Modeling Tools for Energy Smart Grids. Centro Interdipartimentale per l Energia e l Ambiente CIDEA Università di Parma

Transcription

1 Modeling Tools for Energy Smart Grids Centro Interdipartimentale per l Energia e l Ambiente CIDEA Università di Parma

2 Energy Systems and Smart Grids Users (thermal & electrical loads) Generation (boilers, CHP, Heat Pumps, PV, solar thermal, gasifiers, ORC, etc.) Prosumers Storage (PCM, batteries, etc.) Distribution links (pipes, AC/DC lines, etc.) Design of efficient Smart Grids (thermal & electric) Integration of FER & Storage

3 1 Why? 2 How? Energy Systems and Grid Modelling 3 Tools: Systems Dynamics (Matlab/Simulink ) Energy Systems and Buildings (TRNSYS ) 4 Application: the Campus grids 5 XiL approach: system layout definition & design management strategies design & validation 6 The role of control strategies: Dynamic Programming for Optimized Strategy definition

4 Fuel Electricity Heating Cooling From an old architecture... Energy plant BOILER SPACE HEATING ELECTRIC GRID HOT WATER GAS NETWORK SPACE COOLING CHILLER LIGHTING & APPLIANCES

5 Radiation Fuel Electricity Heating Cooling SUN SOLAR PHOTOVOLTAIC (PV) AIR HEAT PUMP (GSHP and ASHP) GROUN D AUXILIARY BOILER (AB)...to new smart solutions Energy plant SPACE HEATING ELECTRIC GRID SOLAR THERMAL (SH) COGENERAT OR (CHP) HOT WATER GAS NETWORK ABSORPTION CHILLER (ABS) SPACE COOLING DISTRICT HEATING AUXILIARY CHILLER (AC) LIGHTING & APPLIANCES

6 Design, Improve and Manage Energy Grids <0,1 1 Model complexity Map Based Models Mean Value Models 0D fast running Models Concepts & Architecture (prosumers) Models can be used in each step of the process to limit Testing & costs & time. Running 10 1D fast running Models Components Options & Sizes Management System 100 CPU Time vs. Model approach x Real Time 1D-3D detailed Models 3D Models Integration Detailed design System or subsystem models with different level of complexity for each step. In-field Monitoring + Simulation Models allow to shorten development time and costs and improve Management Strategies

7 UniPR Simulation Tools In the last decade several models for the dynamic simulation of Energy Systems have been developed and included in Simulink libraries.

8 Real Application: the Campus grids THERMAL THERMAL POWER POWER STATION STATION

9 South New branch of the Campus grids THERMAL POWER STATION 1 3 2

10 Modelling Approach: pipe loop Mass flow rate is determined from the fluid mass dynamics taking account of pressure losses and available p E. p l1 Temperature change is determined from the heat flow estimated from pipe characteristics and int&ext temperatures. T l1 p E p l2 T E T l2 p l3 T l3 p E = p in -p out p li = press.losses T E = T in -T out T li = temp.losses The first pipe loop can be coupled with the two Dampers. Further loops can be added linking them to any pair of nodes of the previous loop.

11 Results: Steady-state Earth Sciences Building Dept.of Chemistry Building Supply Pressure 4.4 [bar] Supply Pressure 3.2 [bar] Return Pressure 4.3 [bar] Return Pressure 3.1 [bar] Flow rate Flow rate 10.2 [kg/s] Return TEMPERATURE 37.3 [kg/s] Return TEMPERATURE

12 Results: Transients

13 Systems Models for XiL applications Mathematical Models for MiL/SiL/HiL applied to Energy Grids: Co-simulation with very low CPU time. Optimization of grids architecture and sizing. Design & Testing of management strategies. Grids and Systems Models + Management Strategies Design costs & time Energy consumption Emissions Data input (from data base or real on-road monitoring Grids & Systems behavior Costs and emissions

14 Optimization A modelling approach is necessary in order to concurrently optimize architecture, sizing and management strategy size optimization algorithm control optimization algorithm multi-source energy system model Project submitted to PRIN 2015: Development of methodologies and instruments for the optimal design and management of distributed multi-energy systems connected to district heating and cooling networks