Building-to-grid predictive power flow control for demand response and demand flexibility programs

Razmara, Meysam; Bharati, Guna R.; Hanover, Drew; Shahbakhti, Mahdi; Paudyal, Sumit; Robinett, Rush D.

doi:10.1016/j.apenergy.2017.06.040

Cited by 107 publications

(34 citation statements)

References 23 publications

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“…The investigation on different aspects of energy cost optimisation using MPC to coordinate the energy management for an electrical system has been conducted during recent years. In [24], an MPC system is designed for a commercial building to optimally manage in real time the energy supply from the grid, PV, and energy storage system. This strategy reduces cost and achieves load rump-rate reduction from the grid.…”

Section: Mpc-based Energy Managementmentioning

confidence: 99%

“…Thus, the 4 5 input matrix is expressed by analysing the vector Eqs. (9) -(21), (23), (24), (25) and the expressions of discrete state space model given by Eq. (22).…”

Section: System Designmentioning

confidence: 99%

“…The state vector is given by Eq. (24) and the state space model expressed by Eq. (16) describe the design approach of the output matrix.…”

Section: System Designmentioning

confidence: 99%

See 2 more Smart Citations

An optimal energy management system for a commercial building with renewable energy generation under real-time electricity prices

Mbungu

Bansal

Naidoo

et al. 2018

Sustainable Cities and Society

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Highlights• Develops a real-time electricity pricing structure in conjunction with TOU electricity tariff. • Develops an adaptive strategy in the framework of the smart grid using MPC design. • Develops a new approach to optimization of the cost of energy in real-time electricity pricing environment. • Designs an optimal strategy for integrating PV with battery storage to the grid in realtime electricity pricing scheme. • Gives the consumer an opportunity to deal with the cost of electricity usage.Abstract-This paper presents an approach to the energy management and control of the effective cost of energy in real-time electricity pricing environment. The strategy aims to optimise the overall energy flow in the electrical system that minimises the cost of power consumption from the grid. To substantiate these claims different cases of time-of-use (TOU) and renewable energy electricity tariff, i.e. in summer and winter seasons, and the robustness of system is analysed. A given energy demand for commercial usage in the city of Tshwane (South Africa) is used to investigate the behaviour of the designed method during low and high demand periods. As grid integrated renewable energy resources, photovoltaic (PV) is an important consideration in assuring excellent power supply and environmental issues in the commercial building. An adaptive optimal approach in the framework of model predictive control (MPC) is designed to coordinate the energy flow on the electrical system. The results show that the proposed adaptive MPC strategy can promote the new approach of an optimal electrical system design, which reduces the energy cost to pay the utility grid by about 46 % or more depending on the set target. Index Terms-Battery bank, Energy management, Model predictive control, Photovoltaic, Smart grid, Time-of-use tariff. NOMENCLATURE state matrix (-) input matrix (-) cost of electricity to pay or output vector (Rand or R) 1 cost of electricity to pay the utility grid (Rand or R) 2 cost of electricity consumption from the renewable energy (Rand or R) 3 cost of electricity consumption by the load (Rand or R) output matrix (-) 1 input vector (kWh) 1 energy flow of the utility grid (kWh) 2 energy flow of the PV (kWh) 3 energy flow of the charging of battery (kWh) 4 energy flow of the discharging of battery (kWh) energy consumption (kWh) charging energy on battery (kWh) discharging energy from battery (kWh) The deployment of buildings' energy management systems started in the 1970s when the development of direct digital control signal from the advent of a microprocessor was introduced.It offers the ability to control and manage the energy system by providing the users with a betterquality environment. Since its inception, it has been observed that the development of energy Page 3 of 38 energy demand (kWh) energy drawn from battery (kWh) energy consumption at sample (kWh) energy supply from grid (kWh) maximum energy from battery (kWh) energy nominal on battery (kWh) energy supply from photovoltaic array (kWh) PV energy consumption at...

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Section: Mpc-based Energy Managementmentioning

confidence: 99%

“…Thus, the 4 5 input matrix is expressed by analysing the vector Eqs. (9) -(21), (23), (24), (25) and the expressions of discrete state space model given by Eq. (22).…”

Section: System Designmentioning

confidence: 99%

See 1 more Smart Citation

An optimal energy management system for a commercial building with renewable energy generation under real-time electricity prices

Mbungu

Bansal

Naidoo

et al. 2018

Sustainable Cities and Society

View full text Add to dashboard Cite

show abstract

“…This district consists of 23 residential buildings having 264 apartments and is thermally fed by ground source heat pumps (GSHP); thus emphasizing the primary use of electrical energy for heating purposes. Indeed, GSHP represent a significant research field [5,6], so that they are at the cutting edges of research with the demand side management (DSM) in order to manage electric grid constraints [7].…”

Section: Introductionmentioning

confidence: 99%

Impact of Heat Pump Flexibility in a French Residential Eco-District

et al. 2018

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This paper investigates the impact of load shedding strategies on a block of multiple buildings. It particularly deals with the quantification of the factors i.e., peak shaving, occupants’ thermal comfort or CO 2 emission reduction and how to quickly quantify them. To achieve this goal, the paper focuses on a new residential district, thermally fed by heat pumps. Four modeling approaches were implemented in order to estimate buildings’ response towards load shedding. Two schemes were combined in order to study an overall load shedding. This strategy for the neighborhood has proved itself efficient for both peak shaving and thermal comfort. Most of the clipped heating load during the peak period is shifted to low-consumption periods, providing an effective peak shaving. The thermal comfort is guaranteed for at least 96% of the time. For CO 2 emissions reduction, the link between consumption reduction and CO 2 emissions savings should be realized carefully, since shifting the consumption could increase these emissions.

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“…A conventional definition states that DR is a program of actions, aimed at changes in habits of end-use customers in consuming energy [1]; these changes are mainly driven by price signals and discounted rates that discourage the use of electricity during peak hours and allow savings on bills [2]. The easiest way to induce a customer to change his habits in using electricity is to schedule its electric loads; the bigger the savings in the bill achieved through loads scheduling, the higher the participation of the customer in a DR program.…”

Section: Introductionmentioning

confidence: 99%

An Energy Box in a Cloud-Based Architecture for Autonomous Demand Response of Prosumers and Prosumages

et al. 2017

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Abstract:The interest in the implementation of demand response programs for domestic customers within the framework of smart grids is increasing, both from the point of view of scientific research and from the point of view of real applications through pilot projects. A fundamental element of any demand response program is the introduction at customer level of a device, generally named energy box, able to allow interaction between customers and the aggregator. This paper proposes two laboratory prototypes of a low-cost energy box, suitable for cloud-based architectures for autonomous demand response of prosumers and prosumages. Details on how these two prototypes have been designed and built are provided in the paper. Both prototypes are tested in the laboratory along with a demonstration panel of a residential unit, equipped with a real home automation system. Laboratory tests demonstrate the feasibility of the proposed prototypes and their capability in executing the customers' loads scheduling returned by the solution of the demand-response problem. A personal computer and Matlab software implement the operation of the aggregator, i.e., the intermediary of the energy-integrated community constituted by the customers themselves, who participate in the demand response program.

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Building-to-grid predictive power flow control for demand response and demand flexibility programs

Cited by 107 publications

References 23 publications

An optimal energy management system for a commercial building with renewable energy generation under real-time electricity prices

An optimal energy management system for a commercial building with renewable energy generation under real-time electricity prices

Impact of Heat Pump Flexibility in a French Residential Eco-District

An Energy Box in a Cloud-Based Architecture for Autonomous Demand Response of Prosumers and Prosumages

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