User flexibility aware price policy synthesis for smart grids. Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.; Gruber, J.; Hayes, B.; Prodanovic, M.; and Elmegaard, L. 2015. cited By 0; Conference of 18th Euromicro Conference on Digital System Design, DSD 2015 ; Conference Date: 26 August 2015 Through 28 August 2015; Conference Code:117072
User flexibility aware price policy synthesis for smart grids [link]Paper  doi  abstract   bibtex   
In order to optimally manage a modern electricity distribution network, peaks in residential users demand should be avoided, as this can reduce energy and network asset management costs. Furthermore, this must be done without compressing residential users demand. To this aim, in a demand response setting, residential users are given a price policy, which economically motivates them to shift their loads in order to achieve this goal. However, if the price policy for all users is similar, this demand response may result in simply shifting the demand peaks (peak rebound), leaving the problem unsolved. In this paper we propose a novel methodology which i) for each network substation s, automatically computes the desired power profile to be kept in order to optimally manage the network itself, ii) for each network substation s, automatically synthesizes individualized price policies for residential users connected to s, so that s is kept at the desired profile. Note that price policies individualization avoids the peak rebound problem, as different users have different low tariff areas. Furthermore, our methodology measures the flexibility of a residential user as the capacity needed by a home energy storage system (e.g., a battery) to always follow the given price policy, thus mitigating residential users discomfort. We show the feasibility of our approach on a realistic scenario taken from an existing medium voltage Danish distribution network. © 2015 IEEE.
@CONFERENCE{Mancini2015478,
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={User flexibility aware price policy synthesis for smart grids},
journal={Proceedings - 18th Euromicro Conference on Digital System Design, DSD 2015},
year={2015},
pages={478-485},
doi={10.1109/DSD.2015.35},
art_number={7302312},
note={cited By 0; Conference of 18th Euromicro Conference on Digital System Design, DSD 2015 ; Conference Date: 26 August 2015 Through 28 August 2015;  Conference Code:117072},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958211717&partnerID=40&md5=59622a862247f3cb978fda8b893bf5a2},
affiliation={Sapienza University of Rome, Roma, Italy; Instituto IMDEA Energia, Spain; SEAS-NVE, Denmark},
abstract={In order to optimally manage a modern electricity distribution network, peaks in residential users demand should be avoided, as this can reduce energy and network asset management costs. Furthermore, this must be done without compressing residential users demand. To this aim, in a demand response setting, residential users are given a price policy, which economically motivates them to shift their loads in order to achieve this goal. However, if the price policy for all users is similar, this demand response may result in simply shifting the demand peaks (peak rebound), leaving the problem unsolved. In this paper we propose a novel methodology which i) for each network substation s, automatically computes the desired power profile to be kept in order to optimally manage the network itself, ii) for each network substation s, automatically synthesizes individualized price policies for residential users connected to s, so that s is kept at the desired profile. Note that price policies individualization avoids the peak rebound problem, as different users have different low tariff areas. Furthermore, our methodology measures the flexibility of a residential user as the capacity needed by a home energy storage system (e.g., a battery) to always follow the given price policy, thus mitigating residential users discomfort. We show the feasibility of our approach on a realistic scenario taken from an existing medium voltage Danish distribution network. © 2015 IEEE.},
author_keywords={Grid State Estimation;  Peak Shaving;  Policy Robustness Verification;  Price Policy Synthesis},
keywords={Electric energy storage;  Electric power transmission networks;  Electric utilities;  Housing;  Smart power grids;  Systems analysis, Demand response;  Electricity distribution networks;  Energy storage systems;  Novel methodology;  Peak shaving;  Price policy;  Realistic scenario;  Residential users, Costs},
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), pp. 905-913; Kishore, S., Snyder, L.V., Control mechanisms for residential electricity demand in smartgrids (2011) Proc. of SmartGridComm; Mishra, A., Irwin, D., Shenoy, P., Kurose, J., Zhu, T., Smartcharge: Cutting the electricity bill in smart homes with energy storage (2012) Proc. of E-Energy; Economics, F., First, S., (2012) Demand Side Response in the Domestic Sector-A Literature Review of Major Trials, , UK Department of Energy and Climate Change, Tech. Rep., August; Rad, A.H.M., Leon-Garcia, A., Optimal residential load control with price prediction in real-Time electricity pricing environments (2011) IEEE Trans. Smart Grid, 1 (2), pp. 120-133; Mancini, T., Mari, F., Melatti, I., Salvo, I., Tronci, E., Gruber, J.K., Hayes, B., Elmegaard, L., Demand-Aware price policy synthesis and verification services for smart grids (2014) Proc. SmartGridComm; Keane, A., Ochoa, L., Borges, C., Ault, G., Alarcon-Rodriguez, A., Currie, R., Pilo, F., Harrison, G., State-of-The-Art techniques and challenges ahead for distributed generation planning and optimization (2013) IEEE Trans. Power Syst, 28 (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; Hayes, B., Hernando-Gil, I., Collin, A., Harrison, G., Djokic, S., Optimal power flow for maximizing network benefits from demandside management (2014) IEEE Trans. Power Syst, 29, p. 4; Hayes, B.P., Prodanovic, M., State estimation techniques for electric power distribution systems (2014) Proc. of EMS; 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. Power Syst, 27 (4); Hayes, B., Gruber, J., Prodanovic, M., A closed-loop state estimation tool for MV network monitoring and operation (2015) IEEE Trans. Smart Grid, p. 1; Haughton, D., Heydt, G., A linear state estimation formulation for smart distribution systems (2013) IEEE Trans. Pow. Syst, 28, p. 2; Reiss, P., White, M., Household electricity demand, revisited (2005) Rev. Econ. Studies, 72 (3), pp. 853-883. , July; Douglass, P.J., Garcia-Valle, R., Nyeng, P., Stergaard, J., Togeby, M., Smart demand for frequency regulation: Experimental results (2013) IEEE Trans. Smart Grid, 4 (3), pp. 1713-1720; (2015) ADVANCED Project Deliverables, , http://www.advancedfp7.eu/; 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; Mari, F., Melatti, I., Salvo, I., Tronci, E., Model based synthesis of control software from system level formal specifications (2014) ACM TOSEM, 23 (1); Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., On-The-fly control software synthesis (2013) Proc. of SPIN, , LNCS 7976; Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., A map-reduce parallel approach to automatic synthesis of control software (2013) Proc. of SPIN, , LNCS 7976; Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., On model based synthesis of embedded control software (2012) Proc. of EMSOFT; Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., Automatic control software synthesis for quantized discrete time hybrid systems (2012) Proc. of CDC; 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. of PDP, pp. 734-742; Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., Anytime system level verification via random exhaustive hardware in the loop simulation (2014) Proc. of DSD, pp. 236-245; Alimguzhin, V., Mari, F., Melatti, I., Salvo, I., Tronci, E., Sylvaas: System level formal verification as a service (2015) Proc. of PDP, pp. 476-483; Mancini, T., Mari, F., Massini, A., Melatti, I., Merli, F., Tronci, E., System level formal verification via model checking driven simulation (2013) Proc. of CAV, , LNCS 8044; Wang, Z., Wang, L., Adaptive negotiation agent for facilitating bi-directional 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 agent-based model (2013) IEEE Trans. Smart Grid, 4, p. 1; Hayes, B., Prodanovic, M., Short-Term operational planning and state estimation in power distribution networks (2014) CIRED; Wu, J., He, Y., Jenkins, N., A robust state estimator for medium voltage distribution networks (2013) IEEE Trans Pow Syst, 28 (2); Hayes, B., Prodanovic, M., A comparison of MV distribution system state estimation methods using field data (2015) IEEE PES; De Castro, L., Cramton, P., Prediction markets for electricity demand (2012) Proc. of CCC},
sponsors={INESC TEC; Synopsys},
publisher={Institute of Electrical and Electronics Engineers Inc.},
isbn={9781467380355},
language={English},
abbrev_source_title={Proc. - Euromicro Conf. Digit. Syst. Des., DSD},
document_type={Conference Paper},
source={Scopus},
}
Downloads: 0