In the subject of self-consumption there is a concept that we must never forget: energy efficiency. This efficiency must be understood from both the generation and consumption sides.
Let us first analyze efficiency from the point of consumer. It is evident that if my household consumes less electricity, the cost of my self-consumption facility will be lower. Are we taking any measure of efficiency for this to occur? A first step that can be taken is to reduce the consumption of lighting in the home. The change of halogen and low consumption bulbs by others of LED technology will allow us to reduce enough the electricity consumption in lighting. Another step that we can take is to replace our old appliances with others of class A +++ that have a lower level of consumption.
Efficient measures that are not always within reach of most budgets are to improve the isolation of our home. The insulation of the envelope of the building is fundamental. The use of insulation in facades, ceilings and floors and a suitable choice of windows can reduce the consumption of our building.
Other measures simply go through the change of habits in consumption that we must learn if we want to implement self-consumption in the home. The simple gesture of turning off light bulbs or electrical appliances that are not used, to avoid to leave electronic devices in stand.by (phantom energy) and to put the appliances in operation in the hours of the day when more energy is generated will allow an efficient management of our system. This can be done by implementing energy management software (EMS) in our home but it is an added cost.
If we are thinking about buying an electric car maybe this is the time to choose it with V2G (Vehicle to grid) technology with its Vehicle to Home (V2H) and Vehicle to Building (V2B) variants. This technology allows energy stored in an electric car to be injected into the electrical grid or to a dwelling or building using the car battery as an electrical storage system. In this way a better integration of renewable energies can be achieved in the electrical system.
Perhaps these measures will allow a home to consume only 1500 kw/h a year compared to the current 3000 kw/h of average consumption in Spain. This would reduce the cost of our self-consumption facility which would mean that many households will consider doing this installation in their homes.
From the point of view of the generation side, progress is being made by leaps and bounds. The efficiency of existing photovoltaic panels that use new materials with a longer useful life is very far from those manufactured 10 years ago and the price per w is lower, reaching values of 0.8 € per watt installed. Equally, the technology of the batteries makes them more efficient and with a greater durability supporting greater cycles of recharge and at a lower price.
And is the electricity grid ready for self-consumption? According to the operator of the Spanish electricity system the network is prepared for hundreds of thousands of self-consumers to enter the network.
What are the electric companies doing? Power companies are realizing that self-consumption will sooner or later arrive to settle permanently in each of our homes and that is the time has come to move ahead. Some companies start to market self-consumption kits, control systems or maintenance contracts that ensure a proper functioning of the system.
What is necessary so that everything starts to work? As easy as getting to an agreement point where distributors (power companies) begin to see prosumers (current users and future producers) as potential allies and non-competitors.
On the one hand, the electricity companies claim that the use of the distribution network should be paid not only by the current consumer but by the future producer and as we know these costs represent more than 50% of the current electricity tariff. But it is also true that companies are going to save the generation costs that are difficult to know at present.
But what would happen if a large number of users decide to become only their own power generators and definitely disconnect from the network? And it is then when the government enters and depending on the laws that apply and according to on whether they are advantageous for the consumer, the companies or both when the consumer decides.
Any processing plant – continuous, batch, hybrid – can improve its economic, safety and environmental indicators in two ways: improving its processing equipment or improving the control of those equipments.
The improvement of processing equipment is usually a task that requires large investments, since it almost always involves the acquisition of new processing equipment or in the best case requires expensive remodeling.
On the contrary, these performance indicators can be substantially improved through control, without, in the majority of cases, any investment in new technical means of instrumentation and control. This is because in practically all cases there is a wide margin to improve the performance indicators of a processing plant through its regulation.
The origin of this margin of improvement is multiple. The most common causes are: the control system is not well designed or tuned; due to ignorance or haste, all the benefits of the available control system are not used; the automaton programmer or the process engineer are not control experts; the dynamics of the processes under automatic regulation are not known with the required depth; the design of the plant has not been made under the integrated design approach.
Are also diverse and numerous actions that can be implemented to improve the performance of control loops without any investment and that we will review in next posts, such as: improve the tuning of the regulator, redesign the controller, implement anticipatory compensation of disturbances, enhance the tuning of cascade regulation loops, redesigning or re tuning the level controllers of the buffer tanks if necessary, using a control algorithm advanced available or supportable by the controller instrument, reducing couplings between loops, making a better assembly of the measuring probe, etc.
In its vast majority, the processing plants are automated under control structures (basic control, cascade control, split range control, selective control, coupled loops, etc.) based on the universal PID controller, in all its particularizations (P, PI, PD, PID, PI_D, etc.).
Despite its longevity and the development of multiple advanced control techniques, PID control maintains an overwhelming presence in the process industry.
Its extensive use in the industry is such that all the surveys known by the author conclude unanimously, in which more than 95% of the existing control loops are of the PID type. However, also many surveys conclude that a high percentage of the loops with PID control in the world, are operated in manual mode, while another similar percentage operates defectively. For example, as shown in the following figure, in [1] it is reported that only 16% of the PID regulation loops are optimally tuned and their performance is therefore excellent.
There is no doubt that in most cases, the incorrect or poor tuning of the controller can be the cause of the poor performance of the control loop or its irregularities in the operation.
However, it should not be forgotten that automatic regulation systems are holistic systems, and as such they must be analyzed as a whole and not only through the parts that compose them. That is why it is necessary to review the other components of the loop before deciding what action should be exercised on said loop.
Hence, the procedure of action in all cases, must begin with a field review of all the components of the loop (controller, process, actuator, measurer and communication channels), as well as an analysis of the possibility of coupling with other process loops.
The result of this first phase will determine what concrete action corresponds to perform to solve the poor performance of the automatic regulation loop.
CARTIF offers this service to optimize the performance of the regulation systems of processing plants. The optimization reduces the oscillations and the variability of the production plant, making the regulation system more accurate, faster, more stable and safer, and in this way improving its efficiency, safety, environmental impact and profitability.
In next post, the execution procedure will be described for each of the possible actions, starting with the simplest one, the re-tuning of the controller.
A little more than a year ago, in another post of this blog, our colleague Sergio Saludes already commented what is deep learning and detailed several of its applications (such as the victory of a machine based on these networks over the world champion of Go, considered the most complex game in the world).
Well, in these 16 months (a whole world in this topic) there has been a great progress in terms of the number of applications and the quality of the results obtained.
Considering, for example, the field of medicine, it has to be said that diagnostic toolsbased on deep learning are increasingly used, achieving in some cases higher success rates than human specialists. In specific specialties such as radiology, these tools are proving to be a major revolution and in related industries such as pharmaceuticals have also been successfully applied.
Autonomous vehicle driving projects, so in vogue these days, mainly use tools based on deep learning to calculate many of the decisions to be made in each case. Regarding this issue, there is some concern about how these systems will decide what actions to take, especially when human lives are at stake and there is already a MIT webpage where the general public can collaborate in creating an “ethics” of the autonomous car. Actually, these devices can only decide what has previously been programmed (or trained) and there is certainly a long way to go before the machines can decide for themselves (in the conventional sense of “decide”, although this would lead to a much more complex debate on other issues such as singularity).
Regarding the Go program discussed above (which beat the world champion by 4 to 1), a new version (Alpha Go Zero) has been developed that has beaten by 100 to 0 to that previous version simply knowing the rules of the game and training against itself.
In other areas such as language translation, speech comprehension and voice synthesis have also advanced very noticeably and the use of personal assistants on the mobile phone is beginning to become widespread (if we overcome the natural rejection or embarrassment of “talking” with a machine).
All these computer developments are associated with a high computational cost, especially in relation to the necessary training of the neural networks used. In this respect, progress is being made on the two fronts involved: much faster and more powerful hardware and more evolved and optimized algorithms.
It seems that deep learning is the holy grail of artificial intelligence in view of the advances made in this field. This may not be the case and we are simply looking at one more new tool, but theres is no doubt that is an extremely powerful and versatile tool that will give rise to new and promising developments in many applications related to artificial intelligence.
And of course there are many voices that warn of the potential dangers of this type of intelligent systems. The truth is that it never hurts to prevent the potential risks of any technology, although, as Alan Winfield says, it’s not just artificial intelligence that should be feared, but artificial stupidity. Since, as always happens in these cases, the danger of any technology is in the misuse that can be given and not in the technology itself. Faced with this challenge, what we must do is promote mechanisms that regulate any unethical use of these new technologies.
We are really only facing the beginning of another golden era of artificial intelligence, as there have been several before, although this time it does seem to be the definitive one. We don’t know where this stage will take us, but trusting that we will be able to take advantage of the possibilities offered to us, we must be optimistic.
The day all of us enjoy electricity dynamic prices thanks to the smart grid, we will see how the washing machine and other home appliances come into life. And they will do it to allow us to pay less for the energy they need to do their duties. This will be one of the advantages of dynamic prices that are those that change along the day to encourage us to use energy when there is a surplus and to dissuade us of using energy when there is a shortage.
To have a better understanding of how dynamic prices will impact on our lives, there has been a research project conducted in Belgium that involved 250 families equipped with smart home appliances, namely washing machines, tumble dryers, dishwashers, water heaters and electric car chargers. Smart home appliances are those that receive information about electricity rates and that can make decisions about their own operation. For the purposes of the project, the day was divided into six time slots with different electricity prices according to the energy market. The families involved in the experiment were divided into two groups.
Researchers of Liner Intelligent Networks project in a demostration
The first group got information about next day electricity prices through an app installed in a mobile device. Then, they have to plan the use of the appliance for the next day considering the prices and their needs.
The second group have appliances that reacted to the prices in an automated fashion while preserving the owners’ utility. To understand how it worked, imagine a family who wants to have their dishes ready for dinner at 6PM. At 8AM, when they left home to work, they switch on the washing machine and indicate the hour the dishes must be ready. In the case the washing machine needs two hour to complete the work, the machine knows it could start to work at some moment between 8AM and 4PM and it chooses the moment in the time slot with lower price. In the case the energy were cheaper after 4PM, the washing machine started to work at 4PM to assure the dishes were clean and dry at the moment the owners needed them. Other appliances, like the water heater, just chose the time slots with cheaper energy to keep water at desired temperature.
The customers in the first group found the system annoying and they left the experiment. However, those in the second group found the method did not affect their comfort and that their appliances preferred the night to work. Besides this, there was a reduction in the electricity bill: 20% for dishwashers, 10% for washing machines and tumble dryers, and 5% for water heaters.
One of the findings of the project was that customers do not like to be on the lookout of the next day prices. This result is quite surprising if we consider the success of the Opower company, that according to them they were capable of reducing the bill, energy use and CO2 emissions using a customer information system quite similar to the one used by the Belgians with the first group, the one based on getting information the day before to make decisions in advance. But today Opower is in the Oracle realm, maybe because this big company was more interested in the data and knowledge Opower had about how people demand energy than in the possible benefits for environment, electric grid and customers’ wallets. Anyway, it seems the original’s Opower spirit remains alive.
The smart grid will make possible our washing machines will be connected to the power company through Internet soon and it will be in charge of making decisions about when to work in order to reduce our electricity bill. After that, if the washing machine makers were able to design a machine capable of ironing the clothes our happiness would be complete.
The main interest of this event “Robocup” is the advances in development of service robots, whose goal is to help humans in their daily life
At the end of July it took place in Nagoya Japan RoboCup 2017, and for the first time, I had the great opportunity to participate in this competition which brings together roboticists from around the world. Currently, RoboCup is the world’s largest robotic competition (this year participated almost 500 teams from 50 different countries), looking at a proud history of 20 years, starting from one league of football-playing robots, to now also cover many application areas of robots, such as rescue, logistics, and also service robots in people’s homes (RoboCup@Home).
As part of the SQPReL team, a very international team integrated by members of the L-CAS (University of Lincoln) and the LabRoCoCo (University of Rome “Sapienza”), I participated in the RoboCup at Home league. In that league the robots must be able to perform different housework in order to try to help humans in their daily life. Maybe one day in the future, most of the population will have one of these kinds of robots at home.
After 6 days of hard work in Nagoya added to the previous 2 months of preparation, the team was very proud to have achieved a good 3rd place in the RoboCup@Home Social Standard Platform League.
Nice but, what is actually the Robocup and what is it for?
RoboCup born as an international joint project to promote AI, robotics, and related fields. An attempt to foster AI and intelligent robotics research by providing standard problems. One of the effective ways to promote science and engineering research is to set challenging goals and these kind of competitions promote to compare developments and collaboration between the research community. Focusing on the RoboCup@Home, this league aims to develop service and assistive robots with high relevance for future domestic applications.
And when is the future? Are there no robots able to perform these tasks yet?
These kinds of robots have had a major presence in research centers in the recent years, such as Sacarino, the robot designed by CARTIF. However, there are few applications where robots are part of our daily life activities due to the difficulty to evaluate service robot applications and to obtain feedback mechanisms aimed at improving the general performance of the robot. Benchmarking in robotics has emerged as a solution to evaluate the performance of robotic systems in a reproducible way and to allow comparison between different research approaches, and here is where appears RoboCup@Home providing benchmarking through scientific competitions.
RoboCup@Home use a set of benchmark tests to evaluate the robot abilities and performance in a realistic non-standardized home environment setting (it changes every year and is not known until the day before the competition). Focus lies on the following domains:
Navigation: path-planning and safely navigating avoiding (dynamic) obstacles.
Mapping: building a representation of a partially known or environment.
Person Recognition: detecting and recognizing a person.
Person Tracking: tracking the position of a person over time.
Object Recognition: detecting and recognizing objects in the environment.
Object Manipulation: the ability of grasping, moving or placing an object.
Speech Recognition: recognizing and interpreting spoken user commands.
Gesture Recognition: recognizing and interpreting human gestures.
Cognition: understanding and reasoning about the environment.
How are those ability evaluated?
The competition is organized in several tasks (host a cocktail party, act as a waiter in a restaurant, follow verbal commands given by a human) that must be accomplished by the robots autonomously. These tasks are integrated tests, thus each test comprises a set of functionalities that must be properly integrated to achieve good performance. However, the scoring system allows for giving partial credit if only a part of the test is achieved.
In a future post I will explain more in detail the tasks that were carried out this year during the competition and our team’s experiences.
Urban mobility is paramount to address cities’ sustainable regeneration due to the number of issues that derive from a non-sustainable and non-efficient urban transport strategy. Urban transport represents almost a quarter of all the EU transport CO2 emissions. Conventional fuel vehicles contribute to the 40% of the city pollution, leading both to environmental damage and severe illnesses.
The challenge is to identify and analyze the best strategies to introduce clean technologies within an urban environment aligning with the city transport plans and policies and complying with the citizens’ needs.
Valladolid city has a strong commitment with sustainable transport and electromobility, as it is inferred from the list of measures taken at city level and their participation in a number of smart city projects at national and European level.
One of the most remarkable ones is REMOURBAN (REgeneration MOdel for accelerating the smart URBAN transformation) that is implementing a number of actions with the aim of boosting even more the penetration of electric mobility in Valladolid city.
Before REMOURBAN:
The largest share of public city transport in Valladolid is covered by the buses fleet, which consists of 103 PLG fuelled, 46 biodiesel, and one hybrid (non plug-in) Additionally, there are currently 466 taxis operating along the city. Among them, there are several hybrids (non plug-in) and others PLG fuelled. There are also two FEV, the first one operating since December 2011.
Mobility actions to be deployed within REMOURBAN project:
Though not fully deployed, most of the foreseen actions are already in progress.
Five plugged-in hybrid buses have been in operation for one year now. Two of them have been partially funded through REMOURBAN project.
Two FEV cars belonging to the City Hall private fleet are also providing service.
Additionally, a set of 45 fully electric vehicles (taxis, last mile delivery and other private business) are expected to arrive soon. To achieve this ambitious target, the City Hall has launched an interesting offer to boost the adoption of electric vehicles by these professionals. Interested parties will be able to apply as long as they commit to monitor the performance of their electric vehicles and related charging infrastructure. In return they will be getting as much as 8.350€ along 24 months.
Charging infrastructure has also been duly considered and the 34 slow charging points currently available all along the city will be soon upgraded and integrated in a remote management system to allow for seamless and reliable monitoring. Moreover, new charging infrastructure is being put in place to ensure fast charging to the buses and last mile delivery vehicles. In this sense, two pantographs (120kW) have also been installed at the beginning and end of bus line 7, and are currently being commissioned. They will provide the required electricity for their batteries so as to cover the inner area of the city in fully electric mode. The charging process should take around 8 minutes.
The freight delivery vehicles will profit from a fast charging station (50kW) that will also be installed in CENTROLID logistics hub. Last but not least, 4 additional charging points (22kW, Schuko, Mennekes) will be installed to provide charging to the taxis (not exclusively).
Monitoring actions:
A local ICT platform, in Valladolid, will be managed by CARTIF and further on will feed a global one for the whole project. Everything is being currently set up in order to get ready to register data, both from vehicles performance and from charging processes once the vehicles are in place. This is expected to happen by the beginning of year 2018 and will allow for two years monitoring (as requested by the EC).
On-board Units (provided and installed by GMV) will be registering a number of variables (speed, electric instantaneous engine consumption, battery level, instantaneous auxiliary systems consumption, GPS, emissions, etc.) that relate only to vehicle performance while on route. Additionally, data from charging processes will be collected by a charging manager. This will consist of initial and final charging time, as well as related charging energy.
Information from each monitored vehicle will come from both sources (driving route and charging process). The related set of data will be anonymized and processed by the local platform.
The final aim is to get valuable knowledge from electric vehicles performance in real conditions. All lessons learnt and experience gained will be transferred to other cities willing to adopt these technologies.
