A human centric look at electricity consumption and design towards a “Smart Campus”

It was almost a year ago when we concluded a project named “The Smart Campus Simulation Tool”. We are looking to release the simulation tool to open source. In this post, we wanted to explore the problem context which informed our design.

To us a Smart Campus represented a socio-technical system that would be “malleable” enough for us to achieve our objectives. We approached it to be a socio-technical system, the technology (the adaptive sensor based control system) has to work with the social context of an academic institute. At the end of the day, people have to accept and be willing to make changes to their lifestyles.

We wanted to look at the issue of electricity consumption for the IIIT-Bangalore. The institute had invested in a fair amount of energy saving equipment such as solar panels and more efficient water heating systems. But, they were not clear about the eventual savings in energy, the electricity consumption patterns or if there was a strategy to reduce the overall consumption in the campus.

An overview of campus simulation model.
An overview of campus simulation model.

Consumption of electricity is a difficult notion to comprehend and convey. For example, when a switch is thrown, does one wonder where the electricity is generated from? It may so happen that a forest is being cleared in Chattisgarh so that you may be able to spend an extra hour on Xbox. Furthermore, we have an inherent expectation (if you grow up with some privilege,) that electricity “has” to flow if a switch is turned on. People who have no access to electricity are vulnerable in many ways to the extent that their social mobility may suffer due to lack of electricity. People who have intermittent access or pay huge bills are also cautions about consumption. Nevertheless, we seldom question the source of generation. 

Causal relationships like the one above between your consumption and environmental degradation are common and are uncomfortable (but true). Such examples try to guilt you into changing your consumption behaviour. However, it is not an easy to make lifestyle changes nor is it easy to ponder on the utility before doing everyday mundane tasks. Responsible use of electricity requires changes to behavioural and cultural practices as well as upgrades to the technical systems around us. Looking at both social and technological aspects was the cornerstone of our approach. 

We tried to look at the campus as a location which enables different people to achieve their academic goals. People in the campus perform various activities that allow them to achieve this goal. We looked at activities that consumed electricity. We then developed a simulation tool that assumed the use of sensor -based control and behavioural modification to try and check if a technology-assisted behavioural change was possible. The results of the simulation would be the base to design a serious game. The game in conjunction with sensor-based control systems would address both social and technological aspects of the issue.

Our simulation mainly consists of:

  1. a model for generating activities (explanation for what this activity means below) for various actors present on the campus,
  2. an agent based model for minimising electricity usage while keeping the comfort level of individuals at an acceptable level.

We define an activity as any action that an individual takes during the course of one’s day in the campus. A good way to model an activity is to collect detailed information using “energy dairies”. As a small academic institute, the campus had limited types of actors. We therefore chose to use a survey-based approach to collect information on daily routines. We conducted a survey to understand various daily routines for all the individuals on the campus. We also conducted interviews with some of the administrative and housekeeping staff.  We used this information to create a model for the generation of activities for various actors on the campus.

The smart campus simulation setup.
The smart campus simulation setup.

To model the “smart” systems of the campus, we created a control mechanism based on autonomous agents trying to collectively bring down the electricity consumption of the campus while keeping track of inhabitant’s comfort levels. We modelled the rooms and work areas as the autonomous agents. Each such agent was responsible for the operation of various devices that would consume electricity. It was then tasked with the objectives of minimising usage of certain devices by:

  1. negotiating the electricity consumption with other rooms (agents).
  2. Directing uses to use more common areas.
  3. Restricting when possible, the use of high power consumption devices such as air-conditioners and elevators.

In all of the above cases the it is assumed that the individual can override the agents, thus, keeping the human at the centre of the system.  (This also allows us to collect information on what sort of activities will not be compromised in the name of energy savings. ) However, a denial from the system to allow the operation of devices resulted in a decrease in the satisfaction of the inhabitants. The agents were asked to minimise the use of electricity with as little discomfort as possible for the inhabitants.

Once the models were ready we created a simulation tool and calibrated it based on the data collected by the campus for over a year on a daily basis. We could then play out scenarios such as:

  • What happens when we want to aggressively minimise consumption
  • or, what happens when the comfort for the inhabitant is paramount and
  • finally, what happens when we set a electricity consumption target for ourselves?
Calibration of the simulation, Real Data: Red, Simulated Data: Blue
Calibration of the simulation, Real Data: Red, Simulated Data: Blue

 

Results from using a aggressive savings scenario.
Results from using an aggressive savings scenario

 

Results from allowing a maximum savings scenario.
Results from allowing a maximum savings scenario
Results from using a popular choice for devices, scenario.
Results from using a popular choice for devices, scenario

It was very interesting for us to see the results and present it to the inhabitants of the campus. We are now trying to work with students to create and deploy the sensor systems at the campus. We see a potential for extending this tool to include larger spatial/network levels such as a neighbourhood or a set of neighbourhoods as opposed to a campus. We are also looking at including multiple sources of electricity, given that decentralised power and micro-grids can become popular. Furthermore, we are also exploring the possibility to include other resources such as water consumption and sewage as well into the analysis. For a more detailed description to the tool and to some other people doing similar work please refer to our paper “Krishna, Harsha, Onkar Hoysala, Krishna G. Murali, Bharath M. Palavalli, and Eswaran Subrahmanian. “Modelling technology, policy and behaviour to manage electricity consumption.” In Humanitarian Technology Conference (R10-HTC), 2014 IEEE Region 10, pp. 40-45. IEEE, 2014.”. We hope to produce and publish more results soon. In the meantime please free to check our tool at:The Smart Campus Simulation Tool

Understanding the complexity of energy systems with a simulation game

This post is by Dr. Émile Chappin, Assistant Professor of Energy & Industry, Delft University of Technology, and a Visiting Researcher at Fields of View. Dr. Chappin worked with us on developing a simulation game to understand to complexity of energy systems. These are his thoughts about the complexity of the sector and how a simulation game helps in understanding it.

 

Vibrant Electronics City sets the scene for three weeks of intensive research on serious gaming. We are driven by the need for stability and affordability of our energy supply – they are essential for flourishing societies. That’s the reason to deal with the nitty-gritty of typical European electricity markets in which billions of Rupees or Euros are at stake but where megawatts and megawatthours are easily mixed up. The key is not only in the details: electricity markets are complex systems, of which the performance is the result of the transactions in the market, the responses to the influences from outside, such as (proposed) policies, the evolving institutions and rational or irrational expectations.

 

This is where we start: how can we really learn to understand the essential workings of this system? The pure nature of complexity tells us that we can’t, really. But that’s not a satisfactory answer. We should do something that helps us – students, researchers, policy makers and companies – to gain better understanding of these systems. We need to start learning how we can somehow manage the system as a whole throughout the coming decades. Not in the classical sense of management, which presumes that some form of direct control is possible. We need to find new ways of shaping the system in a (more) desired direction. How? Join us in the world of simulation games!

We would like to share four insights we learnt from complexity and developing and using simulation games and models:

  1. The notion of optimality is void. There is no perfect outcome of this system/problem. Such judgments of the system state are observer-dependent, time-dependent and cannot be predicted. One can only speak of trajectories that appear desirable or not, given a set of strong assumptions, a time-frame, a set of objectives and a delineated system.

  2. Simulation and gaming should be used as tools for discussion. Because the system we’re observing is complex, any model we make and any simulation we run is definitively wrong. That, however, does not make them useless: they can be used as a digital laboratory, our laboratory in silico. By applying many modeling and simulation techniques capturing parts of the real-world system and its problems, and using those in a variety of relevant contexts, we may get a glimpse of understanding what patterns may emerge and how we can contribute in shaping the system [1]. That is the approach for TU Delft’s Energy Modeling Laboratory [2].

  3. Experience and involvement leads to deeper understanding. The complexity in the real-world system works in counterintuitive mechanisms and leads to patterns that are hard to really understand. Our experience shows that grasping some of these patterns by experiencing them in a serious game really helps to build an intuition for the consequences of the system’s complexity [1]. That in itself implies that lessons learnt – or patterns observed – may well contribute to understanding the complexity of the real world system and any effort in shaping the system accordingly. An example in our game is the understanding that ‘simple’ economic laws such as the notion of marginal cost bidding really work (at least to a certain extent). Other examples are the irrational response to soft information of future developments, the almost unbelievable developments on world markets for fuels, the wicked trade-offs between short-term profit, market share and the reliability and affordability of energy supply in the long run.

  4. Managing is the art to use the mechanisms that drive change. Understanding and exploring what the mechanisms are that drive our societal system is extremely difficult, if not impossible. Let’s consider this management that, making use of that, an art, an “attempt to bring order out of chaos” [3]. How to know what decisions matter, what actors matter and what outcomes matter? How to measure performance? How to measure change? To answer such questions, we need to bring together theory from various fields (history, engineering, multi-actor systems, complexity, economics, policy, design, etc.) and knowledge from application domains (energy, water, transport, IT).
    We hope that simulation and gaming contributes to this process. By doing so, we make the theory operational in specific domains: we ask questions such as how we can develop and maintain an affordable electricity sector which is both decarbonized and in which supply is secured. It helps us to define what change and stability really means and how we can measure it. That way we hope to find out how we may bring about changes that put our systems on a more desired trajectory. If we can manage our precious infrastructures – the backbones of our society – that may be how.

How can a three week trip to Bangalore help gaining insight in the Dutch electricity sector? Which countries – including their energy sectors – are more different than the Netherlands and India? Well… despite the fact that the Indian and the Dutch culture are fundamentally different, both societies show many communalities. Both India and the Netherlands are quite busy: at least traffic is a pain. The fraction of the Indian population that resides in Holland may not be so far apart from the fraction of Dutch people that are in India. What Indian food is, is impossible to define, as it is for Dutch food (although for different reasons). It is easy to complain about the weather – umbrellas are a requisite in your backpack. Dutch and Indians can express themselves in peculiar ways in English. Indians like chocolate and ‘stroopwafels’ as least as well as the Dutch. And… more often than not, we can meet each other in humor.

These commonalities show that the complexity of our societies does not mean we cannot try to understand and improve them. It means we need to find new ways of doing so. The mechanisms and laws probably do not work as we expect them to! There is only one way forward: dive in the deep, experience new things, debate with an open mind, challenge all assumptions, indulge in to cultural diversity, and… embrace complexity!

 

Literature

[1] Chappin, E. J. L. (2011). Simulating Energy Transitions, PhD thesis, TU Delft, the Netherlands. http://chappin.com/thesis

[2] Energy Modeling Laboratory, TU Delft. http://emlab.tudelft.nl

[3] Stephen Sondheim, composor and lyricist, 2005.

 

Of games, gaming simulation and piracy in games

One of my fellow researchers shared the following game with me:

http://www.greenheartgames.com/app/game-dev-tycoon/

Game Dev Tycoon™ is a business simulation game available for Windows, Mac and Linux as well as on the Windows 8 Store. In Game Dev Tycoon you replay the history of the gaming industry by starting your own video game development company in the 80s. Create best selling games. Research new technologies and invent new game types. Become the leader of the market and gain worldwide fans.

He found it really interesting,

“What happens when pirates play a game development simulator and then go bankrupt because of piracy?”: http://www.greenheartgames.com/2013/04/29/what-happens-when-pirates-play-a-game-development-simulator-and-then-go-bankrupt-because-of-piracy/
They ran an experiment where they released a pirated version of the game and saw how people reacted when during the simulation they ran out of money – because of piracy!

Interesting, yes. But the limitation of such games is that it is a game, as against a simulation.  An example of this effect is; most tycoon games simplify external effects as the more it is a simulation the less fun it can be. The tycoon style game play is a very popular design for  management/financial games (A close cousin is “Diner Dash” or “Farm Frenzy” which sheds light on logistics and functional parts of an organisation). Consider this, if you have played The Sims, you can find a job by simply using a computer in less than 20 seconds. But one can make an entire game out of the context of finding a job (in effect simulating the entire experience). Would you still be interested in playing The Sims if it simulates all the frustrations you experienced while finding a job?

Game Dev Tycoon simplifies the issues surrounding piracy and how it can be tackled to a great extent. Often the high price for ‘good’ games makes it inaccessible to a large audience. Some reasons for a high price may be:

  1. The game was developed using unrealistic targets. (Example: Duke Nukem Forever, no pun intended 🙂 )
  2. Games developed in mainstream  studios  Vs Indie studios

Some innovators in the field tackle piracy in the following ways  (instead of  slapping on a restrictive DRM):

  1. FTP (Free To Play) models offer a glimpse of the game before asking us to pay. The payment is usually a continuous nominal subscription versus a one time payment. The jury is still out on this. Example: LOTRO, Dungeons and Dragons, host or other games. Premium content for the players (enhancing their game-play and/or in game status) are also offered by such games.
  2. Innovative DRM systems in marketplaces  such as Steam and Uplay instead of an always on system (Example: The latest SimCity).
  3.   A low/high priced game followed by high/low paid DLCs (Downloadable Content). Example: Skyrim,  The Sims (Some DLCs for The Sims 3 is more expensive than the base game!).

Currently in Steam,  the beta version of the game is available at a lower price. The players test the game as they play beta versions and then get access to the full version for free when it is released. A very interesting experiment in reducing costs in the game development process and using the “crowd” for both testing and funding.

Musings on Solid Waste Management in Bangalore

The last couple of months have given us so many unique experiences which we never thought we would have during the course of our Industrial Engineering & Management degree. Working on our project on understanding networks in solid waste management has been an eye opener on so many levels. We are slowly, but surely coming to terms with the complexity of the garbage issue at hand in Bangalore.

 

The complete process of waste management is a complex one involving multiple systems and sub-systems. Through our project we aim to apply concepts and tools of Industrial Engineering like Network Optimization, Supply Chain Management and Simulation Modeling to analyze ways improve the process and provide a more systematic approach to addressing the problem. Our primary area of work is the optimization of transportation network in solid waste management which includes push carts, collection autos and trucks. We also aim to create a problem statement of the garbage situation through our findings throughout the project.

 

The garbage problem in Bangalore has become more evident since the irregular functioning of the three main garbage landfills leading to pile up of garbage at various points mainly on roads and empty sites. The coordination and organization of this process is poor and leads to pile-up of garbage at these pick up points whose location is chosen without appropriate planning. There is no synchronization or time management in the movement of the collection vehicles till the secondary point, and also of the trucks from this point to the landfills. Through the course of the project so far, we have interacted with the various stakeholders associated with the problem. From the Pourakarmikas to the officials to residents, we have tried to view the problem from various perspectives. Through these interactions we have obtained quite a few interesting details and insights.

 

 

Garbage collection point
Garbage collection point

 

The basic process of collection consists of dood-to-door waste collection by the auto-rickshaws. The autos consist of 1 driver and 2-3 collectors. Once the auto-rickshaws are done collecting, they go to one of the truck’s pick-up points and load the waste into the trucks. The dry-leaves and other waste left on the roads are collected by the Pourakarmikas using push-carts and those too are loaded into the trucks at the pick-up points.

 

In our first field observation at ward 19 (Sanjaynagar), in a casual talk with the driver of the garbage auto, we were told that no instructions were given to the drivers on what route he should take to complete the area assigned to him. We followed the auto and accompanied the collectors through the process. The BBMP had laid out a directive stating the incorporation of waste segregation at every house (into wet and dry waste). Our presence gave them a sense of empowerment as the residents took the collectors’ pleas to segregate the waste (as instructed by their supervisors), more seriously with us going along with them. Most residents on the other hand found the exercise of segregation pointless as they assume that all kinds of waste were mixed eventually in the garbage truck/compactor.

 

In another such chat with the same garbage truck driver, he mentioned his inability to cover all points of collection on certain days. The reason being, the truck overloads well before they could cover 75% of garbage pick-up points, at times leaving a pile of foul garbage until the next day/ trip. We also found differences in the actual number of vehicles (auto-rickshaws, trucks and push-carts) assigned for Solid Waste Management (SWM) in Sanjaynagar ward and the data provided in the BBMP SWM monitoring file[1].

 

These are few of many details and instances we have observed and recorded through the course of our work in Sanjaynagar ward. We hope to understand the problem in a deeper sense in the days to come.

 

 

This article is written by Anuj N.K, Akhil Sukumaran, Nandhakumar S, Kunal Vinayakya and Prateek Sultania, final year students at M.S Ramaiah Institute of Technology studying Industrial Engineering and Management. 


[1] www.bbmp.gov.in