@CONFERENCE{Mancini2015794,
author={Mancini, T.a  and Mari, F.a  and Melatti, I.a  and Salvo, I.a  and Tronci, E.a  and Gruber, J.K.b  and Hayes, B.b  and Prodanovic, M.b  and Elmegaard, L.c },
title={Demand-aware price policy synthesis and verification services for Smart Grids},
journal={2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014},
year={2015},
pages={794-799},
doi={10.1109/SmartGridComm.2014.7007745},
art_number={7007745},
note={cited By 6; Conference of 2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014 ; Conference Date: 3 November 2014 Through 6 November 2014;  Conference Code:110040},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84922440591&partnerID=40&md5=21a7eb46ccdc700bebf293afa24e280f},
affiliation={Sapienza University of Rome, Italy; Instituto IMDEA Energía, Spain; SEAS-NVE, Denmark},
abstract={In management tasks for modern electricity networks the stakeholders face typically two conflicting objectives: maximization of income (increasing demand) and reduction of demand peaks (reducing costs). To improve management of electricity distribution networks, an integrated service-based methodology is presented in this paper. Namely, the proposed approach: i) computes the operational constraints in order to improve utilization of the whole network; ii) enforces those constraints by focusing on each network substation separately; iii) verifies that probability of violating those constraints in nonnominal cases is fairly low. The feasibility of the approach has been tested tested by using a realistic scenario taken from an existing medium voltage Danish distribution network. In such scenario, the proposed method improves the network utilization and offers economic benefits for all the principal participants, i.e. DSOs, retailers and end users. © 2014 IEEE.},
keywords={Electric utilities, Conflicting objectives;  Economic benefits;  Electricity distribution networks;  Electricity networks;  Integrated service;  Net work utilization;  Operational constraints;  Realistic scenario, Smart power grids},
references={Hilshey, A.D., Hines, P.D.H., Rezaei, P., Dowds, J.R., Estimating the impact of electric vehicle smart charging on distribution transformer aging (2013) IEEE Trans. Smart Grid, 4 (2); Meliopoulos, A., Polymeneas, E., Tan, Z., Huang, R., Zhao, D., Advanced distribution management system (2013) IEEE Trans. Smart Grid, 4 (4), pp. 2109-2117. , Dec; Huang, Y.-F., Werner, S., Huang, J., Kashyap, N., Gupta, V., State estimation in electric power grids: Meeting new challenges presented by the requirements of the future grid (2012) Signal Processing Magazine, IEEE, 29 (5), pp. 33-43; Manitsas, E., Singh, R., Pal, B., Strbac, G., Distribution system state estimation using an artificial neural network approach for pseudo measurement modeling (2012) IEEE Trans. Pow. Sys., 27 (4), pp. 1888-1896. , Nov; Haughton, D., Heydt, G., A linear state estimation formulation for smart distribution systems (2013) IEEE Trans. Pow. Sys., 28 (2), pp. 1187-1195. , May; Hayes, B., Hernando-Gil, I., Collin, A., Harrison, G., Djokíc, S., Optimal power flow for maximizing network benefits from demand-side management (2014) IEEE Trans. Pow. Sys., PP (99), pp. 1-9; Vlot, M.C., Knigge, J.D., Slootweg, J.G., Economical regulation power through load shifting with smart energy appliances (2013) IEEE Trans. Smart Grid, 4 (3), pp. 1705-1712; Reiss, P., White, M., Household electricity demand, revisited (2005) Rev. Econ. Studies, 72 (3), pp. 853-883. , July; Mari, F., Melatti, I., Salvo, I., Tronci, E., Model based synthesis of control software from system level formal specifications (2014) ACM Trans. SW Eng. and Methodology, 23 (1); Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., Automatic control software synthesis for quantized discrete time hybrid systems (2012) Proc. CDC, pp. 6120-6125. , IEEE; Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., On-The-fly control software synthesis (2013) Proc. SPIN, , LNCS 7976, Springer; Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., A map-reduce parallel approach to automatic synthesis of control software (2013) Proc. SPIN, , LNCS 7976, Springer; Wang, Z., Wang, L., Adaptive negotiation agent for facilitating bidirectional energy trading between smart building and utility grid (2013) IEEE Trans. Smart Grid, 4 (2), pp. 702-710; Kunwar, Y.K.N., Kumar, R., Area-load based pricing in dsm through ann and heuristic scheduling (2013) IEEE Trans. Smart Grid, 4 (3), pp. 1275-1281; Thimmapuram, P.R., Kim, J., Consumers price elasticity of demand modeling with economic effects on electricity markets using an agentbased model (2013) IEEE Trans. Smart Grid, 4 (1), pp. 390-397; Mancini, T., Mari, F., Massini, A., Melatti, I., Merli, F., Tronci, E., System level formal verification via model checking driven simulation (2013) Proc. CAV, , LNCS 8044, Springer; Mancini, T., Mari, F., Massini, A., Melatti, I., Tronci, E., System level formal verification via distributed multi-core hardware in the loop simulation (2014) Proc. PDP, , CPS; Grosu, R., Smolka, S.A., Monte carlo model checking (2005) Proc. TACAS, , LNCS 3440, Springer; Dagum, P., Karp, R.M., Luby, M., Ross, S.M., An optimal algorithm for monte carlo estimation (2000) SIAM J. Comput., 29 (5); Lemay, M., Gunter, C., Cumulative attestation kernels for embedded systems (2012) IEEE Trans. Smart Grid, 3 (2), pp. 744-760; Verzino, G., Cavaliere, F., Mari, F., Melatti, I., Minei, G., Salvo, I., Yushtein, Y., Tronci, E., Model checking driven simulation of sat procedures (2012) Proc. SpaceOps; Hayes, B., Prodanovíc, M., Short-Term operational planning and state estimation in power distribution networks (2014) CIRED Workshop; De Castro, L., Cramton, P., Prediction markets for electricity demand Proc. Allerton 2012. IEEE},
sponsors={},
publisher={Institute of Electrical and Electronics Engineers Inc.},
isbn={9781479949342},
language={English},
abbrev_source_title={IEEE Int. Conf. Smart Grid Commun., SmartGridComm},
document_type={Conference Paper},
source={Scopus},
}

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Smart Grid, 4 (4), pp. 2109-2117. , Dec; Huang, Y.-F., Werner, S., Huang, J., Kashyap, N., Gupta, V., State estimation in electric power grids: Meeting new challenges presented by the requirements of the future grid (2012) Signal Processing Magazine, IEEE, 29 (5), pp. 33-43; Manitsas, E., Singh, R., Pal, B., Strbac, G., Distribution system state estimation using an artificial neural network approach for pseudo measurement modeling (2012) IEEE Trans. Pow. Sys., 27 (4), pp. 1888-1896. , Nov; Haughton, D., Heydt, G., A linear state estimation formulation for smart distribution systems (2013) IEEE Trans. Pow. Sys., 28 (2), pp. 1187-1195. , May; Hayes, B., Hernando-Gil, I., Collin, A., Harrison, G., Djokíc, S., Optimal power flow for maximizing network benefits from demand-side management (2014) IEEE Trans. Pow. Sys., PP (99), pp. 1-9; Vlot, M.C., Knigge, J.D., Slootweg, J.G., Economical regulation power through load shifting with smart energy appliances (2013) IEEE Trans. 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Smart Grid, 4 (2), pp. 702-710; Kunwar, Y.K.N., Kumar, R., Area-load based pricing in dsm through ann and heuristic scheduling (2013) IEEE Trans. Smart Grid, 4 (3), pp. 1275-1281; Thimmapuram, P.R., Kim, J., Consumers price elasticity of demand modeling with economic effects on electricity markets using an agentbased model (2013) IEEE Trans. Smart Grid, 4 (1), pp. 390-397; Mancini, T., Mari, F., Massini, A., Melatti, I., Merli, F., Tronci, E., System level formal verification via model checking driven simulation (2013) Proc. CAV, , LNCS 8044, Springer; Mancini, T., Mari, F., Massini, A., Melatti, I., Tronci, E., System level formal verification via distributed multi-core hardware in the loop simulation (2014) Proc. PDP, , CPS; Grosu, R., Smolka, S.A., Monte carlo model checking (2005) Proc. TACAS, , LNCS 3440, Springer; Dagum, P., Karp, R.M., Luby, M., Ross, S.M., An optimal algorithm for monte carlo estimation (2000) SIAM J. 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Smart Grid Commun., SmartGridComm","document_type":"Conference Paper","source":"Scopus","bibtex":"@CONFERENCE{Mancini2015794,\nauthor={Mancini, T.a and Mari, F.a and Melatti, I.a and Salvo, I.a and Tronci, E.a and Gruber, J.K.b and Hayes, B.b and Prodanovic, M.b and Elmegaard, L.c },\ntitle={Demand-aware price policy synthesis and verification services for Smart Grids},\njournal={2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014},\nyear={2015},\npages={794-799},\ndoi={10.1109/SmartGridComm.2014.7007745},\nart_number={7007745},\nnote={cited By 6; Conference of 2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014 ; Conference Date: 3 November 2014 Through 6 November 2014; Conference Code:110040},\nurl={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84922440591&partnerID=40&md5=21a7eb46ccdc700bebf293afa24e280f},\naffiliation={Sapienza University of Rome, Italy; Instituto IMDEA Energía, Spain; SEAS-NVE, Denmark},\nabstract={In management tasks for modern electricity networks the stakeholders face typically two conflicting objectives: maximization of income (increasing demand) and reduction of demand peaks (reducing costs). To improve management of electricity distribution networks, an integrated service-based methodology is presented in this paper. Namely, the proposed approach: i) computes the operational constraints in order to improve utilization of the whole network; ii) enforces those constraints by focusing on each network substation separately; iii) verifies that probability of violating those constraints in nonnominal cases is fairly low. The feasibility of the approach has been tested tested by using a realistic scenario taken from an existing medium voltage Danish distribution network. In such scenario, the proposed method improves the network utilization and offers economic benefits for all the principal participants, i.e. DSOs, retailers and end users. © 2014 IEEE.},\nkeywords={Electric utilities, Conflicting objectives; Economic benefits; Electricity distribution networks; Electricity networks; Integrated service; Net work utilization; Operational constraints; Realistic scenario, Smart power grids},\nreferences={Hilshey, A.D., Hines, P.D.H., Rezaei, P., Dowds, J.R., Estimating the impact of electric vehicle smart charging on distribution transformer aging (2013) IEEE Trans. Smart Grid, 4 (2); Meliopoulos, A., Polymeneas, E., Tan, Z., Huang, R., Zhao, D., Advanced distribution management system (2013) IEEE Trans. Smart Grid, 4 (4), pp. 2109-2117. , Dec; Huang, Y.-F., Werner, S., Huang, J., Kashyap, N., Gupta, V., State estimation in electric power grids: Meeting new challenges presented by the requirements of the future grid (2012) Signal Processing Magazine, IEEE, 29 (5), pp. 33-43; Manitsas, E., Singh, R., Pal, B., Strbac, G., Distribution system state estimation using an artificial neural network approach for pseudo measurement modeling (2012) IEEE Trans. Pow. Sys., 27 (4), pp. 1888-1896. , Nov; Haughton, D., Heydt, G., A linear state estimation formulation for smart distribution systems (2013) IEEE Trans. Pow. Sys., 28 (2), pp. 1187-1195. , May; Hayes, B., Hernando-Gil, I., Collin, A., Harrison, G., Djokíc, S., Optimal power flow for maximizing network benefits from demand-side management (2014) IEEE Trans. Pow. Sys., PP (99), pp. 1-9; Vlot, M.C., Knigge, J.D., Slootweg, J.G., Economical regulation power through load shifting with smart energy appliances (2013) IEEE Trans. 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Smart Grid, 4 (2), pp. 702-710; Kunwar, Y.K.N., Kumar, R., Area-load based pricing in dsm through ann and heuristic scheduling (2013) IEEE Trans. Smart Grid, 4 (3), pp. 1275-1281; Thimmapuram, P.R., Kim, J., Consumers price elasticity of demand modeling with economic effects on electricity markets using an agentbased model (2013) IEEE Trans. Smart Grid, 4 (1), pp. 390-397; Mancini, T., Mari, F., Massini, A., Melatti, I., Merli, F., Tronci, E., System level formal verification via model checking driven simulation (2013) Proc. CAV, , LNCS 8044, Springer; Mancini, T., Mari, F., Massini, A., Melatti, I., Tronci, E., System level formal verification via distributed multi-core hardware in the loop simulation (2014) Proc. PDP, , CPS; Grosu, R., Smolka, S.A., Monte carlo model checking (2005) Proc. TACAS, , LNCS 3440, Springer; Dagum, P., Karp, R.M., Luby, M., Ross, S.M., An optimal algorithm for monte carlo estimation (2000) SIAM J. 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