Need to get back into the habit of blogging!

I have been familiarising myself with a few techniques that are used in the paper "The use of constraint programming for the autonomous management of power flows":

• back tracking search - Search the tree by starting at the root and traversing in a depth first manner. At a particular node C, checks whether a valid solution can be computed from C, if not whole subtree is pruned. Obviously the hard part using a good approximation function that can calculate whether a valid solution exists.
• best first - explores the tree by expanding the most promising node chose according to a specific rule. A* search is an example.

I have implemented the DC power flow equations in matlab, they use considerably less code then the java implementation. Hopefully this matlab implementation will be used by CPLEX, a constraint optimisation solver, so that it can calculate the flow, however I am still working on expressing the problem in CPLEX language. 

In parallel to this I have been describing the model and the problem in mathematical terms, I have written a one page mathematical explanation of the constraints, the network and the variables defining their domains and bounds. This in theory will allow me to then translate it into any coding environment in order to implement it.

A selection of papers that I have read:

1. Dam KH van, Houwing M, Lukszo Z, Bouwmans I. Agent-based control of distributed electricity generation with micro combined heat and power: cross-sectoral learning for process and infrastructure engineers. Computers & Chemical Engineering. 2008;32(1-2):205-217. 

2. Taylor P, Xu T, McArthur S, et al., others. Integrating voltage control and power flow management in AuRA-NMS. In: SmartGrids for Distribution, 2008. IET-CIRED. CIRED Seminar.; 2008:1-4.

3. Pipattanasomporn M, Feroze H, Rahman S. Multi-agent systems in a distributed smart grid: Design and implementation. In: Power Systems Conference and Exposition (PSCE 2009).; 2009:1-8. 

4. Dolan MJ, Davidson EM, Ault GW, McDonald JR. Techniques for managing power flows in active distribution networks within thermal constraints. In: Electricity Distribution-Part 1, 2009. CIRED 2009. 20th International Conference and Exhibition on.; 2009:1-4.

I have implemented the same network as the one in the paper "The use of constraint programming for the autonomous management of power flows". However it does not specify any of the loads, and therefore I will not be able to recreate the exact experiments without them.

Next week I am putting the PhD on a one week hold to code full time on a project for BAE systems.

Back in Southampton

Back in Southampton now here is a summery of what I have been doing:
I have been focusing my attention on achieving a good understanding of how the electricity system works by reading a variety of books including 

1. Galvin R, Yeager K, Stuller J. Perfect power: how the microgrid revolution will unleash cleaner, greener, and more abundant energy. 1st ed. McGraw-Hill Professional; 2008.

2. Weedy BM, Cory BJ. Electric Power Systems. 4th ed. John Wiley & Sons; 2004.

3. Gonen T. Electric power distribution system engineering. 2nd ed. McGraw-Hill New York; 2007.

4. Chard FDLC. Electricity Supply: Transmission and Distribution. 1st ed. Longman Group Limited; 1976.

I have also been studying the paper:

1. Davidson EM, Dolan MJ, McArthur SDJ, Ault GW. The use of constraint programming for the autonomous management of power flows. In: 15th International Conference on Intelligent System Applications to Power Systems (ISAP 2009).; 2009:1-7.

with the intention of first recreating the results found in the paper and then applying a decentralised way to calculate power flow analysis. By the end of January the goal is to have a mathematical model of the various constraints and equations used and a set of experiments and results written up in a small two column style paper.

TODO this week

I have just had the second ORCHID meeting. In it we covered all the research people have been doing since the last meeting. I spoke only briefly about max-sum and the areas I have been researching. I have also attended a library training course where we learnt about all the different resources available to us at Southampton. TODO (This Week) : Read DPOP Paper "Distributed constraint optimization with structured resource constraints", read other max-sum papers, research funding opportunities for internships abroad, research variable clustering (GDL paper), research pseudotrees.

While testing the max-sum algorithm against an example in a paper. I found a discrepancy between the papers value for a particular message and my codes value for a particular message. I checked the value manually on paper and it was the same as my codes. I then showed Gopal and he confirmed that the maths that I had used was sound. I am going to check that the paper has made mistake at my supervisors meeting today (just to make sure that I have implemented the max-sum algorithm correctly). TODO: Continue implementation of the max-sum algorithm, Lecture 12:00, version 2 of Gantt Chart

Implementation of MAX-SUM part deux

Finished implementing max-sum yesterday. Been testing it to make sure that it has no bugs. Once this is done, I will knock up a quick viewer to show the max-sum algorithm working visually. TODO: Finish testing max-sum, start implementation of the viewer

Things went wrong

On Friday I accidentally deleted my code I had been working on last week. Although I hadn't written much of the actual max-sum code, I had all the nice functions in place that handled the message passing etc so is a bit of a bore to write again (it is good practise though) Over the weekend I read a paper "Decentralised Coordination of Mobile Sensors Using the Max-Sum Algorithm" here is my take on it:

Uses max-sum to monitor and predict the state of spatial phenomena using a team of mobile sensors. Identifies that some centralised solutions exist (Gaussian Processing) however not acceptable in this setting for security reasons as provides central point of failure. To coordinate sensors, want to choose a move that maximises the total value obtained by the agents. (i.e. the agents that are connected to eachother and thus their utilities depend on eachother). Straight forward max-sum is not suitable in this setting as computation of messages is a bottleneck. Therefore introduces two techniques that prune the size of the joint action space (i.e. Utility) 1. Action pruning algorithm: pre run before the max-sum, prunes states that can never be maximised 2. Joint action pruning algorithm: speeds up computation of the messages from function to variable, uses branch and bound. TODO: Continue coding the max-sum algorithm, go to a lecture at 14:00 on sustainable energy.

Implementation of MAX-SUM

Yeh its a horrible day in Southampton (what a surprise!) This week I have been implementing the MAX-SUM algorithm in java to get a feel for how it works. Even though I studied it in my masters year, implementing it has definitely made me understand the fundamentals more thoroughly. There was one aspect that I couldn't at first get my head around. It was how you calculate the max of multiple agents utilities and q messages. As you increase the number of agents connected to each other, you increase the dimensions of the resulting cube of values which you must maximise across. (Hypercube territory) Thankfully Alex was able to explain it to me with code. TODO: Finished the implementation of the max-sum algorithm, add a viewer so can see if its working

4 day training reflection

The four day intensive course has given me a number of useful skills that I will be using for the next three years, and probably beyond. The things that were really useful to me was the chance to give three presentations and get feedback. Other helpful areas were how to get the most out of your supervisors and how to make my routine of how I read and analyse papers even more useful.

Doing this course has allowed me to network with a number of other PhD students across a range of disciplines. I even have an idea about a possible collaboration with a civil engineer called Andrew Hamilton who is looking at traffic control using emerging technologies. One of his emerging technologies involved cars talking to each other. Immediately I talked to him about agents and how they could play a role in this for coordinating traffic. We swapped emails and will be talking soon about how to solve this problem when we have both researched our respective areas more thoroughly.

However being on this course has meant that this week I have achieved nothing for my PhD. TODO (next week): Implement the MAX-SUM algorithm and clustering variables on a factor graph.

monday morning

Today I spent most of my time finishing off the reading of "factor graphs and the sum-product algorithm". Oli and I also went through some more examples for the power systems lectures. TODO (for tomorrow): Read the BAE systems report on Smart Grids, Make a gantt chart for time up until the 9 month report, Go through the last question for power systems analysis.

maths

Today I have been trawling through the paper "The Generalized Distributive Law" to understand the maths behind the Max-Sum algorithm. The GDL is based on the "humble" distributive law [i.e ab + ac = a(b + c)] but generalised to other things, such as trees. The idea is that you decompose a problem into a set of smaller problems such that the complexity to solve the smaller problems is less than the complexity to solve the original function. Example f(x1, x2, x3), the complexity to solve this is dependant on all the variables, whereas if f(x1, x2, x3) = f(x1, x2) + f(x2, x3) the complexity is dependant on the maximum number of variables in the functions (in this case 2) therefore reducing the number of operations required to solve the problem. Ruben helped me to understand the basic concept of the GDL algorithm. The paper did contain some difficult maths which I got the general gist of, however I will need to go over this in more detail. TODO (tomorrow) : Read the second paper that Max-Sum is based on "Factor Graphs and the Sum-Product Algorithm"

monday morning

This week I shall be focusing on a lot of reading, surprise surprise! I was given another book to read by my supervisor Gopal called Perfect Power which details "how the microgrid revolution will unleash cleaner greener, and more abundant energy". TODO: Finish reading the current paper, and read another, go to the 14:00 lecture on sustainable energy, read some hot air, look at notes on conventional generation techniques.

interesting lecture

Had a lecture on power systems analysis today. It was quite interesting and gave me a few ideas of what could be done. For instance load factor (average power / peak power) could be taken into consideration when controlling a microgrid. The idea is that you want the load factor to be as close to 1 as possible, that way the fluctuations between supply and demand is reduced meaning that high cost generators, which allows peak demand to be satisfied, do not have to be used as much! This is difficult to achieve in a microgrid that contains alot of renewable generators and many loads, but this could be solved using agents. I am interested in this and will look into this area of agent based microgrid management. TODO: Print off some more papers to read, read one paper and make notes, explore load factor and load loss factor, read notes on power systems analysis, go to lecture at 12:00 (sustainable energy), read some hot air (for background knowledge).

computer set up

Finally set up the new computer, its a beastly quad core with 12 GB of RAM and two 22" monitors, veeeerrrry nice! TODO: Read two papers and make comments, download and print some of the papers suggested by Gopal, read some Hot Air.

the start of the week

Tried to go to the conventional generation technologies lecture today at 9am but the lecture was full and there were no chairs. Sorted out my ID card and now in the office getting ready to read a bunch of stuff. TODO : Read some more hot air, Read one paper and make notes, Go to the lecture at 14:00. Over the weekend I have been thinking about what sort of area of smart grid I want to look at. I definitely want to look at integration of microgenerators in a microgrid environment. I need to find the papers that I read for my 4th year research project and make notes on them.

induction

Today is the first part of my induction to the university and postgraduate research. It involves some talks by various important people and a tour of the university campus (in case I have forgotten where everything is :p) TODO: Other then that I am going to read two papers today, they are Multi-Agent Systems for Power Engineering Applications Part I and II (written by the IEEE Power Engineering Society's (PES) Intelligent System Subcommittee). These should give a great deal of background knowledge about how to apply agents to the smart grid environment. I will also be reading my daily dose of "Sustainable Energy - without the hot air" I suggest anyone and everyone to read this, available online http://www.withouthotair.com/

lectures

I have a couple of lectures today, one was at 9:00 (power systems) and the other is at 12:00 (sustainable energy). Both should provide a good background knowledge to the area of Smart grids and energy. TODO: Read and provide comments on two papers, go to the lecture at 12, read some more of hot air, hand in demonstrator form and hopefully set up the new pc.

tasks for the day

Got into the office about half an hour ago and have been getting ready to read all day. Got a selection of papers and a book on sustainable energy (without the hot air), so should be good! Hopefully the computer will come today so I can set up my working environment properly. Still, early days!