A MILP formulation for utility scale optimal demand side response

Balasubramaniam, Karthikeyan; Saraf, Parimal; Hazra, Puspal; Hadidi, Ramtin; Makram, Elham B.

doi:10.1109/pesgm.2016.7741956

Cited by 8 publications

(8 citation statements)

References 12 publications

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“…The authors of [16] presented mathematical models for application in several types of loads and operated them in real time. The peak load demand was minimized, taking into consideration the problem constraints, such as the system energy balance and the limitation for power and electrical energy in each load.…”

Section: Literature Reviewmentioning

confidence: 99%

A Mixed Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

et al. 2020

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Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs charge and discharge processes and also those of BESS, in which the binary decision variables represent the charging and discharging of EVs/BESS in each period. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis are considered. The results point to a 65% reduction in peak load consumption supplied by an external power grid and a 28.4% reduction in electricity consumption costs.

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Section: Literature Reviewmentioning

confidence: 99%

A Mixed Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

et al. 2020

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“…In [16], mathematical models for different types of loads is presented, enabling their operation in real time. The objective function aims to minimize the peak load demand over a given day, while its constraints involve electrical energy and power limits for each type of load and the system energy balance.…”

Section: Literature Reviewmentioning

confidence: 99%

A Mixed-Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

Foroozandeh¹,

Ramos²,

Soares³

et al. 2020

Preprint

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Efficient alternatives in energy production and consumption are constantly investigated by increasingly strict policies. In this way, the pollutant emissions that contribute to the greenhouse effect reduce and sustainability of the electricity sector increase. With more than a third of the world's energy consumption, buildings have great potential to contribute these sustainability goals. Additionally, with growing incentives in the Distributed Generation (DG) and Electric Vehicle (EV) industry, it is believed that Smart Buildings (SBs) can be a key in the field of residential energy sustainability in the future. In this work, an energy management system in SBs are developed to reduce the power demanded of a residential building. In order to balance the demand and power provided by the grid, microgrids such as Battery Energy Storage System (BESS), EVs and Photovoltaic Generation panels (PV) are used. Here, a Mixed Binary Linear Programming formulation (MBLP) is proposed to optimize the charge and discharge scheduling of EVs and also BESS. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis is considered. The results point a 65% reduction in peak load consumption supplied by grid and a 28.4% reduction in electricity consumption costs.

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“…Balasubramaniam et al [18] intend to develop mathematic models for different types of loads, making possible their operation in real time. In this way, adjustable loads, constant loads, dependent loads (are influenced by the operation of other loads) and VEs are considered.…”

Section: Smart Building Linear Optimization Reviewmentioning

confidence: 99%

A Short Review on Smart Building Energy Resource Optimization

Joench

Soares

Lezama

et al. 2019

2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia)

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Motivated by increasingly strict policies aiming to reduce the pollutants emission that contribute to the greenhouse gases effect and seeking the sustainability of the electricity sector, buildings have great potential to contribute to these goals. For accounting more than a third of the world's energy consumption and combining the growing incentive in Distributed Generation (DG) and the electric vehicle (EV) industry, smart buildings will be a key development in the years to come. In this way, this work presents an introduction to the linear programming (LP) optimization method and review the main works related to the scope of Smart Buildings (SB) energy resources optimization modeled as LP, with the objective to analyze different approaches taken to meet their goals.

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A MILP formulation for utility scale optimal demand side response

Cited by 8 publications

References 12 publications

A Mixed Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

A Mixed Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

A Mixed-Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

A Short Review on Smart Building Energy Resource Optimization

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