WORK PROGRESS AND ACHIEVEMENTS

Transcription

1 WORK PROGRESS AND ACHIEVEMENTS Grant Agreement number: Project acronym: Project title: Funding Scheme: Date of latest version of Annex I against which the assessment will be made: SmartHG Energy Demand Aware Open Services for Smart Grid Intelligent Automation Collaborative project Periodic report: 1st 2nd 3rd 4th Period covered: from 1 October 2013 to 30 November 2014 Name, title and organisation of the scientific representative of the project s coordinator: Project website address: Enrico Tronci Sapienza University of Rome Tel: Fax: tronci@di.uniroma1.it

2 Contents Executive Summary 7 Introduction 8 I Second Year Progress and Achievements 11 2 System Specifications 12 3 Design of Home Intelligent Automation Services (HIASs) Design and Development of Open Standard Internet-based communication between Home Devices and Intelligent Automation Services (IASs) Design and Development of Open Standard Internet-based communication between Intelligent Automation Services (IASs) Design and Development of the Home Energy Usage Modelling and Forecasting (EUMF) Service Design and Development of the Home Energy Bill Reduction (EBR) Service Design and Development of the Home Energy Usage Reduction (EUR) Service Design of Grid Intelligent Automation Services (GIASs) Design and Development of Database and Analytics (DB&A) Service Design and Development of Energy Demand Aware Price Policies (DAPP) Service Design and Development of the EDN Virtual Tomography (EVT) Service Design and Development of the Price Policy Safety Verification (PPSV) Service Design and Development of Open Standard Internet based Communication between Distribution System Operators (DSOs) and Intelligent Automation Services (IASs) Protocol Evaluation Evaluation of Energy Usage Modelling and Forecasting (EUMF) service Evaluation of Energy Bill Reduction (EBR) service

3 5.3 Evaluation of Energy Usage Reduction (EUR) service Evaluation of Demand Aware Price Policies (DAPP) service Evaluation of EDN Virtual Tomography (EVT) service Evaluation of Price Policy Safety Verification (PPSV) service Evaluation of Database and Analytics (DB&A) service Demonstration Hardware Deployment in Kalundborg Test-Bed Interfacing Kalundborg Distribution System Operator (DSO) with the project services Hardware Deployment in Minsk Test-Bed Interfacing Minsk DSO with the project services Dissemination and Exploitation Dissemination Plan Dissemination Activity Market Analysis Exploitation Plan

4 List of Acronyms API Application Programming Interface COP Coefficient of Performance DAPP Demand Aware Price Policies DAPP-H Demand Aware Price Policies for Homes DAPP-K Demand Aware Price Policies for Substation-Level Energy Storage Control 23 DB&A Database and Analytics DBService Database Service DSO Distribution System Operator DR Demand response EDN Electric Distribution Network EUMF Energy Usage Modelling and Forecasting EUMF-H Energy Usage Modelling and Forecasting for Homes

5 EUMF-K Energy Usage Modelling and Forecasting for Control EUR Energy Usage Reduction EUR-H Energy Usage Reduction for Homes EUR-K Energy Usage Reduction for Control EBR Energy Bill Reduction ESS Energy Storage System EVT EDN Virtual Tomography GIAS Grid Intelligent Automation Service HAN Home Area Network HECH Home Energy Controlling Hub HIAS Home Intelligent Automation Service IAS Intelligent Automation Service PEV Plug-in Electrical Vehicle PPSV Price Policy Safety Verification RESTful Representational State Transfer SaaS Software as a Service SE State Estimation

6 SEIL Smart Energy Integration Lab SMC SmartHG Market Controller TD Transmission and Distribution UC Use Case

7 Executive Summary The purpose of this document is to summarise second year SmartHG achievements. To this aim, we start this document by recalling SmartHG general objectives and motivations, namely to propose economically viable Intelligent Automation Services (IASs) able to minimise energy usage and cost for residential homes whilst optimising operations of the Electric Distribution Network (EDN). We present the general structure of the SmartHG workflow, and we illustrate the role of each WP and task in the project. Part I describes SmartHG project achievements for each WP and for each task in the WP. Such WP achievements are summarised in the following. WP2 has been completed on M12. WP3 and WP4 main achievements consist in organising SmartHG IASs in an integrated methodology, where Grid Intelligent Automation Services (GIASs) detect how EDN operations may be optimised, possibly proposing price policies to residential users, and Home Intelligent Automation Services (HIASs) enforce such price policies at the residential home level. WP5 and WP6 main achievement consists in showing that all SmartHG IASs are economically viable, which is the main objective of the SmartHG project. To this aim, WP6 main achievement consists in setting up the test-beds (Kalundborg in Denmark, Central District in Israel, IMDEA Smart Energy Integration Lab (SEIL) in Spain, plus Minsk in Belarus) used for the evaluation, whilst WP5 main achievement is the collection of the evaluation results for each IAS. WP7 main achievements consist in: i) the multiple dissemination activities (coordinated through a dissemination plan) carried out in the second year and ii) the description of the overall SmartHG exploitation plan, which has identified customers and a detailed exploitation plan for each of the SmartHG IASs, and also contains a market analysis showing profitability of the proposed exploitation plan. 7

8 Introduction SmartHG project focuses on developing economically viable Intelligent Automation Services (IASs) gathering real-time data about energy usage from residential homes and exploiting such data for intelligent automation pursuing two main goals: minimise energy usage and cost for each residential home, and support the Distribution System Operator (DSO) in optimising operation of the Electric Distribution Network (EDN). To this aim, SmartHG consists of four main pillars, as shown in Figure 1. In the following we discuss such pillars and how they have been embedded in the overall SmartHG architecture shown in Figure Internet-based open standard protocols enabling effective communication between: i) home devices (e.g., sensors, smart appliances, local generators, electric vehicles, energy storage) and SmartHG IASs; ii) SmartHG IASs and DSO software systems; iii) any pair of SmartHG IASs. This will enable development of hardware deviceindependent energy services, possibly on the basis of the services already available. In Figure 2, this enables both the global and local feedback. 2. User-aware SmartHG Home Intelligent Automation Services (HIASs) focusing on residential homes. Such services will measure home energy usage and local generation (e.g., from renewable sources), forecast it and actuate selected home devices (e.g., Energy Storage System (ESS), Plug-in Electrical Vehicle (PEV), and heat pump) in order to minimise the home energy bill and usage (local optimisation) with respect to a given price policy computed to attain global (EDN level) optimisation. In Figure 2, this enables the advice/actuation communication between HIAS (in green) and residential homes. 3. Demand-side aware SmartHG Grid Intelligent Automation Services (GIASs) focusing on the EDN. Such GIASs will compute individual (yet fair) price policies for each single home taking into account user preferences while optimising EDN operations. Grid safety for such price policies will be formally verified using modelchecking-based techniques. Furthermore, such SmartHG GIASs will increase grid reliability by estimating and controlling (using price policies) voltages and currents in internal unmonitored nodes of the grid. In Figure 2, this enables the communication GIAS (in red) and residential homes as well as DSOs. 8

9 4. SmartHG case studies in Kalundborg, Central District and Minsk will enable thorough technical, environmental and economical evaluation of project results. Resting on such pillars, the SmartHG core work-flow is shown in Figure 3. Namely, an iterative refinement process aims at providing increasingly better design and implementation for the project IAS, divided in those working on the residential home side (HIASs, in WP3) and those working on the DSO side (GIASs, in WP4). Such iteration is made possible by the continuous evaluation phase (WP5), which has the goal of determining if SmartHG IASs are economically viable as wanted. In order to perform a thorough and real-world evaluation, WP5 rests on the demonstration activities carried out in WP6. Such activities provide the evaluation phase with real data coming from the Kalundborg and Central District test-beds (in the third year, data from Minsk should also be available). Moreover, such activities also allows us to test on real power electronics the IASs which interact with smart devices, by using the IMDEA Smart Energy Integration Lab (SEIL). Furthermore, networking with other project (in the dissemination activities of WP7) and detailed exploitation plans (in the exploitation activities of WP7) are also used to enhance IASs design and evaluation. Finally, the management phase monitors the overall work-flow, in order to guarantee high quality results. Figure 1: The four SmartHG pillars This document summarises the main achievements of this project iteration. Further details about achievements, approach followed to obtain such achievements, and experimental results (when applicable) can be found in the SmartHG second year deliverables. Each chapter of this document contains references to deliverables where such information can be found. 9

10 Figure 2: The SmartHG architectural control schema Figure 3: General SmartHG work-flow 10

11 Part I Second Year Progress and Achievements 11

12 WP 2 System Specifications This WP has been completed on M12. 12

13 WP 3 Design of Home Intelligent Automation Services (HIASs) The activities carried out in the second year inside Work Package WP3 target the design (see Deliverable D3.2.1) and the implementation (see Deliverable D3.2.2) of the HIASs, i.e., of those SmartHG Intelligent Automation Services (IASs) which work on the residential user side. For the second year, such design has been driven from insights coming from the first year evaluation of such services, as well as with networking between SmartHG partners and other national and international projects on the same topics. The achievements we obtained on such HIASs design and implementation are the following. The Energy Usage Modelling and Forecasting (EUMF) service has been split in two different services, Energy Usage Modelling and Forecasting for Homes (EUMF-H) and Energy Usage Modelling and Forecasting for Control (EUMF-K), in order to accommodate different requirements arisen in the second year. Namely, a shortterm forecasting service to be used by other services (EUMF-K) and a long-term forecasting service to be used by residential users (EUMF-H). The Energy Usage Reduction (EUR) service has been split in two different services, Energy Usage Reduction for Homes (EUR-H) and Energy Usage Reduction for Control (EUR-K), in order to accommodate different requirements arisen in the second year. Namely, EUR-H evaluates efficiency of electricity usage of electrical appliances in a given home and EUR-K estimates home thermal insulation and capacitance from measurements of temperature and heat pump electric consumption. The Energy Bill Reduction (EBR) service has been re-designed so as to directly drive selected home appliances (i.e., the Energy Storage System (ESS) and the Plug-in Electrical Vehicle (PEV)), in a way which is transparent to residential users. 13

14 Part I Second Year Progress and Achievements A working prototype for the Home Energy Controlling Hub (HECH), able to collect information from smart meters and send it to the Database and Analytics (DB&A) service, has been completed by using a Raspberry Pi. All HIASs have been made available as Web services, which either allow the download of the object code to be used at the user premises (for EBR and EUMF-K) or follows the Software as a Service (SaaS) paradigm (all other HIASs). This also allowed us to propose, in WP7, a detailed quantitative exploitation plan for each HIAS. All SaaS Web services developed above have been based on the Representational State Transfer (RESTful) paradigm, allowing access not only to human users, but also to other IASs, thus allowing IAS-to-IAS communication. The following sections outline the work carried out in WP3 and described in Deliverables D3.2.1 and D The tasks planned for the second year activity for WP3 are summarised in Table 3.1. Task Title T3.1 Design and Development of Open Standard Internet-based communication between Home Devices and IASs T3.2 Design and Development of Open Standard Internet-based communication between IASs T3.3 Design and Development of the Home EUMF Service T3.4 Design and Development of the Home EBR Service T3.5 Design and Development of the Home EUR Service Table 3.1: WP3 second year tasks (Deliverables D3.2.1 and D3.2.2) Task 3.1. Design and Development of Open Standard Internetbased communication between Home Devices and Intelligent Automation Services (IASs) In this year iteration of this task, we have realised a second prototype of the HECH by using a Raspberry Pi communicating on one side with home devices and on the other side with the DB&A for storing measurements. Home devices have been supplied by Develco Products. In particular: ZigBee wall plugs, and gateways to communicate with a dedicated server (SmartAMM, also developed by Develco Products) to read measurements from wall plugs. Moreover, new open protocols for secure communication have 14

15 Part I Second Year Progress and Achievements been designed, based on a Home Area Network (HAN) constructed from a ZigBee mesh network. Task 3.2. Design and Development of Open Standard Internetbased communication between Intelligent Automation Services (IASs) In order to allow communication between IASs, we have split all SmartHG services into two categories: (i) IASs without real-time requirements (DB&A, EDN Virtual Tomography (EVT), Price Policy Safety Verification (PPSV), Demand Aware Price Policies for Homes (DAPP-H), EUR-H, EUR-K, and EUMF-H), and (ii) IASs with real-time requirements (Demand Aware Price Policies for Substation-Level Energy Storage Control (DAPP-K), EBR, and EUMF-K). In order to realise efficient and effective communication for (i), we designed and implemented a RESTful service for each IAS without real-time requirements. As for (ii) communication directly takes place on the user premises, since such services allow the authorised user to download their objective code and execute it locally. Task 3.3. Design and Development of the Home Energy Usage Modelling and Forecasting (EUMF) Service In the second year of the SmartHG project, the Energy Usage Modelling and Forecasting (EUMF) service has been split in two new services, EUMF-K and EUMF-H. Namely, EUMF-K is a service to be used by real-time services such as EBR and DAPP-K for short-term forecasting, whilst EUMF-H is a SaaS service providing possibly long-term forecasting to human users. More details on this architecture restyling can be find in Deliverable D Both EUMF-K and EUMF-H have been designed and prototyped. EUMF-K covers a lack of the first year EUMF service, in order to provide a forecasting to real-time IASs. EUMF-H consisted in completing and improving the algorithms on which its first year ancestor EUMF relied upon. This included a new thermostatic model, able to improve consumption forecasting and to provide new information to the EUR-H service. Task 3.4. Design and Development of the Home Energy Bill Reduction (EBR) Service The second year iteration of design and prototype of the Energy Bill Reduction (EBR) service went through a complete re-design w.r.t. the first year version. Namely, the first year version of EBR consisted in a plan describing how to turn on/off the home appliances. It was the residential user responsibility to apply this plan, so as to minimise 15

16 Part I Second Year Progress and Achievements the energy bill. In this second year, the EBR directly drives selected home appliances (i.e., the ESS and the PEV), in a way which is transparent to the residential users. This results in a more usable and reliable service. Task 3.5. Design and Development of the Home Energy Usage Reduction (EUR) Service The second year iteration of design and prototype of the EUR service has been split in two new services, EUR-K and EUR-H. EUR-K takes as input sensor measurements about indoor and outdoor temperature and heat pump electric consumption, and estimates home average thermal insulation and capacitance. From the home external surface area, we can compute the home average U-value. Using such data and the heat pump Coefficient of Performance (COP), EUR-K supports home users in increasing home energy efficiency. This is done by evaluating trade-offs among home retrofits decreasing U-value and retrofits increasing heat pump COP. EUR-H explores methods to estimate overall energy efficiency of the electrical appliances in a given home. 16

17 WP 4 Design of Grid Intelligent Automation Services (GIASs) The activities carried out in the second year inside Work Package WP4 target the design (see Deliverable D4.2.1) and the implementation (see Deliverable D4.2.2) of the GIASs, i.e., of those SmartHG Intelligent Automation Services (IASs) which work on the Distribution System Operator (DSO) side. For the second year, design has been driven from insights coming from the first year evaluation of such services, as well as with networking between SmartHG partners and other national and international projects on the same topics. The achievements we obtained on design and implementation of GIASs are the following. EDN Virtual Tomography (EVT), Demand Aware Price Policies (DAPP) and Price Policy Safety Verification (PPSV) offer now an integrated approach for improving Electric Distribution Network (EDN) usage, by exploiting the EDN hierarchy induced by EDN substations interconnection (see Figure 4.1). Such an approach works as follows: 1. EVT is used to help DSO to define desired power profiles on each EDN substation; 2. for each EDN substation s, DAPP computes individualised price policies for residential users connected to s, so that the requirements on the desired power profile for s computed above is met; 3. for each EDN substation s, PPSV evaluates safety of s under the assumption that residential users are allowed to probabilistically deviate from their price policies; 4. results of PPSV are collected and their effect on the entire EDN are evaluated by using again EVT. The DAPP service has been split in two different services, Demand Aware Price Policies for Homes (DAPP-H) and Demand Aware Price Policies for Substation- Level Energy Storage Control (DAPP-K), to be used in two different scenarios: 17

18 Part I Second Year Progress and Achievements EDN configuration! Network readings Services EVT Operational! constraints Network! state! estimation EDN DSO Network! measurements Tariffs! User demand DAPP Retailer Price policies! User demand Price verification process Operational constraints Verification outcome Price policies Figure 4.1: The proposed GIASs architecture. PPSV DAPP-H is used when peaks in the aggregated residential users demand have to be handled in a Demand response (DR) approach (as in the integrated approach discussed above), whilst DAPP-K is used when demand peaks have to be handled with an Energy Storage System (ESS) installed on an EDN substation. Moreover, DAPP-H has been designed on the assumption that Energy Bill Reduction (EBR) will be installed on residential homes to directly control given appliances, thus making price policies transparent to residential users. Finally, we also compute users flexibility required by a price policy, in order to make it more contractually clear. The PPSV service has been re-designed so as to enable both a safety verification (by performing, with a parallel algorithm, a sort of robustness analysis) and an economic evaluation of the effect of individualised price policies output by DAPP-H, in order to provide an economic evaluation of the whole integrated methodology discussed above. The EVT service has been greatly improved in its internal algorithm. The design of each GIAS has driven the development of the corresponding prototype. This allowed us to perform, in WP5, the evaluation of all GIASs by using such prototypes. All GIASs have been made available as Web services, which either allow the download of the object code to be used at the user premises (for DAPP-K) or follow the Software as a Service (SaaS) paradigm (all other GIASs). This also allowed us to propose, in WP7, a detailed quantitative exploitation plan for each GIAS. 18

19 Part I Second Year Progress and Achievements All SaaS Web services developed above have been based on a Representational State Transfer (RESTful) service, allowing access not only to human users, but also to other IASs, thus allowing IAS-to-IAS communication. The following sections outline the work carried out in WP4 and described in Deliverables D4.2.1 and D The tasks planned for the second year activity for WP4 are summarised in Table 4.1. Task Title T4.1 Design and Development of Database and Analytics (DB&A) Service T4.2 Design and Development of Energy DAPP Service T4.3 Design and Development of the EVT Service T4.4 Design and Development of the PPSV Service T4.5 Design and Development of Open Standard Internet based Communication between DSOs and IASs Protocol Table 4.1: WP4 second year tasks (Deliverables D4.2.1 and D4.2.2) Task 4.1. Design and Development of Database and Analytics (DB&A) Service The DB&A service has been re-defined to embrace two services: i) Database Service (DBService), which primarily provides measurement data coming from the Home Energy Controlling Hubs (HECHs) to the other IASs, through RESTful Application Programming Interfaces (APIs); ii) SmartHG Market Controller (SMC), which is responsible for the delegation of access. Furthermore, there has been a complete re-design of the DBService (formerly known as DB&A) and the SMC based on set of requirements and Use Cases (UCs). This has been done in such a way that there is a link between a certain feature and user requirement, which ensures traceability when implementing the prototype. The new design is able to handle different types of users and store/provide measurement data more targeted towards services that analyse power and energy. Task 4.2. Design and Development of Energy Demand Aware Price Policies (DAPP) Service The DAPP service has been re-designed so as to embrace two different services. Namely, DAPP-H (Figure 4.2) is the direct evolution of first year DAPP, whilst DAPP-K (Figure 4.3) is a new service developed to control an ESS installed on an EDN substation. 19

20 Part I Second Year Progress and Achievements Figure 4.2: DAPP-H input and output. Figure 4.3: DAPP-K input and output. Such services have to be employed in two different scenarios: i) DAPP-H is to be used when the DSO does not want to change the configuration of EDN substations, and instead wants to shift residential user demand by proposing individualised price policies (we recall that price policies are individualised so as to avoid peak rebounds); ii) DAPP-K is to be used when the DSO aims at fulfilling residential users demand as it is, by counteracting demand peaks with ESS installed at each EDN substation (or the more overloaded ones). Furthermore, the DAPP-H service has been re-designed w.r.t. the previous DAPP service. Namely, we clarified our deployment setting as follows: DAPP-H output is still a set of individualised price policies, one for each residential user connected to a given substation. However, it is not the residential users responsibility to actually follow the given price policy: to this aim, we assume that each residential user has the EBR service installed. Since EBR automatically drives selected user appliances, without sending information to the DSO (which would not be accepted by the residential user), with this setting we achieve our task objectives. Moreover, the DAPP-H service now computes individualised price policies which are more clear from a contractual perspective. To this aim, the users flexibility (i.e., how much the user has to deviate from the habits in order to follow the price policy) is also computed and returned. Finally, both DAPP-H and DAPP-K have been made available as Web services. In the former case, users (i.e., DSOs) may access DAPP-H using the SaaS paradigm (i.e., upload the input, invoke an execution, wait and then download/visualise the output), whilst for DAPP-K the Web service allows to download the object code to be used to control the substation ESS. Task 4.3. Design and Development of the EDN Virtual Tomography (EVT) Service The EVT service has been enhanced so as to include a fully-functional State Estimation (SE) system, developed basing on detailed recordings from the Kalundborg test site EDN. This SE system has the capability to detect various types of bad data which can 20

21 Part I Second Year Progress and Achievements occur due to metering or communication errors, and to replace erroneous or missing input data with reliable estimates. Furthermore, demand forecasting techniques have been developed in order to forecast electricity demand profiles at the distribution substation level. Such demand forecasts are important as an input to the SE, and also for the EVT to provide early warning of potential network issues, and generate recommendations and advices for the DSO. Finally, EVT have been made available as a Web service, following the SaaS paradigm (i.e., upload the input, invoke an execution, wait and then download/visualise the output). Task 4.4. Design and Development of the Price Policy Safety Verification (PPSV) Service The PPSV service has been re-designed so as to enable both a safety verification (by performing a sort of robustness analysis) and an economic evaluation of the effect of individualised price policies output by DAPP-H. To this aim, the safety verification algorithm has been based on the first year version of PPSV, enhanced by designing and implementing a parallel algorithm which allows execution of PPSV on a daily basis. The economic evaluation has been introduced in this second year by enabling PPSV to return 24 probability distributions (one per each hour of the day) on the aggregated power demand, instead of just one probability distribution as in the safety verification. Such economic evaluation, which has the objective of validating the full EVT-DAPP- PPSV chain for an economic perspective, has to use data from longer periods, i.e., one year. Finally, PPSV have been made available as a Web service, following the SaaS paradigm (i.e., upload the input, invoke an execution, wait and then download/visualise the output). Task 4.5. Design and Development of Open Standard Internet based Communication between DSOs and Intelligent Automation Services (IASs) Protocol A design methodology for IASs has been developed to model, simulate, and evaluate DR communication protocols together with DR strategies for smart grids applications. This provides us with a formal way to describe, model, and synthesise a DR communication protocol combined with user scenarios. 21

22 WP 5 Evaluation The activities carried out in the second year inside Work Package WP5 target evaluation of all SmartHG Intelligent Automation Services (IASs) (see Deliverable D5.2.1). For the second year, our evaluation has been driven from insights coming from the first year evaluation, as well as with networking between SmartHG partners and other national and international projects on the same topics. We set up two common reference scenarios, based on the Kalundborg and the Central District test-beds. All services (except for Database and Analytics (DB&A), for which only a testing phase was required) have been evaluated in at least one of such reference scenarios. For Energy Usage Reduction (EUR) and Energy Usage Modelling and Forecasting (EUMF), also the Minsk scenario has been used. Our technical evaluation shows that all IASs have CPU time and RAM usage compatible with their intended use. Our economic evaluation estimates the economic saving for the Distribution System Operator (DSO) due to peak shaving of the aggregated demand at the substation level. This of course is a complex matter. We take the conservative approach of underestimating Transmission and Distribution (TD) costs due to demand peaks by only considering average costs arising from the need to replace a substation transformer, before its nominal lifetime, due to overloading stemming from demand peaks. We base our TD investment deferral evaluation on the probability that such an event occurs. The following sections outline the work carried out in WP5 and described in Deliverable D The tasks planned for the second year activity for WP5 are summarised in Table 5.1. Task 5.1. Evaluation of Energy Usage Modelling and Forecasting (EUMF) service Following the objectives for this task, the Energy Usage Modelling and Forecasting for Homes (EUMF-H) and Energy Usage Modelling and Forecasting for Control (EUMF-K) services have been evaluated, from the technical perspective, on all the available project test-beds: Kalundborg and Central District (for EUMF-K) and Minsk (for EUMF-H). 22

23 Part I Second Year Progress and Achievements Task Title T5.1 Evaluation of EUMF service T5.2 Evaluation of Energy Bill Reduction (EBR) Service T5.3 Evaluation of EUR Service T5.4 Evaluation of Demand Aware Price Policies (DAPP) Service T5.5 Evaluation of EDN Virtual Tomography (EVT) Service T5.6 Evaluation of Price Policy Safety Verification (PPSV) Service T5.7 Evaluation of DB&A service Table 5.1: WP5 second year tasks (Deliverable D5.2.1) To this aim, we ran the services using data from selected homes and, once obtained the output forecast for power demand, we compared it with the actual power demand, which was known. As a result, forecasting errors are most of the times below 50%. As for EUMF-H, this evaluation is also valid for Energy Usage Reduction for Homes (EUR-H), as these two are considered as an integrated service in our evaluation. As for EUMF-K, which is used by Demand Aware Price Policies for Substation-Level Energy Storage Control (DAPP-K) and EBR, we also made an indirect evaluation, by comparing results of the causal execution (i.e., based on forecast output by EUMF-K) of DAPP-K and EBR with the results of the non-causal execution of the same services (i.e., in this case EUMF-K is replaced by an oracle which is able to correctly forecast user power demand, by using known home historical data). As a result, by using the oracular forecasting services DAPP-K only improves the final saving in one year of 60% on average, and EBR only improves by the 35%. This shows the technical soundness of the EUMF service. Task 5.2. Evaluation of Energy Bill Reduction (EBR) service Following the objectives for this task, the EBR service has been evaluated, from the technical perspective, on the Kalundborg and Central District scenarios. To this aim, we ran the service using data from two selected homes. In order to make the evaluation as close as possible to the real usage scenario, each run was performed twice, once on the Home Energy Controlling Hub (HECH) (as EBR will have to be run on the HECH once deployed) and once on a workstation at the IMDEA Smart Energy Integration Lab (SEIL) (in order to test EBR commands for Energy Storage System (ESS) and Plug-in Electrical Vehicle (PEV) on real power electronics). As for the economic evaluation, we compared the energy bills to be paid in one year with and without using EBR on the same homes as above. By also considering the 23

24 Part I Second Year Progress and Achievements amortisation of the average cost of a battery, we were able to show that by using EBR for 10 years, residential users can save up to 1,470 EUR in the Kalundborg scenario, and up to 11,500 EUR in the Central District scenario. Task 5.3. Evaluation of Energy Usage Reduction (EUR) service Following the objectives for this task, the EUR-H and Energy Usage Reduction for Control (EUR-K) services have been evaluated, from the technical perspective, on all the available project test-beds: Kalundborg and Central District (for EUR-K) and Minsk (for EUR-H). To this aim, as for EUR-H, its evaluation is embedded in the one for EUMF-H, which uses EUR-H to enforce its forecasting. As for EUR-K, we showed that it is able to generate suggestions on how to modify either the home insulation, the heat pump or the user habits in order to reduce energy consumption of the home heat pump. This shows the technical soundness of the EUR service. Task 5.4. Evaluation of Demand Aware Price Policies (DAPP) service Following the objective for this task, the DAPP-K and the Demand Aware Price Policies for Homes (DAPP-H) services have been evaluated, from the technical perspective, on the Kalundborg scenario (as it is the only one providing information for Electric Distribution Network (EDN) substations). To this aim, we selected an EDN substation with 62 homes, and we tripled each home so as to obtain an EDN substation with 186 homes, for which the aggregated residential user power demand may exceed the substation safety threshold. Then, we ran both services on such a scenario. As a result, DAPP-K and DAPP-H turned out to work correctly. Our economic evaluation of DAPP-H shows that, in the Kalundborg scenario, if residential users strictly follow DAPP suggested power profiles, then the DSO can save, on average, 0.6 EUR per residential user per year due to TD investment deferral. Residential users themselves can save, on average, about 150 EUR per year (considering a 10-year amortising plan for storage device costs). Even though peak shaving of aggregated demand can be at variance with reduction of electrical energy costs (arbitrage) and/or CO 2 emission reduction, our evaluation on Kalundborg test bed data shows that DAPP-H allows the energy supplier to save about 0.8 EUR per residential user per year and to reduce CO 2 emission by about 5 Kg per year per residential user. As for DAPP-K, this service has turned out to be not economically profitable (to date) in the Kalundborg scenario, when the ESS cost is considered. We identified future scenarios (e.g., with lower ESS costs) for which DAPP-K can be economically profitable. Even though peak shaving of aggregated demand can be at variance with reduction of CO 2 emissions, our evaluation on Kalundborg test bed data shows that DAPP-K reduces CO 2 emissions by, on average, 7 Kg per year per residential user. 24

25 Part I Second Year Progress and Achievements Figure 5.1: EVT technical evaluation: before corrective actions on Kalundborg scenario. Figure 5.2: EVT technical evaluation: after corrective actions on Kalundborg scenario. Task 5.5. Evaluation of EDN Virtual Tomography (EVT) service Following the objectives for this task, the EVT service has been evaluated, from the technical perspective, on the Kalundborg test-bed (the only one containing information for the whole EDN). To this aim, we ran the service using data from the Kalundborg EDN in the worst scenario. Results are reported in Figures , before and after application of corrective actions returned by EVT. This shows the technical soundness of the EVT service. Task 5.6. Evaluation of Price Policy Safety Verification (PPSV) service Following the objective for this task, the PPSV service has been evaluated, from the technical perspective, on the same scenario used for DAPP-H, i.e., the one obtained from the Kalundborg test-bed. By using PPSV, we estimated economic and environmental savings also when residential users may deviate (on a probabilistic basis) from the power profiles proposed by DAPP-H. As a result, we have that the DSO can save about 0.53 EUR per residential user per year due to TD investment deferral. Even though peak shaving of aggregated demand can be at variance with reduction of electrical energy costs (arbitrage) and/or CO 2 emission reduction, our PPSV evaluation shows that DAPP-H price policies allow the energy supplier to save about 1.2 EUR per year per residential user, and to reduce CO 2 emissions by about 11.2 Kg per year per residential user. 25

26 Part I Second Year Progress and Achievements Task 5.7. Evaluation of Database and Analytics (DB&A) service Following the objectives for this task, the DB&A service has been evaluated, from the technical perspective, by preparing and executing a testing plan. After some iterations involving error discoveries and corrections, all tests passed. This shows the technical soundness of the DB&A service. 26

27 WP 6 Demonstration The following sections outline the work carried out in WP6 and described in Deliverable D The tasks planned for the second year activity for WP6 are summarised in Table 6.1. Task Title T6.1 Hardware Deployment in Kalundborg Test-Bed T6.2 Interfacing Kalundborg Distribution System Operator (DSO) with the project services T6.3 Hardware Deployment in Minsk Test-Bed T6.4 Interfacing Minsk DSO with the project services Table 6.1: WP6 second year tasks (Deliverable D6.2.1) Task 6.1. Hardware Deployment in Kalundborg Test-Bed We completed deployment of sensing devices for appliances and main in 20 homes in Svebølle (Kalundborg, Denmark) out of the 25 planned in the project. We also exploited IMDEA Smart Energy Integration Lab (SEIL) to reproduce energy demand and generation for any home in the test-bed. More specifically, we used electronic loads to reproduce the (recorded) energy demand, generators to reproduce the (recorded) local generation and batteries to investigate the effect of energy storage (e.g., from batteries or Plug-in Electrical Vehicle (PEV)) on the overall home electricity demand. 27

28 Part I Second Year Progress and Achievements Task 6.2. Interfacing Kalundborg Distribution System Operator (DSO) with the project services The communication interface between SmartHG hardware devices collecting measurements in Svebølle (Kalundborg, Denmark) monitored houses and the SmartHG Database and Analytics (DB&A) service has been designed and implemented. Develco Products smart meters send the data gathered from monitored houses to SmartHG DB&A through the MEP card of Echelon meters (already installed in all homes) and the Develco Products gateway, which is connected to an existing Internet router. Figure 6.1 shows the DB&A and smart meter communication design. Figure 6.1: Database and Analytics (DB&A) and smart meters communication design Panoramic Power sensors send the data gathered from monitored appliances to Panoramic Power servers, via Panoramic Power bridge. All data are then sent to SmartHG DB&A and shown on the Panoramic Power dashboard, where only registered users can access them. Task 6.3. Hardware Deployment in Minsk Test-Bed We had problems with Belarus customs in shipping hardware devices there. Accordingly, so far we were only able to plan sensor deployment in Minsk and send there smart meters and gateways (but not sensors and bridges). In order to meet our goal of having two different test-beds ready by the end of the second year, as a recovery plan we deployed a test-bed in Central District (Israel). So far in Central District we completed deployment of sensing devices for appliances and mains in 9 homes out of the 13 foreseen in our present recovery plan. In Central District test-bed we are monitoring appliances and mains whereas in Minsk test-bed we were (planning) only for main monitoring. 28

29 Part I Second Year Progress and Achievements Task 6.4. Interfacing Minsk DSO with the project services A DSO is not directly involved in the Central District test-bed. For this reason, data and functionalities have been made available to a DSO through the SmartHG Web services. To see and download the data gathered from test-beds, a DSO will access SmartHG DB&A. Then a DSO can submit these data to the Demand Aware Price Policies (DAPP) service in order to compute a price policy and to the Price Policy Safety Verification (PPSV) service to evaluate its robustness. A DSO can use the EDN Virtual Tomography (EVT) service by uploading to the EVT website the electrical network topology. 29

30 WP 7 Dissemination and Exploitation The activities carried out in the second year inside Work Package WP7 target dissemination and exploitation activities (see Deliverables D7.2.1 and D7.2.2). For the second year, the dissemination activity has consisted in preparing an enhanced version of the dissemination tools (in particular of the project web-site, which now also includes a technical section), in presenting SmartHG to international events and in publishing papers acknowledging for EU support. As for the exploitation activities, in the second year we prepared a detailed and quantitative exploitation plan for each SmartHG Intelligent Automation Service (IAS), by keeping into account expected costs and revenues. The following sections outline the work carried out in WP7 and described in Deliverable D7.2.1 and D The tasks planned for the second year activity for WP7 are summarised in Table 7.1. Task Title T7.2 Dissemination Activity T7.4 Exploitation Plan Table 7.1: WP7 second year tasks (Deliverables D7.2.1 and D7.2.2) Task 7.1. Dissemination Plan This task has been completed on M12. Task 7.2. Dissemination Activity During the second year of the project, in order to improve usability and utility, the visual design of the project website has been updated and new contents have been added. The Technical Section of the SmartHG website has been designed, implemented 30

31 Part I Second Year Progress and Achievements and published. SmartHG mailing list, newsletter, social network accounts have been used to spread activities and public results of the project. Furthermore, a project leaflet and two sets of slides describing the project have been produced. A significant number of dissemination activities were performed during the second year of the project, including five talks at international conferences, nine scientific papers with a direct link to SmartHG funding, other seven scientific papers related to SmartHG topics, five project presentations at international events, participation of SmartHG partners to other ten international events, and two online contributions. Furthermore, nine networking and cooperation activities were established in order to introduce SmartHG and SmartHG IASs potential. Task 7.3. Market Analysis This task has been completed on M12. Task 7.4. Exploitation Plan The second year exploitation plan identifies SmartHG services to be exploited along with their potential customers. This, in turn, defines an exploitation plan for each SmartHG partner as well as for the consortium as a whole. To this end, we started from the initial qualitative and heterogeneous exploitation plan identified in the first year, and we produced an organic and quantitative analysis. 31