HLUC03

1. Description of the Use Case

1.1. Name of the Use Case

1.2. Version Management

1.3. Scope and Objectives of Use Case

• Electrical and thermal energy production
• Electrical and thermal energy storage Based on electrical and thermal loads consumption data, as well as energy interchange with the electricity and district heating grid. | | Related business case(s) | PUC8 Multi-vector Optimisation of assets’ sizing in a LES PUC9 Optimal sizing of electrical parts of a LES |

1.4. Narrative of Use Case

Short description

The optimal sizing of a multi-vector LES involves the sizing of different assets, in order to make its operation more efficient. The assets may concern: • Electrical production assets, like PV panels and Wind generators • Thermal production assets such as solar thermal panel and geothermal heat pumps • Storage assets, such as batteries and hot water tanks Depending on the role of the involved business actor (grid/microgrid operator, facility operator, aggregator, DER owner), the business goals and relevant optimization objectives can vary. The optimization is proposed to tackle the following objectives:

1. Cost reduction for energy use or profit maximization from market participation
2. Fossil fuels/CO2 emissions reduction
3. Grid dependency reduction The optimization process should enable the operator to model and possibly combine the different objectives of the involved actors. In order to perform the simulations, the availability and cost of thermal and electrical energy exchanged with the main grids is considered. High import cost and low export price will increase the need for reducing the dependency of the LES from the main grid.

Complete description

A multi-vector local energy system (LES) operator can pursuit various goals, depending on its roles. Such goals may concern: • Increasing quality of service for load and production assets (any vector) • Increasing energy efficiency and reliability of the LES • Minimizing cost of operation • Reducing the environmental impact (CO2 emissions) • Maximizing the profits from selling energy to the market

To achieve such goals, the LES operator, can consider investments in local energy production (i.e. Distributed energy resources - DERs) such as PV panels, Wind generators, solar thermal panels and geothermal heat pumps. The former two technologies can increase the self-production of electricity and reduce electricity costs. Moreover, they can reduce peak power consumption or even provide revenues from selling energy to the energy market. From the two latter technologies, the local heat production can contribute in reducing the dependency from District Heat (DH) supplier or even become a heat producer and supply the grid with excessive production. Such assets can be installed in the operator facilities or in the facilities of consumers, which may be involved in the investment by leasing their properties or even investing in the assets. This way the role of DER Owners is considered to be in close collaboration with the operator that orchestrates the investment.

Furthermore, investments in storage of electrical and thermal energy can be considered and designed in order to lower the costs of energy supply from the main grid (e.g. peak shaving), as well as improve the profitability of energy production (by optimizing the energy consumption or energy trading). In a similar manner, local consumers/producers may be involved in such investments.

The core functionalities of the optimal planning comprise the modelling of the various assets and objectives of the investor, as well as the various ownership schemes in order to identify the most efficient scenarios for future investments.

From the perspective of an investor (e.g. a DER owner), the needs of electrical and thermal energy should be evaluated, integrating the current and estimating the future loads (from different vectors) as way to increase self-consumption. Also, the energy market for electrical (i.e. the local DSO and customers in the LES) and thermal energy (i.e. the DH supplier and the customers in the LES) should be investigated in terms of volume versus value, both for import and export. Assessing these inputs and providing the relevant optimisation criteria and assets of interest, the investor must be provided with the most beneficial scenarios with regard to the sizing of assets and the investment cost. The optimisation should concern different vectors and possible transformations of energy amongst them.

A typical use case should model the optimal sizing of electrical assets for storage and production, considering the current assets and the future electrical loads of the LES, whilst also considering production and loads (through transformation e.g. HVAC for heating) from other vectors(see - PUC 11: Sizing of electrical parts of a LES). In this scenario, the pricing of each energy vector (e.g. electric, thermal, gas) during the day and throughout the year will be considered, along with the constraints regarding the autonomous operation of the LES, as well as other techno-economic constraints.

Finally, another use case combining both electrical and heating production and storage assets, should enable the identification of the optimal investment in the LES (see PUC 07: Multi-vector Optimisation of assets’ sizing in a LES).

1.5. Key Performance Indicatiors (KPI)

1.6. Use case conditions

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

1.8. General remarks

2. Diagrams of Use Case

3. Technical Details

3.1. Actors

3.2. References

4. Step by Step Analysis of Use Case

4.1. Overview of Scenarios

Notes

4.2. Steps – Scenarios

5. Information Exchanged

6. Requirements (optional)

7. Common Terms and Definitions

8. Custom Information (optional)