Risk-based scheduling of smart apartment building under market price uncertainty using robust optimization approach

Abstract Nowadays market price uncertainty is one of the important challenging issues in the optimal scheduling of smart apartment building (SAB). So, in this paper, a robust optimization approach (ROA) is proposed for robust scheduling of SAB in the presence of price uncertainty. For modeling the market price uncertainty, upper and lower limits of the market price are considered instead of the forecasted market prices. The proposed sample system includes a SAB that contains ten smart homes (SHs) with different living habits and equipped with different equipment, i.e. combined heat and power (CHP), boiler, battery storage system (BSS), thermal storage system (TSS) and smart appliances. To assess the effectiveness of a home energy management system (HEMS) on the performance of the proposed problem, two different controlling scenarios are studied, namely normal and smart scenarios. It should be mentioned that the proposed model is formulated as mixed-integer linear programming (MILP) which guarantees global optimal solution and carried out with general algebraic modeling system (GAMS) software.

[1]  Edris Pouresmaeil,et al.  Framework for smart transactive energy in home-microgrids considering coalition formation and demand side management , 2018, Sustainable Cities and Society.

[2]  Kazem Zare,et al.  Information gap decision theory-based risk-constrained scheduling of smart home energy consumption in the presence of solar thermal storage system , 2018 .

[3]  Luhao Wang,et al.  Integrated scheduling of energy supply and demand in microgrids under uncertainty: A robust multi-objective optimization approach , 2017 .

[4]  Sayyad Nojavan,et al.  Optimal scheduling of multi-smart buildings energy consumption considering power exchange capability , 2018, Sustainable Cities and Society.

[5]  Lazaros G. Papageorgiou,et al.  Economic and environmental scheduling of smart homes with microgrid: DER operation and electrical tasks , 2016 .

[6]  Lazaros G. Papageorgiou,et al.  Efficient energy consumption and operation management in a smart building with microgrid , 2013 .

[7]  Nadeem Javaid,et al.  An Efficient Power Scheduling in Smart Homes Using Jaya Based Optimization with Time-of-Use and Critical Peak Pricing Schemes , 2018, Energies.

[8]  Shahram Jadid,et al.  Cost reduction and peak shaving through domestic load shifting and DERs , 2017 .

[9]  Lazaros G. Papageorgiou,et al.  Energy Management of Smart Homes with Microgrid , 2017 .

[10]  Nadeem Javaid,et al.  A new heuristically optimized Home Energy Management controller for smart grid , 2017 .

[11]  Shahram Jadid,et al.  Optimal residential appliance scheduling under dynamic pricing scheme via HEMDAS , 2015 .

[12]  Mario Zanon,et al.  Day-Ahead Scheduling and Real-Time Economic MPC of CHP Unit in Microgrid With Smart Buildings , 2019, IEEE Transactions on Smart Grid.

[13]  Nadeem Javaid,et al.  Time and device based priority induced comfort management in smart home within the consumer budget limitation , 2018 .

[14]  Jianzhong Wu,et al.  Robust-Index Method for Household Load Scheduling Considering Uncertainties of Customer Behavior , 2015, IEEE Transactions on Smart Grid.

[15]  Shahram Jadid,et al.  Optimal joint scheduling of electrical and thermal appliances in a smart home environment , 2015 .

[16]  Onur Elma,et al.  A new home energy management algorithm with voltage control in a smart home environment , 2015 .

[17]  Akin Tascikaraoglu,et al.  A demand side management strategy based on forecasting of residential renewable sources: A smart home system in Turkey , 2014 .

[18]  Jianhui Wang,et al.  MPC-Based Appliance Scheduling for Residential Building Energy Management Controller , 2013, IEEE Transactions on Smart Grid.

[19]  Kazem Zare,et al.  Robust thermal and electrical management of smart home using information gap decision theory , 2018 .

[20]  Shuai Lu,et al.  Robust scheduling of smart appliances with uncertain electricity prices in a heterogeneous population , 2014 .

[21]  Andreas Sumper,et al.  Real time experimental implementation of optimum energy management system in standalone Microgrid by using multi-layer ant colony optimization , 2016 .

[22]  Kazem Zare,et al.  Optimal bidding and offering strategies of merchant compressed air energy storage in deregulated electricity market using robust optimization approach , 2018 .

[23]  Behnam Mohammadi-Ivatloo,et al.  Robust optimization based price-taker retailer bidding strategy under pool market price uncertainty , 2015 .

[24]  G Hamed Shakouri,et al.  Multi-objective cost-load optimization for demand side management of a residential area in smart grids , 2017 .

[25]  Hassan Ghasemi,et al.  Residential Microgrid Scheduling Based on Smart Meters Data and Temperature Dependent Thermal Load Modeling , 2014, IEEE Transactions on Smart Grid.

[26]  Melvyn Sim,et al.  Robust discrete optimization and network flows , 2003, Math. Program..

[27]  Kazem Zare,et al.  Heating and power hub models for robust performance of smart building using information gap decision theory , 2018 .

[28]  Carlos Henggeler Antunes,et al.  Integrated Management of Energy Resources in Residential Buildings—A Markovian Approach , 2018, IEEE Transactions on Smart Grid.

[29]  Amjad Anvari-Moghaddam,et al.  Optimal Smart Home Energy Management Considering Energy Saving and a Comfortable Lifestyle , 2016, IEEE Transactions on Smart Grid.

[30]  Behnam Mohammadi-Ivatloo,et al.  Robust scheduling of thermal, cooling and electrical hub energy system under market price uncertainty , 2019, Applied Thermal Engineering.

[31]  Hêriş Golpîra,et al.  A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty , 2019, Energy.

[32]  Kankar Bhattacharya,et al.  Optimal Demand Response for Distribution Feeders With Existing Smart Loads , 2018, IEEE Transactions on Smart Grid.

[33]  Ryohei Yokoyama,et al.  Optimal Operations Management of Residential Energy Supply Networks with Power and Heat Interchanges , 2017 .

[34]  Fei Wang,et al.  Multi-Objective Optimization Model of Source–Load–Storage Synergetic Dispatch for a Building Energy Management System Based on TOU Price Demand Response , 2018, IEEE Transactions on Industry Applications.

[35]  A. Rahimi-Kian,et al.  Cost-effective and comfort-aware residential energy management under different pricing schemes and weather conditions , 2015 .

[36]  Mehdi Rahmani-andebili,et al.  Scheduling deferrable appliances and energy resources of a smart home applying multi-time scale stochastic model predictive control , 2017 .

[37]  Hoay Beng Gooi,et al.  Micro-generation dispatch in a smart residential multi-carrier energy system considering demand forecast error , 2016 .

[38]  Kostas Kalaitzakis,et al.  Development of Demand Response Energy Management Optimization at Building and District Levels Using Genetic Algorithm and Artificial Neural Network Modelling Power Predictions , 2018, Energies.

[39]  Ozan Erdinc,et al.  Economic impacts of small-scale own generating and storage units, and electric vehicles under different demand response strategies for smart households , 2014 .

[40]  Nadeem Javaid,et al.  Energy Optimization in Home Energy Management System Using Artificial Fish Swarm Algorithm and Genetic Algorithm , 2017, INCoS.

[41]  Amin Safari,et al.  Real-time based approach for intelligent building energy management using dynamic price policies , 2018 .

[42]  Shahram Jadid,et al.  Optimal electrical and thermal energy management of a residential energy hub, integrating demand response and energy storage system , 2015 .

[43]  Mumtaz Karatas,et al.  A robust optimization approach to hybrid microgrid operation using ensemble weather forecasts , 2017 .

[44]  David Kendrick,et al.  GAMS, a user's guide , 1988, SGNM.

[45]  Farrokh Aminifar,et al.  Load commitment in a smart home , 2012 .

[46]  Juan M. Corchado,et al.  Stochastic interval-based optimal offering model for residential energy management systems by household owners , 2019, International Journal of Electrical Power & Energy Systems.

[47]  Kyung Sup Kwak,et al.  Interoperable Internet-of-Things platform for smart home system using Web-of-Objects and cloud , 2018 .

[48]  Behnam Mohammadi-Ivatloo,et al.  Optimal bidding strategy of electricity retailers using robust optimisation approach considering time-of-use rate demand response programs under market price uncertainties , 2015 .

[49]  Yang Chen,et al.  A collaborative operation decision model for distributed building clusters , 2015 .

[50]  Prodromos Daoutidis,et al.  Energy management and load shaping for commercial microgrids coupled with flexible building environment control , 2018 .

[51]  Sayyad Nojavan,et al.  A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism , 2016 .

[52]  Sajjad Golshannavaz,et al.  A multi-objective HEM strategy for smart home energy scheduling: A collaborative approach to support microgrid operation , 2018 .

[53]  Long Zhao,et al.  Job Scheduling With Uncertain Local Generation in Smart Buildings: Two-Stage Robust Approach , 2014, IEEE Transactions on Smart Grid.

[54]  Alexander Rassau,et al.  An efficient scheme for residential load scheduling integrated with demand side programs and small-scale distributed renewable energy generation and storage , 2018, International Transactions on Electrical Energy Systems.

[55]  Kun Yu,et al.  Robust Optimization of Power Consumption for Public Buildings Considering Forecasting Uncertainty of Environmental Factors , 2018 .

[56]  Dan Wang,et al.  Robust optimization for load scheduling of a smart home with photovoltaic system , 2015 .

[57]  Hamidreza Zareipour,et al.  Home energy management incorporating operational priority of appliances , 2016 .

[58]  Weicong Kong,et al.  Coordinated residential energy resource scheduling with vehicle-to-home and high photovoltaic penetrations , 2018 .

[59]  Pierluigi Mancarella,et al.  Optimization under uncertainty of thermal storage-based flexible demand response with quantification of residential users' discomfort , 2015, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[60]  Lazaros G. Papageorgiou,et al.  Fair cost distribution among smart homes with microgrid , 2014 .

[61]  Hongbin Sun,et al.  Feasible region method based integrated heat and electricity dispatch considering building thermal inertia , 2017 .

[62]  Omid Abrishambaf,et al.  Demand response implementation in smart households , 2017 .

[63]  Amjad Anvari-Moghaddam,et al.  A multi-agent based energy management solution for integrated buildings and microgrid system , 2017 .

[64]  F. Jolai,et al.  Optimal investment and unit sizing of distributed energy systems under uncertainty: A robust optimization approach , 2014 .

[65]  P. Siano,et al.  Optimal behavior of smart households facing with both price-based and incentive-based demand response programs , 2017, 2017 IEEE Manchester PowerTech.

[66]  Olivier Deblecker,et al.  Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule , 2018 .

[67]  Vincent W. S. Wong,et al.  Residential Demand Side Management Under High Penetration of Rooftop Photovoltaic Units , 2016, IEEE Transactions on Smart Grid.

[68]  Jiangfeng Zhang,et al.  Residential load management in an energy hub with heat pump water heater , 2017 .

[69]  Yi-Ping Phoebe Chen,et al.  True real time pricing and combined power scheduling of electric appliances in residential energy management system , 2016 .