, LED, which are hard to disaggregate, and appliances with consumption not varying in a periodic fashion.

Thus, NILM is not quite an easy task. Heuristic algorithms, such as Genetic Algorithms (GA) or Particle Swarm Algorithms (PSA), along with machine learning techniques are often used to solve that.

One of the important applications of NILM is the Home Energy Management System (HEMS). HEMS is responsible for scheduling appliances to reduce energy bills (Real-Time Pricing should be present) while saving a user’s comfort. It is also responsible for renewable energy system management if any. HEMS not only saves user’s money but also reduces consumption peak, which is good for energy producers because they can use fewer power generators.

Next, there are two examples of HEMS.

In [2] the following scheme was used:

Energy Management Controller (EMC) uses the Constrained Swarm Intelligence-based Consumer-Centric DSM module and database of historical records to disaggregate energy and schedule appliances. Also, HEMS is taking into consideration alternative energy (solar power on the image).

A phenomenal reduction in peak power consumption is achieved by 13.97% in that scheme.

In [3] the following scheme was used:

Data Acquisition Device is present. It is used to get consumption data. ZigBee-based Plug-load Control Relays are used to switch appliances on and off. Also, there is a computer that runs NILM algorithm (upper) and Home Gateway (lower) which has Database and communicates with ZigBee-based Plug-load Control Relays. Homeowners can get access to data using an internet browser.

NILM in that scheme is pretty complex:


It has three stages: off-line load learning & modeling, on-line load monitoring, and day-ahead in-home load scheduling. Such techniques as Hard c-Means clustering, sequential forward selection (SFS), hard c-means-based k-nearest neighbor classifier (k-NNC) are used. (See [3] for details).

Also, we’ve found a company called Smappee that offers appliances submeter, which can be integrated with HEMS:

That company has three ways to record appliances consumption (

The first and second ways use ILM, while the third way, which is cheaper, uses NILM. In a third way you should install a clamp to your power cable. The company claims that its patented NILM has a 70% average accuracy.

We came to the conclusion that for our project we could use NILM. NILM is pretty complex but real task. It’s already used by companies, such as Smappee, but may be not very accurate. We are not experts in field, so we can try ready solutions. For that purpose NILM toolkit [4] would be handy, which gives opportunity to evaluate different NILM algorithms on open datasets, such as REDD, BLUED, PLAID, REFIT, TRACEBASE, WHITED, UK-DALE, DRED [1]. Core idea of our project is similar to HEMS, maybe we should try to schedule appliances too.

Iolanda De Almeida Oliveira, Pavel Ivliev, Michael Kämpf, Igor Kirianov

Supervising Professor:
Zarina Charlesworth


  1. A Ruano, A Hernandez, J Ureña, M Ruano, J Garcia NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review. Energies 12, 2203 (2019)
  2. YH Lin, YC Hu Residential consumer-centric demand-side management based on energy disaggregation-piloting constrained swarm intelligence: Towards edge computing. Sensors 2018, 18, 1365.
  3. YH Lin, MS Tsai An Advanced Home Energy Management System Facilitated by Nonintrusive Load Monitoring With Automated Multiobjective Power Scheduling. IEEE Trans. Smart Grid 2015, 6, 1839-1851.
  4. Nipun Batra, Jack Kelly, Oliver Parson, Haimonti Dutta, William Knottenbelt, Alex Rogers, Amarjeet Singh, Mani Srivastava. NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring. In: 5th International Conference on Future Energy Systems (ACM e-Energy), Cambridge, UK. 2014. DOI:10.1145/2602044.2602051 arXiv:1404.3878

How Corona virus could affect Smart Cities

mercredi 27 Mai 2020

In the past month, several apps such as the CovApp have surfaced on the internet.

Their main goal is to target infected individuals and retrace their whereabouts to help identify potentially infected people.

But why and how could this affect Smart Cities ?

Well, the answer is simple. Data management is one of the key activities of Smart Cities.

By controlling traffic flux in heavily frequented areas such as public buildings, parks, train stations and airports, Smart City data centers could easily target and identify virus carriers.

The information could then be passed on to local Healthcare centers which will contact the aforementioned individuals and invite them to a medical check-up.

The Covid-19 crisis has shown the world the importance of traceability, transparency and a country’s capacity to take immediate action.

In this regard, could Smart Cities be part of such a solution ?

CNET – Explaining contact tracing apps that could save us from COVID-19

Energy Challenge Neuchâtel

mercredi 06 Mai 2020

Great News about Cleverly – the clever app for your home!

After an intensive week in February 2020 and the following weeks, we have submitted our project to the Energy Challenge 2020 of the Canton of Neuchâtel.

Cleverly is therefore competing with various other projects for the initial investment of CHF 3’000.–. This seed capital will help us to create a first prototype of our app and start our collaboration with partners such as local governments, communities and corporations.

We strongly believe that a community platform is needed to transform our future into a bright, electrifying one! We will keep you updated.

Your Cleverly Team

Iolanda De Almeida Oliveira, Pavel Ivliev, Michael Kämpf, Igor Kirianov

Supervising Professor:
Zarina Charlesworth

Environmental impact of smart grids

mercredi 22 Avr 2020

Most researchers agree that it is rather a question of when than of if the smart grid will be introduced (Tuballa & Abundo, 2016). To date, we have been writing and talking about the potential future business models and necessary steps in order to initiate the proclaimed transition process. However, we did not spend sufficient time on elaborating the potential environmental impact a smart grid may create.

An overwhelming part of the smart grid research has been focusing on the technological, legal and social aspects of a smart grid transformation (Pratt et al., 2010). The main measures of success stated are “improved reliability and cost-effective operation” (p. 5). However, as Pratt et al. argue, smart grids may create a potentially significant benefit for governmental climate change actions and therefore may propose an opportunity for accelerated, state-sponsored programs. To date, most empirical research regarding Co2 and energy savings in connection with smart grids are based on assumptions and represent solely estimates calculated by the respective studies (Hledik, 2009). Therefore, it is important to remember, that the actual environmental impact may be above or beyond the intervals provided by researchers.

In order to demonstrate a certain consensus between different studies, three specific researches will be briefly summarized. For further information on the different categories and mechanisms considered within each study as well as the underlying empirical data, please refer to the bibliography at the end of this blog post.

First, the study conducted by Pratt et al. (2010) for the United States Department of Energy focused on eight mechanisms impacting the energy consumption and the generation mix. One of the greatest impacts is created by information and feedback systems according to Pratt et al with close to three precent. The findings of the study suggest that the energy consumption and therewith linked Co2 emission may be reduced by 18% (p. 7), assuming a 100% smart grid implementation.

Second, the study conducted by Rohmund, Wikler, Faruqui, Siddiqui, & Tempchin (2009) is based on overall seven mechanisms and their respective influence. Similar to Pratt et al., the study attributes the greatest reduction potential for feedback systems on the energy usage. The authors of the study state the interval of the potential energy consumption and therewith linked Co2 emission reduction between 3.1% and 11.3% (p. 125)

Third, Hledik (2009) uses in his study five different mechanisms for measuring the potential energy consumption and Co2 emission reduction. In contrast to the research of Pratt et al. and Rohmund et al., Hledik argues that the major reduction potential is offered by load shifting and decentralized production and distribution. Overall, Hledik estimates the overall potential reduction to lay approximately between 5.1% and 15.7% of the total output (p. 38).

The aim of this brief comparison of the findings of current empirical research is, to demonstrate that governmental actors may consider the implementation of smart grids as a viable option for achieving their set climate goals (EU Commission Task Force for Smart Grids, 2016; Hledik, 2009). It is undisputable that smart grids create a positive externality regarding climate change and therefore propose an interesting additional measurement for climate policy making.

The difficulty for governments, however, is the non-existence of reliable research based on real-world data due to the lack of large-scale smart grid initiatives (EU Commission Task Force for Smart Grids, 2011). Nevertheless, we believe that smart grids have to be discussed on a national level and supported by sufficient funding in order to diversify the national climate actions.

Iolanda De Almeida Oliveira, Pavel Ivliev, Michael Kämpf, Igor Kirianov

Supervising Professor:
Zarina Charlesworth


EU Commission Task Force for Smart Grids. (2011). Task Force Smart Grids Expert Group 2 : Regulatory Recommendations for Data Safety , Data Handling and Data Protection Report. Task Force for Smart Grids.

EU Commission Task Force for Smart Grids. (2016). Smart Electricity Grids.

Hledik, R. (2009). How Green Is the Smart Grid? Electricity Journal, 22(2), 29–41.

Pratt, R. G., Balducci, P., Gerkensmeyer, C., Katipamula, S., Kintner-Meyer, M. C. W., Sanquist, T. F., … Secrets, T. J. (2010). The smart grid: an estimation of the energy and CO2 benefits. United States Department of Energy.

Rohmund, I., Wikler, G., Faruqui, A., Siddiqui, O., & Tempchin, R. (2009). Assessment of Achievable Potential for Energy Efficiency and Demand Response in the U.S. (2010 – 2030). EPRI. Palo Alto.

Tuballa, M. L., & Abundo, M. L. (2016). A review of the development of Smart Grid technologies. Renewable and Sustainable Energy Reviews, 59, 710–725.