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Sviluppo di strategie di gestione ottimale di reti complesse di distribuzione dell energia

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6° Presentazione del workshop finale del progetto EFFICITY

Sviluppo di strategie di gestione ottimale di reti complesse di distribuzione dell'energia

Sito web del progetto: www.efficity-project.it

Published in: Engineering
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Sviluppo di strategie di gestione ottimale di reti complesse di distribuzione dell energia

  1. 1. Piacenza – 30 aprile 2019 Progetto Efficity (Bando Regione Emilia-Romagna DGR 1097/2015 - POR-FESR 2014-2020) Progettare la città sostenibile: distretti energetici intelligenti e digitalizzazione Sviluppo di strategie di gestione ottimale di reti complesse di distribuzione dell’energia Francesco Melino – CIRI FRAME, Università di Bologna
  2. 2. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 2 Indice della presentazione 1. Reti complesse di distribuzione dell’energia 2. Algoritmo per il controllo (real-time) ottimale di reti complesse di distribuzione dell’energia A. Calcolo termo-fluidodinamico B. Calcolo sistemi energetici (AG) 3. Caso applicativo: Campus di Parma
  3. 3. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 3 Reti complesse di distribuzione dell’energia Thermal Power Plant Hydraulic Power Plant Wind PhotovoltaicThermal storage Distributed photovoltaic and thermal panels +– Electric storage Natural Gas Networg Auxiliary boiler District Heating/ Cooling Network Heat pump CHP units NATURAL GAS ELECTRICAL ENERGY THERMAL ENERGY COOLING ENERGY Absorption and compression chillers Biomass boiler BIOMASS BIO National Electrical Grid Thermal Power Plant (CHP application)
  4. 4. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 4 Reti complesse di distribuzione dell’energia
  5. 5. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 5 Reti complesse di distribuzione dell’energia
  6. 6. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 6 3-CENTO – Complex Energy Networks Tool Optimizer • Calcolo delle prestazioni ed ottimizzazione di una rete complessa di distribuzione dell’energia:  Elettrica;  Termica (Frigorifera);  del Combustibile. • Calcolo «real time»  Calcolo fluidodinamico DHN (o DCN);  Regolazione DHN (DCN);  Allocazione del carico;  Scambi elettrici con la rete (o isola);  Annullamento dispersioni termiche. • Ottimizzazione:  Economica  Energetica (Ambientale)  Energetica/Economica
  7. 7. - Key Energy, Rimini - 08.11.2018 7 Calcolo fluidodinamico DHN (o DCN) DHN NODES definition DHN PIPES definition DHN SOURCES definition PUMPS INPUT DHN USERS definition NETWORK GEOMETRY implementation NODES INPUT PIPES INPUT USERS INPUT OPERATIONAL PARAMETERS definition SOURCE INPUT MASS FLOW RATE AND PRESSURES calculation TEMPERATURES calculation UTILITIES FITTING TEXT OUTPUT GRAPH OUTPUT THERMAL DISSIPATIONS calculation PUMPING CONSUMPTION calculation 1 5 4 2 3 6 INPUT SORGENTI 1. NETWORK GEOMETRY IMPLEMENTATION 4. GEOMETRY AND OPERATIONAL PARAMETERS ELABORATION 2. NETWOR K INPUT 3. USERS DEFINITION 5. CALCULATION 6. OUTPUT WRITING • Algoritmo di Todini-Pilati  nessun limite dimensioni e complessità rete di distribuzione termica (frigorifera);  risoluzione idraulica (portate e pressioni). • Strategie di regolazione  portata costante;  DT costante;  mista. • Gestione gruppo pompaggio:  centrale;  pompe di rilancio • Ottimizzazione:  distribuzione pressioni;  distribuzione portate.
  8. 8. - Key Energy, Rimini - 08.11.2018 8 Calcolo fluidodinamico DHN (o DCN) • Algoritmo di Todini-Pilati  nessun limite dimensioni e complessità rete di distribuzione termica (frigorifera);  risoluzione idraulica (portate e pressioni). • Strategie di regolazione  portata costante;  DT costante;  mista. • Gestione gruppo pompaggio:  centrale;  pompe di rilancio • Ottimizzazione:  distribuzione pressioni;  distribuzione portate. 1 2 p12 3 4 p23 p24 5 6 p45 p46 (q3) (q4) (q6) pij = ramo da nodo i a nodo j qi = carico termico nodo (user) i NN = numero nodi NR = numero rami Per ogni ramo: 1 - BILANCIO DI ENERGIA (dove Hi and Hj contenuto energetico del fluido nel nodo i e j)  densità v velocità L lunghezza ramo D diametro ramo f drag coefficient (Darcy coefficient)  coeff. Perdite carico connc. Darcy-Weisbach equation: ∆𝐻 𝑝𝑖𝑗 − 𝐻𝑖 − 𝐻𝑗 = 0 ∆𝐻 = ∆𝐻 𝑑𝑖𝑠 + ∆𝐻𝑐𝑜𝑛=𝑓 𝐿 𝐷 𝜌 𝑣 2 + 𝛽𝜌 𝑣2 2 Per ogni nodo: 2 - BILANCIO DI MASSA (tra portata in ingresso, in uscita e richiesta dall’utenza) 𝐼𝑁 𝑄𝐼𝑁 − 𝑂𝑈𝑇 𝑄 𝑂𝑈𝑇 − 𝑈 𝑞 𝑈 = 0
  9. 9. - Key Energy, Rimini - 08.11.2018 9 Calcolo fluidodinamico DHN (o DCN) • Algoritmo di Todini-Pilati  nessun limite dimensioni e complessità rete di distribuzione termica (frigorifera);  risoluzione idraulica (portate e pressioni). • Strategie di regolazione  portata costante;  DT costante;  mista. • Gestione gruppo pompaggio:  centrale;  pompe di rilancio • Ottimizzazione:  distribuzione pressioni;  distribuzione portate. 1 2 p12 3 4 p23 p24 5 6 p45 p46 (q3) (q4) (q6) pij = ramo da nodo i a nodo j qi = carico termico nodo (user) i NN = numero nodi NR = numero rami Sistema di (NN + NP) equazioni nelle incognite Q ed H       0),( 0),( 21 1211 qQAHQF HAQAHQF Q P Risoluzione iterativa con il metodo di Newton-Raphson      NNNRA NRNNA NRNRA    12 21 11 In particolare: A21 matrice topologica. Le righe della matrice rappresentano i nodi della rete, le colonne sono rappresentative dei rami. Il generico termine di A21(i,j) assume valore 1 se la generica portata qj che attraversa il ramo j è entrante nel nodo i ovvero il nodo i è a valle del ramo j, -1 nel caso contrario, 0 se non esiste connessione tra il nodo i ed il ramo j. A12 trasposta della matrice topologica A11 matrice diagonale, con i termini non nulli definiti come segue:     j j j Pj Q H Q F jjA NRNRA  D      ,11 11
  10. 10. - Key Energy, Rimini - 08.11.2018 10 Calcolo fluidodinamico DHN (o DCN) • Algoritmo di Todini-Pilati  nessun limite dimensioni e complessità rete di distribuzione termica (frigorifera);  risoluzione idraulica (portate e pressioni). • Strategie di regolazione  portata costante;  DT costante;  mista. • Gestione gruppo pompaggio:  centrale;  pompe di rilancio • Ottimizzazione:  distribuzione pressioni;  distribuzione portate. Geometry of DHN Users Input Sources Input Definition of matrices: A11 ; A12; A21 First Attemp Values of H(m=1) and Q(m=1) Todini – Pilati Algorithm DH(m) ,DQ(m) < 10-9 Calculation of : DH(m) , DQ(m) H(m+1) = H(m) + DH(m) Q(m+1) = Q(m) + DQ(m) m = m+1 N Y Pipe Thermal Calculation Pipe Parameters Text Output Graphical Output
  11. 11. - Key Energy, Rimini - 08.11.2018 11 Calcolo fluidodinamico DHN (o DCN) • Algoritmo di Todini-Pilati  nessun limite dimensioni e complessità rete di distribuzione termica (frigorifera);  risoluzione idraulica (portate e pressioni). • Strategie di regolazione  portata costante;  DT costante;  mista. • Gestione gruppo pompaggio:  centrale;  pompe di rilancio • Ottimizzazione:  distribuzione pressioni;  distribuzione portate.
  12. 12. - Key Energy, Rimini - 08.11.2018 12 Calcolo fluidodinamico DHN (o DCN) • Algoritmo di Todini-Pilati  nessun limite dimensioni e complessità rete di distribuzione termica (frigorifera);  risoluzione idraulica (portate e pressioni). • Strategie di regolazione  portata costante;  DT costante;  mista. • Gestione gruppo pompaggio:  centrale;  pompe di rilancio • Ottimizzazione:  distribuzione pressioni;  distribuzione portate. 0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 80,0 90,0 0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 5,0 5,5 6,0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 Efficienza[%] Prevalenza[bar] Portata in massa [kg/s] Punto di design 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1516 17 1819 20 21 22 23 24 25 26 27 28 29 30 3132 33 34 35 3637 3839 4041 42 43 44 45 4647 48 49 50 51 52 53 54 55 56 57 58 59 60 6162 68 64 65 66 67 63 69 70 71 72 73 74 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 2223 24 25 26 2728 29 3032 31 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 Percorso critico #1 Percorso critico #2
  13. 13. - Key Energy, Rimini - 08.11.2018 13 Calcolo fluidodinamico DHN (o DCN) • Algoritmo di Todini-Pilati  nessun limite dimensioni e complessità rete di distribuzione termica (frigorifera);  risoluzione idraulica (portate e pressioni). • Strategie di regolazione  portata costante;  DT costante;  mista. • Gestione gruppo pompaggio:  centrale;  pompe di rilancio • Ottimizzazione:  distribuzione pressioni;  distribuzione portate.
  14. 14. - Key Energy, Rimini - 08.11.2018 14 Calcolo sistemi energetici (AG) • Algoritmo Genetico  Fitness Function  ottimo economico  ottimo energetico (ambientale)  ottimo energetico/economico • Operazioni genetiche  nuova generazione (25%);  crossover (one point or two point);  selezione (metodo roulette);  mutazione (non impiegata). • Input:  caratteristiche sistemi;  scenario tariffario • Output:  allocazione ottimale del carico;  risultati economici. WIND PRIME MOVERS (PM) AUXILIARY BOILERS (AB) UTILITIES (U) ELECTRIC GRID NATURAL GAS ELECTRICAL ENERGY THERMAL ENERGY NATURAL GAS NETWORK SOLAR THERMAL (RGt) PV PANELS CH4 + – EL STORAGE (ES) TH STORAGE (TS) ABS CHILLER (AC) COMP CHILLER (CC) COOLING ENERGY HEAT PUMP (HP) EL RENEWABLE GEN (RGe)
  15. 15. - Key Energy, Rimini - 08.11.2018 15 Calcolo sistemi energetici (AG) • Algoritmo Genetico  Fitness Function  ottimo economico  ottimo energetico (ambientale)  ottimo energetico/economico • Operazioni genetiche  nuova generazione (25%);  crossover (one point or two point);  selezione (metodo roulette);  mutazione (non impiegata). • Input:  caratteristiche sistemi;  scenario tariffario • Output:  allocazione ottimale del carico;  risultati economici. 𝐹𝐹 = 𝐶𝜆 + 𝐶 𝑀 + 𝐶 𝐸 + 𝐶 𝐹 dove: 𝐶𝜆 costo totale del combustibile; 𝐶 𝑀 costo totale di manutenzione; 𝐶 𝐸 costo totale acquisto energia elettrica; 𝐶 𝐹 costo fittizi. 𝐶𝜆 = 𝑖=1 𝑛 𝑃𝑀 𝑓𝜆,𝑖 𝑃𝑀 𝐿 𝑃𝑀,𝑖 + 𝑖=1 𝑛 𝐴𝐵 𝑓𝜆,𝑖 𝐴𝐵 𝐿 𝐴𝐵,𝑖 ∙ 𝜆 𝑓𝑢𝑒𝑙 + 𝑖=1 𝑛 𝐵𝐵 𝑓𝜆,𝑖 𝐵𝐵 𝐿 𝐵𝐵,𝑖 ∙ 𝜆 𝑏𝑖𝑜𝑚𝑎𝑠𝑠 𝐶 𝑀 = 𝑖=1 𝑛 𝑃𝑀+𝑛 𝑅𝐺𝑒 𝑃𝐸𝐿,𝑖 ∙ 𝜇 𝐸𝐿,𝑖 + 𝑖=1 𝑛 𝑅𝐺𝑡+𝑛 𝐴𝐵+𝑛 𝐵𝐵+𝑛 𝐻𝑃 𝑃 𝑇𝐻,𝑖 ∙ 𝜇 𝑇𝐻,𝑖 + 𝑖=1 𝑛 𝐶𝐶+𝑛 𝐴𝐶 𝑃𝐹𝑅,𝑖 ∙ 𝜇 𝐹𝑅,𝑖 𝐶 𝐸 = 𝑃𝐸𝐿,𝑃 ∙ 𝜉 𝐸𝐿,𝑃 essendo: 𝑃𝑖 = 𝑓 𝐿𝑖 . 𝑃𝐸𝐿,𝑃 = 𝑖=1 𝑛 𝑈 𝑃𝐸𝐿,𝑖 𝑈 + 𝑖=1 𝑛 𝐶𝐶 𝑃 𝐹𝑅,𝑖 𝐶𝐶 𝑓𝐸𝐸𝑅,𝑖 𝐶𝐶 𝐿 𝐶𝐶,𝑖 + 𝑖=1 𝑛 𝐻𝑃 𝑃 𝑇𝐻,𝑖 𝐻𝑃 𝑓𝐶𝑂𝑃,𝑖 𝐻𝑃 𝐿 𝐻𝑃,𝑖 − 𝑖=1 𝑛 𝑅𝐺𝑒 𝑓𝐸𝐿,𝑖 𝑅𝐺𝑒 𝐿 𝑅𝐺𝑒,𝑖 − 𝑖=1 𝑛 𝑃𝑀 𝑓𝐸𝐿,𝑖 𝑃𝑀 𝐿 𝑃𝑀,𝑖 − 𝑖=1 𝑛 𝐸𝑆 𝑃𝐸𝐿,𝑖 𝐸𝑆 essendo: 𝐶 𝐹 = 𝑖=1 𝑛 𝑃𝑀 𝑄 𝑑𝑖𝑠𝑝,𝑖 𝜂 𝐴𝐵,𝑎𝑣 ∙ 𝜆 𝑓𝑢𝑒𝑙 ∙ 𝑝 𝑇 − 𝑃𝐸𝐿,𝑆 ∙ 𝜉 𝐸𝐿,𝑆 𝐶 𝐹 = 𝑃𝐸𝐿,𝑆 ∙ 𝜉 𝐸𝐿,𝑆 ∙ 𝑝 𝐸 Priorità termica Priorità elettrica
  16. 16. - Key Energy, Rimini - 08.11.2018 16 Calcolo sistemi energetici (AG) • Algoritmo Genetico  Fitness Function  ottimo economico  ottimo energetico (ambientale)  ottimo energetico/economico • Operazioni genetiche  nuova generazione (25%);  crossover (one point or two point);  selezione (metodo roulette);  mutazione (non impiegata). • Input:  caratteristiche sistemi;  scenario tariffario • Output:  allocazione ottimale del carico;  risultati economici. 6.00 6.05 6.10 6.15 6.20 6.25 6.30 6.35 6.40 6.45 6.50 6.55 6.60 6.65 6.70 6.75 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 G01 G02 G03 G04 G05 G06 G07 G08 G09 G10 ObjectFunctionValue[€] Fitness Function Rank [#] Generation INDEX
  17. 17. - Key Energy, Rimini - 08.11.2018 17 Calcolo sistemi energetici (AG) • Algoritmo Genetico  Fitness Function  ottimo economico  ottimo energetico (ambientale)  ottimo energetico/economico • Operazioni genetiche  nuova generazione (25%);  crossover (one point or two point);  selezione (metodo roulette);  mutazione (non impiegata). • Input:  caratteristiche sistemi;  scenario tariffario • Output:  allocazione ottimale del carico;  risultati economici. input richiesti: o potenze elettrica, termica e frigorifera richieste complessivamente dalle utenze, oltre che eventuale richiesta da parte delle utenze di gas naturale per usi diretti; o numero, tipologia e caratteristiche principali di: • motori primi (potenze elettrica e termica di design, efficienza, curve caratteristiche per il comportamento in off-design, ecc.); • generatori da fonte rinnovabile (potenza di picco, curve di efficienza, ecc.); • sistemi per il riscaldamento ed il raffrescamento (taglia, efficienza, comportamento in off-design, ecc.); • sistemi di accumulo di energia elettrica e termica (massima energia stoccabile); o scenario tariffario (valori dell’energia elettrica acquistata e venduta, costo del combustibile, ecc.)
  18. 18. - Key Energy, Rimini - 08.11.2018 18 Calcolo sistemi energetici (AG) • Algoritmo Genetico  Fitness Function  ottimo economico  ottimo energetico (ambientale)  ottimo energetico/economico • Operazioni genetiche  nuova generazione (25%);  crossover (one point or two point);  selezione (metodo roulette);  mutazione (non impiegata). • Input:  caratteristiche sistemi;  scenario tariffario • Output:  allocazione ottimale del carico;  risultati economici. 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 PM#1 PM#2 PM#3 PM#4 ElectricPower[kW] hour/day 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 PM#1 PM#2 PM#3 PM#4 ThermalPower[kW] hour/day 0.80 0.85 0.90 0.95 1.00 1.05 1.10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 ChangeinCost[-] hour/day Full Load Optimized
  19. 19. - Key Energy, Rimini - 08.11.2018 3-CENTO – Complex Energy Networks Tool Optimizer 19
  20. 20. - Key Energy, Rimini - 08.11.2018 20 3-CENTO – Complex Energy Networks Tool Optimizer
  21. 21. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITYCaso applicativo: Campus di Parma (Nuova Sud) 21 Centrale termica < 12 4 3 5 6 7 8 9 10 11 12 13 14 15 16 ID Utenza Utenza servita 1 Archivio storico 2 Scienze degli alimenti 3 Laboratorio Materiali 4 Polifunzionale/Auditorium 5 Ingegneria Scientifica 6 Palacampus 7 Scienze della terra 8 Bar 9 Centro la Grande – Chiesa/Aule 10 Mensa 11 Centro la Grande – Copisteria 12 Tecnopolo 13 Complesso delle utenze servite dalla porzione Vecchia Sud 14 Complesso delle utenze servite dalla porzione Vecchia Nord 15 Complesso delle utenze servite dalla porzione Nuova Nord 16 Complesso delle utenze servite dalla porzione Autonomo
  22. 22. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 22 Caso applicativo: Campus di Parma (Nuova Sud) 0 1.000 2.000 3.000 4.000 5.000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Fabbisognodidesign[kW] ID Utenza 0 1.000 2.000 3.000 4.000 5.000 6.000 7.000 8.000 9.000 10.000 11.000 12.000 0 730 1460 2190 2920 3650 4380 5110 5840 6570 7300 8030 8760 PotenzaTermica[kW] ora/anno Fabbisogno termico annuo (rete nuova sud) Energia termica/anno = 5 GWh (rete nuova sud) anno termico: 15 ottobre – 15 aprile Fabbisogno: riscaldamento invernale
  23. 23. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 23 Caso applicativo: Campus di Parma (Nuova Sud) T T T T T T T T T T BOILER #1 BOILER #2 BOILER #3 BOILER #4 ingresso rete (uscita centrale) uscita rete (ingresso centrale) BOILER #5 0,0 10,0 20,0 30,0 40,0 50,0 60,0 70,0 80,0 90,0 100,0 110,0 0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 9,0 10,0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 Efficienza[%] Prevalenza[bar] Portata in massa [kg/s] Punto di design mandata rete TLR ritorno rete TLR ritorno utenza mandata utenza 0 500 1.000 1.500 2.000 2.500 3.000 3.500 4.000 4.500 5.000 BOILER #1 BOILER #2 BOILER #3 BOILER #4 BOILER #5 Potenza termica di design Rendimento termico di design 0 10 20 30 40 50 60 70 80 90 100 Potenzatermicadesign[kW] eddicienzatermicadesign[%]
  24. 24. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 24 Caso applicativo: Campus di Parma (Nuova Sud) 3 2 1 1 2 3 4 4 5 5 6 6 78 7 8 9 9 10 11 10 11 12 12 13 13 14 15 1415 16 16 17 17 18 19 18 19 20 21 20 22 21 22 23 23 24 24 25 2627 28 44 43 42 45 46 41 40 68 39 36 37 38 35 30 31 29 32 33 34 2526 27 45 46 47 43 42 44 41 40 69 37 36 38 39 34 35 33 29 30 32 31 28 48 49 50 51 52 53 54 48 49 50 51 52 53 5465 55 56 66 67 57 58 59 60 61 62 63 64 55 5657 58 59 60 61 62 63 64 65 66 6768 47 centrale utenza miscelatore 0-250 -50-150-300 -100-200-500 -400-550 -350-450-600-800 -700 -650-750 0 -50 -100 50 100 150 200 250 -150 -200 [m] [m] 50 70 71 73 75 77 72 74 76 69 70 72 74 76 75 73 71 Temperatura immissione in rete [°C] 80 Temperatura di riferimento [°C] -5 Salto termico utenze (lato rete) [°C] 25
  25. 25. - Key Energy, Rimini - 08.11.2018 25 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (caso base) 0 10 20 30 40 50 8 11 19 32 34 39 44 47 53 65 68 69 71 73 75 77 Portatainmassa[kg/s] IDN 0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 8 11 19 32 34 39 44 47 53 65 68 69 71 73 75 77 Saltodipressione[bar] IDN Lunghezza totale della rete [m] 5167 Portata in massa TOTALE ingresso [kg/s] 165 Potenza termica fornita alle UTENZE dalla rete [kW] 17243 Potenza termica dissipata RETE [kW] 169 Potenza termica fornita sorgenti [kW] 17412 Potenza spesa pompaggio [kW] 145 3 2 1 1 2 3 4 4 5 5 6 6 78 7 8 9 9 10 11 10 11 12 12 13 13 14 15 1415 16 16 17 17 18 19 18 19 20 21 20 22 21 22 23 23 24 24 25 2627 28 44 43 42 45 46 41 40 68 39 36 37 38 35 30 31 29 32 33 34 2526 27 45 46 47 43 42 44 41 40 69 37 36 38 39 34 35 33 29 30 32 31 28 48 49 50 51 52 53 54 48 49 50 51 52 53 5465 55 56 66 67 57 58 59 60 61 62 63 64 55 5657 58 59 60 61 62 63 64 65 66 6768 47 centrale utenza miscelatore 0-250 -50-150-300 -100-200-500 -400-550 -350-450-600-800 -700 -650-750 0 -50 -100 50 100 150 200 250 -150 -200 [m] [m] 50 70 71 73 75 77 72 74 76 69 70 72 74 76 75 73 71
  26. 26. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 26 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (caso base)
  27. 27. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 27 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (caso base)
  28. 28. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 28 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (caso base)
  29. 29. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 29 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (caso base)
  30. 30. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 30 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (caso base)
  31. 31. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 31 Caso applicativo: Campus di Parma (Nuova Sud) – 18 novembre 0 1.000 2.000 3.000 4.000 5.000 6.000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Potenzaelettricarichiesta[kW] ore/giorno 0 2.000 4.000 6.000 8.000 10.000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Potenzatermicarichiesta[kW] ore/giorno
  32. 32. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 32 Sistemi di produzione • un ORC alimentato a biomassa Potenza elettrica: 1058 kW; Potenza termica: 5155 kW; Rendimento elettrico: 0.1387; Rendimento termico: 0.6758 • un serbatoio di accumulo termico da 56825 kWh • una caldaia Potenza termica: 8334 kW; Rendimento termico: 0. 9440 Caso applicativo: Campus di Parma (Nuova Sud) – 18 novembre 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 [€/kWh] ore/giorno acquisto vendita 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Temperaturaambiente[°C] ore/giorno 0 50 100 150 200 250 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Irraggiamento[W/m 2 ] ore/giorno • una caldaia Potenza termica: 94 kW; Rendimento termico: 0. 9440 • pannelli fotovoltaici Potenza elettrica di picco: 6300 kW; Superficie coperta: 42000 m2.
  33. 33. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 33 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (18 novembre) 0 20 40 60 80 100 120 140 160 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 PotenzaElettricaperPompaggio[kW] ore/giorno rete in funzione rilancio rete stand-by rete 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Temperatura[°C] ore/giorno 0 20 40 60 80 100 120 140 160 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Portatainmassa[kg/s] ore/giorno 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Efficienzadidistribuzione[-] ore/giorno - 26% consumo elettrico per pompaggio - 8% potenza termica dispersa
  34. 34. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 34 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (18 novembre) 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 6,500 7,000 7,500 8,000 8,500 9,000 9,500 10,000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 fornita all'accumulo termico [kW] dispersa rete [kW] stand-by rete [kW] rilancio rete [kW] richiesta utenza [kW] potenzatermica[kW] ora/giorno
  35. 35. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 35 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (18 novembre) 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 6,500 7,000 7,500 8,000 8,500 9,000 9,500 10,000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 da caldaie [kW] fornita dall'accumulo termico [kW] da motori primi [kW] potenzatermica[kW] ora/giorno 4 ton CO2 evitate
  36. 36. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 36 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (18 novembre) 40 50 60 70 80 90 100 inizio periodo fine periodo 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 energiadisponibileaccumulo[%] ore/giorno accumulo restituzione
  37. 37. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 37 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (18 novembre) 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 immessa in rete [kW] pompaggio [kW] richiesta utenza [kW] potenzaelettrica[kW] ora/giorno
  38. 38. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 38 Caso applicativo: Campus di Parma (Nuova Sud) – risultati (18 novembre) 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 5,500 6,000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 da fotovoltaico [kW] acquistata dalla rete [kW] da motori primi [kW] potenzatermica[kW] ora/giorno
  39. 39. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITYConclusioni 39 1. Il software 3-CENTO è in grado di ottimizzare una rete complessa di distribuzione dell’energia elettrica, termica (frigorifera) o del combustibile al fine di: o minimizzare il costo di produzione dell’energia; o e/o minimizzare lo scambio di energia elettrica con la rete o e/o minimizzare la dispersione di energia termica nell’ambiente 2. Il software è adatto alla gestione di reti complesse come strumento «real time» 3. L’applicazione del software a un caso studio ha permesso – a parità di servizio energia fornito alle utenze – di ridurre la spesa di combustibile, le emissioni clima alteranti e gli scambi di energia elettrica con la rete nazionale.
  40. 40. - Key Energy, Rimini - 08.11.2018 Il Progetto EFFICITY 40 GRAZIE PER L’ATTENZIONE Francesco Melino – CIRI-FRAME – Università di Bologna francesco.melino@unibo.it Progetto EffiCity - Sistemi energetici efficienti per distretti urbani intelligenti www.efficity-project.it Efficity è un progetto co-finanziato dalla Regione Emilia-Romagna nell’ambito del Bando per progetti di ricerca industriale strategica in ambito energetico (DGR 1097/2015), emesso in attuazione al POR-FESR 2014-2020.

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