Integration of multi-vector LES management in an EMS

1. Description of the Use Case

1.1. Name of the Use Case

IDArea /Domain(s)/Zone(s)Name of the Use Case

1.2. Version Management

Version No.DateName of author(s)ChangesApproval status
1.02019-05-20T00:00:00UTVgv, ICOM, SE,Final versionApproved

1.3. Scope and Objectives of Use Case

ScopeDescribe the main functionalities, prerequisites and integration aspects of an enhanced Energy Management System (EMS) designed for a Local Energy System (LES). Leveraging monitoring and control technologies to intelligently manage and optimize on-site Distributed Energy Resources (DER) - from Renewable Energy Sources (RES) generation to multi-vector load and storage assets - whilst integrating the Building Management Systems (BMS), to enforce optimal management strategies at the building level, hence enabling actors to automatically take actions that provide economic viability and energy reliability to the LES.
Objective(s)Integrating multiple assets in a supervisory control and data acquisition monitoring network:
  • Multi-vector DER generation;
  • On-site multi-vector storage;
  • On-site BMS (sensing, control); | | Related business case(s) | PUC 1 Provide commercial functionality to a multi-vector LES PUC 2 Shift Building Loads using Demand Side Management PUC 3 Shift Harbor Loads using Demand Side Management PUC 4 Optimal scheduling of thermal and electrical storage PUC 5 Optimal scheduling of electrical storage and hydrogen storage PUC 6 Storing excess generation in thermal network PUC 7 Optimal management of EV and FCEVs in a LES |

1.4. Narrative of Use Case

Short description

The main purpose of this HLUC is to describe how multi-vector local generation, on-site multi-vector storage and Building Management Systems (BMS) should interface with an Energy Management System (EMS) of a Local Energy System (LES) enabling optimized operation, through the integration of advanced functionalities provided by the E-LAND Toolbox.

Optimal operation of a LES encompassing multi-vector DER generators (thermal or electrical); on-site multi-vector storage (i.e. electrical batteries, hot water tanks, hydrogen storage, building enthalpy) and load priority control facilitated by the BMS could achieve higher efficiency levels than traditional solutions. The integration with advanced tools e.g. forecasting, optimisation as well as to external sources of data (e.g. weather forecasts) - through an Enterprise Service Bus (ESB) - should provide enough information and endpoints for proper EMS automation scenarios to be enforced having as a goal the optimal operation of the Local Energy System (LES). Therefore, the integrations of various field equipment (e.g. storage controllers, DER controllers, actuators, sensors) and the BMS is crucial for the realization of these advanced operations.

Optimal operation of a Local energy system (LES) can be considered from different perspectives (Facility Operator, Microgrid Operator, Aggregator, DER Owner) and therefore achieved by prioritising and/or optimising indices like: energy efficiency, cost of operation, cost of ownership, energy cost, carbon footprint.

Complete description

Traditionally, Energy Management System (EMS) solutions provide a comprehensive way of understanding energy profiles, identifying actual energy use and waste, as well as perform control actions on a variety of production and storage assets of multiple vectors (thermal, electrical, gas).

However, in the case of a Local Energy System (LES) where multiple business actors with different roles exist (e.g. DER Owner/Producer, Consumer), an enhanced solution is required to provide a top-level view of the operation of the system, enabling the realisation of optimisation scenarios. On this basis, the integration of the EMS with the controllers of the various storage and production assets is necessary. On the other hand, the integration with Building Management Systems (BMS) allows a more in-depth knowledge of the facilities’ loads (electrical or thermal), taking priority based decisions and enabling fine grained Demand Response (DR) actions.

On top of that, the EMS can make use of advanced tools related to forecasting and optimal operational scheduling/ future planning, which combined with all the above can help achieve optimal utilization of the constrained grid capacities, maximizing the use of on-site RES, by utilizing multi-vector energy blending, storage and DR actions.

Such an integrated system can enable the operation of the LES with the following advanced features: • Coordinated DER operation • Control over the energy mix and optimal use of storage with energy forecasting • Increased system reliability and power quality • Optimal load prioritization and shifting • Microgrid enabled operations: the ability of all integrated systems to work together as a single system, enabling facilities to operate as autonomous microgrids; • Quantification and measurement of overall carbon foot-print • Detailed monitoring of real-time energy-related data • Alerts for optimizing operational expenditures (OpEx)

The enhanced EMS will encompass the integration of the following sub-systems: • EMS: integrating the traditional DER Owner energy monitoring and control solution; • DER Controllers: On-site devices offering monitoring & control of the production assets of DER Owners; • Storage Controllers (Thermal/Electric/H2) Devices for multi-vector storage management, handling information on capacity and availability of storage assets of DER Owners; • BMS: Offering a monitoring network at a building level (evaluate energy usage/needs, occupancy, production, weather, etc.) as well as assisting real-time, data-driven decisions for the optimization of the consumption, by analysing offering various modes of operation (demand response, store energy) for various vectors; • Field Devices: For sensing or actuation of various loads, integrated through the BMS or directly; • EV/FCEV Chargers: Devices enabling the monitoring and control of the charging of Electric Vehicles and Fuel Cell Electric Vehicles in the LES, typically owned by the local stakeholders or even third parties • External Data Sources: for weather forecasting and energy prices • Advanced tools: for energy forecasting (Energy Forecaster) and for optimal scheduling (Optimal Scheduler) and planning • Enterprise Service Bus (ESB): A system enabling the integration of the above sub-systems

1.5. Key Performance Indicatiors (KPI)

IDNameDescriptionReference to mentioned use case objectives

1.6. Use case conditions


1.7. Further information to the use case for classification/mapping

Relation to other use cases
Level of depth
Generic, regional or national relation
Nature of the use cases
Further keywords for classification
LES Integration

1.8. General remarks

General remarks

2. Diagrams of Use Case

Technical & Business actor mapping

3. Technical Details

3.1. Actors

Actor NameActor TypeActor DescriptionFurther information specific to this Use Case
DER OwnerBusiness EntityAn asset owner of generation or storage facilities which is able to provide flexibility to the aggregator.
Microgrid OperatorBusiness EntityThe operator of a microgrid. Utilizes the flexibility provided by a local energy system to solve grid problems (reduce grid dependency) and/or achieve energy efficiency and environmental goals.
Facility Manager/OperatorBusiness EntityThe operator of a local energy system. Utilizes the flexibility provided by a local energy system to solve grid problems (reduce grid dependency) and/or achieve energy efficiency and environmental goals.
DER ControllerDeviceDevice able to control the operation of DER.
Electric Storage ControllerDeviceElectrical energy storage: solid state batteries, hydrogen
Thermal Storage ControllerDeviceThermal energy storage: tanks, buffers, building enthalpy
H2 Storage ControllerDeviceDevice able to control the operation of the electrolyser for producing and storing H2.
Building Management System (BMS)SystemA system to monitor and control building’s loads.
Energy Management System (EMS)NoneA system responsible for controlling and monitoring the various assets of the LES as well as for the orchestration of its optimal operation. Provides a user interface to the operator of the LES.
Energy Forecaster (EF)NonePredicts generation from local generation assets (e.g. wind turbines, PV panels), as well as consumption assets.
Optimal Scheduler (OS)NoneA system responsible for optimal scheduling of generation and storage assets as well as community based flexibility
Enterprise Service Bus (ESB)NoneA system enabling the integration of the forecasting and optimisation tools of E-Land toolbox and the EMS. Provides integration of the forecasting function as well as pre-processed meter and weather data
External Data Source (EDS)NoneA system able to store and provide data (environmental, system parameters, energy prices) e.g. PV inverter portal, weather forecasting service, local weather station.

3.2. References

No.References TypeReferenceStatusImpact on Use CaseOrganistaor / OrganisationLink

4. Step by Step Analysis of Use Case

4.1. Overview of Scenarios

No.Scenario NameScenario DescriptionPrimary ActorTriggering EventPre-ConditionPost-Condition


4.2. Steps – Scenarios

Scenario Name:
Step No.Event.Name of Process/ ActivityDescription of Process/ Activity.ServiceInformation Producer (Actor)Information Receiver (Actor)Information ExchangedRequirements, R-ID

5. Information Exchanged

Information exchanged IDName of InformationDescription of Information ExchangedRequirement

6. Requirements (optional)

Category IdentifierNameDescriptionmRID
Req_IDReq_Name‘Integration of multi-vector LES management in an EMS’

7. Common Terms and Definitions

8. Custom Information (optional)

KeyValueRefers to Section