Newsletter Dec Year 3, Issue 1

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1 Newsletter Dec Year 3, Issue 1 Contents: Overview of GreenCom Achievements 2 DSOs and Aggregator Energy Suppliers 3 Heat Pumps and the Grid 4 Home Context Awareness 5 About GreenCom 6 Project co-funded by the European Commission within the 7 th Framework Programme. Objective ICT Smart Energy Grids

2 Page 2 of 6 GreenCom Newsletter Year 3, Issue 1 Overview of GreenCom achievements The pilot setting for Green- Com is now fully expanded and is becoming an actual living lab on the island of Fur with approximately 800 citizens. PV systems, heat pumps and smart home plugs are some of the elements in the project that aims to create a balanced power grid by utilising flexibility in the relation between power production, power consumption and demand. Six substations have been chosen for the pilot on the island of Fur and each feeder is loaded by as many heat pumps and PV systems as possible. PV systems, heat pumps and smart home plugs have been installed in private households for testing in the area within the six substations. 15 heat pumps primarily air to liquid heat pumps - have been installed in the testing area. The project aims to control air to liquid heat pumps, currently seven heat pumps are extended with controlling equipment. The houses within the project are detached family houses located beyond collective supply. Prior to the project the households had oil or bio mass stoves, which have now been replaced with heat pumps. Thus the households are not only testing a smart grid of the future, they are also contributing to the green transition and energy savings. Battery testing and smart home plugs In the same area, PV systems have been installed in 22 households and five of these have recently had batteries installed. The solar panels have been delivered by EnergiMidt and are primarily installed with Kostal inverters, except for the houses with batteries. Here the inverters have been replaced with a Frontius inverter with built in battery control. The PV systems vary in size but are between 4 and 10 kwp. As part of the Home Monitoring and Control business model, 18 households have had smart home plugs installed. The smart home plugs have been installed on appliances such as washing machines, tumble dryers and dishwashers. The owners of all the households within the GreenCom project have invested in PV systems and heat pumps and have received grants worth 80 % from the Danish ForskEL foundation. All together, the citizens involved have invested approximately Euros in heat pumps and PV systems. During their involvement in the GreenCom project, the citizens lead normal everyday lives with cooking, laundry etc. Testing different business models The GreenCom project is trialling different business models within the different installations. Heat-as-a-Service (HaaS) is testing the possibilities for disconnecting or turning down the heat pump in periods with high load on the power grid especially in the hours between 5 and 8 pm. Some of the questions the project seeks to answer are how much energy you can accumulate in the household; if there is enough hot water, how the temperature in the house drops and whether or not the comfort level changes. The fundamental business idea is that the consumers are being economically rewarded for allowing full control of their heat pumps. The operation of the heat pump control is the subject of a contract between the consumer and a new type of energy supplier called an aggregator, establishing an agreed comfort level e.g. a minimum and maximum temperature. Another business model is trialling home monitoring and control (HMC) in order to test the effect of turning off or moving consumption for different energy consuming appliances within the households. In this business model, energy consumers are motivated by two aspects: To save energy and to shift load to get cheaper energy prices. This is achieved by installing a GreenCom home automation platform, which provides access to detailed, itemised energy consumption data for all their appliances. Integration of price signals with the automatic home control features allows the consumers to program automatic shift of load to periods, when the energy is cheapest. The system a) shows detailed consumption data for individual devices and allows the consumer to set up automatic control schemes for different purposes and b) enables control of devices according to price signals. The last business model: Get more out of your PV is testing different scenarios for storing PV produced energy on batteries in each household. On the one side the aim is to test the technical aspects in order to find out how the battery package can be used to help the DSO even out voltage and of capacity issues in the Micro Grid and what this flexibility is worth for the DSO. On the other side the business model s aim is to find out how much power from the solar panels can be used by the households and stored within the hour. Furthermore the project seeks to find out what the business case would look like for the customer when buying a PV system with a battery for storage. By Anne Brandborg EnergiMidt

3 Page 3 of 6 GreenCom Newsletter Year 3, Issue 1 Enabling Interaction between the DSO and the Energy supplier GreenCom features the Decision Support Dashboard, which helps Distribution System Owners (DSO s) to detect partial grid overloads and enables preventing these. Physical power grids face lots of challenges. Not only has the changing consumption of energy induced rapidly changing loads, but also the production of energy, which may depend on the current weather situation. With the Decision Support Dashboard, GreenCom offers a unique solution to easily evaluate the current status of the power grid, and to take action when it comes to critical load situations. This is achieved by enabling communication between the DSO and the Aggregator, who is a new type of energy supplier responsible for reducing loads in specific parts of the grid at certain times, and who is paid for that service by the DSO. Based on historical data, recent data, and recent influences like the weather, a recent load forecast for the power grid is calculated and displayed as an interactive map. This map enables the DSO to evaluate the current grid situation at a glance (Figure right). Furthermore it is possible to investigate specific parts of the grid (radials, transformer stations), and to see load predictions for these grid elements. Based on the status of the grid, the DSO can select parts of the grid that are possibly overloaded in the future. The DSO requests the Aggregator to shift load from the selected parts of the grid to later points in time for certain rewards. The Aggregator is supported by a reasoning logic, which determines whether the request may be fulfilled or not. Additionally, the human Aggregator can investigate the status of the grid and both the consumption and production of energy of the contracted houses (Figure below). If the given request is possible to fulfil, the Aggregator intervenes with the household technology without limiting user comfort and gets rewarded for this grid-protecting service by the DSO. By Sebastian Franken, Fraunhofer Institute for Applied Information Technology

4 Page 4 of 6 GreenCom Newsletter Year 3, Issue 1 Heat Pumps and the Grid Individual heat pumps are not a very commonly used term outside of our project at this time. However, legislation in several countries is driving a gradual take-up of this technology that will see your home gas boiler replaced by an electrically powered heat conversion device. On the face of it the term heat pump is not very interesting, however when you delve a little into the subject you will discover that not only will the technology allow for heating of your home in an extremely efficient manner, but it will also help you to heat your home in a very environmentally friendly manner. Heat Pumps are an important part of the picture that will help enable the large-scale switch to renewable energy sources and meet the challenges of the coming decades. In simple terms, heat pumps enable us to take latent heat energy from our environment (air or the ground) and boost it using heat exchangers to heat water or a given indoor space to required levels. Of course some electricity is required to run a heat pump but it will typically deliver 3-4 times the amount of energy that it consumes. From this arrangement everyone benefits; The consumer gets more cost effective heating of their homes, the aggregator is provided with flexibility A heat as a service contract (HaaS) maybe signed between an aggregator (a new type of energy supplier) and the consumer who hands over control of the heat pump to the aggregator. The level of control that the aggregator has is governed by the HaaS contract that determines maximum and minimum temperature limits to ensure adequate comfort for the consumer whilst giving the aggregator flexibility to manipulate the settings to best suit their needs based on actual and forecasted demand. From this arrangement everyone benefits; the consumer gets more cost effective heating of their homes and the aggregator is provided with flexibility enabling them to trade with other stakeholders based on better load balancing, voltage distribution and optimised energy exchange. For those interested in the technical details the interface for monitoring and control works as follows:- It comprises a USB/UARTto-RS485 converter and a MODBUS40 extension board & software (developed for NIBE heat pumps) that enables us to connect the heat pump to the gateway. The extension board prepares the MODBUS communications protocol for transportation via an RS485 link. In some cases, the heat pump is a distance away from the household so a wifi connection to link gateways at the heat pump and within the home can be used. The commands can be used to control internal parameters such as heat curve, operational mode and scheduled operations. We utilise the heating capacities of houses, the heating comfort intervals and the flexibility in the contract to determine the exact times for running the heat pumps. Various methodologies such as heating curves change the supply temperature of the device, depending on the outdoor temperature to provide a stabilised indoor temperature. Temperatures in various parts of the house can be captured using wireless sensors and fed to the gateway to finally meet required comfort levels. By Mike Hayes(Tyndall) and Niels Koldsø(Actua)

5 GreenCom Newsletter Year 3, Issue 1 Page 5 of 6 Context awareness and the Smart Home As you read this article, you know (more or less) where and how you are using your supplied electricity in your home (or office). You also know (more or less) how it will be used for the next couple of hours. To help deliver a smart grid that can work with fluctuating renewable energy sources, it would help a lot if you could now share this information with the grid! Understanding the current energy demand and being able to predict future demand is a key corner stone of work in Smart Grid projects. For GreenCom, we have been developing a system (an algorithm) that aims to do just that. The developed algorithm is based on a technique called Random Forest (RF). As Sensing & Control s Artificial Intelligence undergraduate Sergio Jurado puts it Predicting a future state opens up several possibilities in many fields, but first of all it requires thorough analysis of the current state and of multiple historical states before that. Smart Plugs, capture the data After several iterations, the algorithm is currently generating 24 hour lookahead predictions to an accuracy of 78%. That accuracy increases for the first few hours of a prediction and is steadily improving overall as the algorithm is supplied with even more data. Aside from supplying the Grid and our end users with a display of their predicted future consumption, we have extended this to cover local energy generation (solar panels) and have also used the results to generate advanced notification alerts. For instance, we can now alert an end user at any moment that they are consuming more energy than usual. Having achieved these results, we then pressed ahead with developing a way to calculate a current usage, or context prediction for a particular home. GreenCom Forecasted vs Real Consumption Random Forest scheme containing three different trees We are now able to do this and can assign one of the following states to a particular home: 1. ACTIVE MODE: In this mode it is considered that someone is at home. 2. InACTIVE MODE: All sensors are in standby and the movement sensor does not detect any change in the last hour. Therefore, it is considered that probably nobody is at home. 3. SLEEP MODE: Similar to InACTIVE mode but within typical sleeping hours. 4. ERROR STATE: None of the sensors assigned to an installation provide data. All in all, we have been very pleased with the data that we have received from our live pilot and with the results of our work to process this data. Future renewable energy supplies will be somewhat unpredictable, as will our own energy demands! Detailed understanding of our household energy needs, both now and in the future, will reduce one of these un-predictabilities. It can play a key role in the system that will help us all to benefit from a non-fossil fuelled energy supply and the cleaner environment that this delivers. By Richard Croyle and Sergio Jurado, Sensing & Control Systems S.L.

6 Page 6 of 6 GreenCom Newsletter Year 3, Issue 1 Further Information: Dr Maurizio A.Spirito Istituto Superiore Mario Boella Phone: spirito@ismb.it About GreenCom The GreenCom project is a 4.9 million Euro project of three years duration with the overall aim to balance the local exchange of energy at the community microgrid level to avoid instabilities in the centralised grid. The project is co-funded by the EU within the 7th Framework Programme, Objective ICT Smart Energy Grids and is developed by the following European partners: Istituto Superiore Mario Boella (Project Coordinator), Fraunhofer Institute for Applied Information Technology, Sensing & Control Systems, In-JeT ApS, Tyndall National Institute, University College Cork, ACTUA and EnergiMidt. For further information visit us at: or contact project coordinator: Maurizio Spirito, spirito@ismb.it We re on the Web! See us at: Project co-funded by the European Commission under the seventh Framework Programme Objective ICT Smart Energy Grids