Bilevel optimization to deal with demand response in power grids: models, methods and challenges

Abstract Commercial buildings generally have large thermal inertia, and thus can provide services to power grids (e.g., demand response (DR)) by modulating their Heating, Ventilation, and Air Conditioning (HVAC) systems. Shifting consumption on timescales of minutes to an hour can be accomplished through temperature setpoint adjustments that affect HVAC fan consumption. Estimating the counterfactual baseline power consumption of HVAC fans is challenging but is critical for assessing the capacity and participation of DR from HVAC fans in grid-interactive efficient buildings (GEBs). DR baseline methods have been developed for whole-building power profiles. This work evaluates those methods on total HVAC fan power profiles, which have different characteristics than whole-building power profiles. Specifically, we assess averaging methods (e.g., Y-day average, HighXofY, and MidXofY, with and without additive adjustments), which are the most commonly used in practice, and a least squares-based linear interpolation method recently developed for baselining HVAC fan power. We use empirical submetering data from HVAC fans in three University of Michigan buildings in our assessment. We find that the linear interpolation method has a low bias and by far the highest accuracy, indicating that it is potentially the most effective existing baseline method for quantifying the effects of short-term load shifting of HVAC fans. Overall, our results provide new insights on the applicability of existing DR baseline methods to baselining fan power and enable more widespread contribution of GEBs to DR and other grid services.

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Demand Response Architectures and Load Management Algorithms for Energy-Efficient Power Grids: A Survey

2012 Seventh International Conference on Knowledge, Information and Creativity Support Systems ◽

10.1109/kicss.2012.45 ◽

2012 ◽

Cited By ~ 31

Author(s):

Yee Wei Law ◽

Tansu Alpcan ◽

Vincent C.S. Lee ◽

Anthony Lo ◽

Slaven Marusic ◽

...

Keyword(s):

Demand Response ◽

Energy Efficient ◽

Power Grids ◽

Load Management ◽

Efficient Power ◽

Management Algorithms

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The Strategy of Integrated Demand Response Considering the Interaction Between Superior Power Grids and Factories

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/371/3/032057 ◽

2019 ◽

Vol 371 ◽

pp. 032057

Author(s):

Yuhong Zhang ◽

Yi Luo ◽

Yingying Deng ◽

Xiao Wang ◽

Libo Lian

Keyword(s):

Demand Response ◽

Power Grids

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A novel optimization model for integrating carbon constraint with demand response and real-time pricing

International Journal of Mathematics for Industry ◽

10.1142/s2661335220500057 ◽

2020 ◽

pp. 2050005

Author(s):

Dinh Hoa Nguyen

Keyword(s):

Real Time ◽

Demand Response ◽

Optimization Model ◽

Consumer Satisfaction ◽

Carbon Emission ◽

Renewable Energy Sources ◽

Power Grids ◽

Power Scheduling ◽

Generation Cost ◽

Real Time Pricing

Since the global warming has recently become more severe causing many serious changes on the weather, economy, and society worldwide, lots of efforts have been put forward to prevent it. As one of the most important energy sectors, improvements in electric power grids are required to address the challenge of suppressing the carbon emission during electric generation especially when utilizing fossil-based fuels, while increasing the use of renewable and clean sources. This paper hence presents a novel optimization model for tackling the problems of optimal power scheduling and real-time pricing in the presence of a carbon constraint while taking into account a demand response possibility, which may provide a helpful method to limit the carbon emission from conventional generation while promoting renewable generation. The critical aspects include explicitly integrating the cost of emission with the total generation cost of conventional generation and combining it with the consumer satisfaction function. As such, conventional generation units must carefully schedule their power generation for their profits, while consumers, with the help from renewable energy sources, are willing to adjust their consumption to change the peak demand. Overall, a set of compromised solution called the Pareto front is derived upon which the conventional generating units choose their optimal generation profile to satisfy a given carbon constraint.

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A bilevel optimization approach to demand response management for the smart grid

2016 IEEE Congress on Evolutionary Computation (CEC) ◽

10.1109/cec.2016.7743807 ◽

2016 ◽

Cited By ~ 4

Author(s):

Fan-Lin Meng ◽

Xiao-Jun Zeng

Keyword(s):

Smart Grid ◽

Demand Response ◽

Bilevel Optimization ◽

Optimization Approach

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The Impact of Demand Response Programs on Reducing the Emissions and Cost of A Neighborhood Home Microgrid

Applied Sciences ◽

10.3390/app9102097 ◽

2019 ◽

Vol 9 (10) ◽

pp. 2097 ◽

Cited By ~ 1

Author(s):

Mohammad Hossein Fouladfar ◽

Abdolah Loni ◽

Mahsa Bagheri Tookanlou ◽

Mousa Marzband ◽

Radu Godina ◽

...

Keyword(s):

Energy Management ◽

Demand Response ◽

Dynamic Pricing ◽

Management System ◽

Power Grids ◽

Energy Management System ◽

Increase Energy Efficiency ◽

Market Clearing Price ◽

Generation Costs ◽

The Impact

The desire to increase energy efficiency and reliability of power grids, along with the need for reducing carbon emissions has led to increasing the utilization of Home Micro-grids (H-MGs). In this context, the issue of economic emission dispatch is worthy of consideration, with a view to controlling generation costs and reducing environmental pollution. This paper presents a multi-objective energy management system, with a structure based on demand response (DR) and dynamic pricing (DP). The proposed energy management system (EMS), in addition to decreasing the market clearing price (MCP) and increasing producer profits, has focused on reducing the level of generation units emissions, as well as enhancing utilization of renewable energy units through the DR programs. As a consequence of the nonlinear and discrete nature of the H-MGs, metaheuristic algorithms are applied to find the best possible solution. Moreover, due to the presence of generation units, the Taguchi orthogonal array testing (TOAT) method has been utilized to investigate the uncertainty regarding generation units. In the problem being considered, each H-MG interacts with each other and can negotiate based on their own strategies (reduction of cost or pollution). The obtained results indicate the efficiency of the proposed algorithm, a decrease in emissions and an increase in the profit achieved by each H-MG, by 37% and 10%, respectively.

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On Optimistic and Pessimistic Bilevel Optimization Models for Demand Response Management

Energies ◽

10.3390/en14082095 ◽

2021 ◽

Vol 14 (8) ◽

pp. 2095

Author(s):

Tamás Kis ◽

András Kovács ◽

Csaba Mészáros

Keyword(s):

Demand Response ◽

Optimal Schedule ◽

Bilevel Optimization ◽

Optimization Models ◽

Optimal Consumption ◽

Solution Approach ◽

Exact Procedure ◽

Special Cases ◽

Optimistic Solution ◽

Modeling Assumption

This paper investigates bilevel optimization models for demand response management, and highlights the often overlooked consequences of a common modeling assumption in the field. That is, the overwhelming majority of existing research deals with the so-called optimistic variant of the problem where, in case of multiple optimal consumption schedules for a consumer (follower), the consumer chooses an optimal schedule that is the most favorable for the electricity retailer (leader). However, this assumption is usually illegitimate in practice; as a result, consumers may easily deviate from their expected behavior during realization, and the retailer suffers significant losses. One way out is to solve the pessimistic variant instead, where the retailer prepares for the least favorable optimal responses from the consumers. The main contribution of the paper is an exact procedure for solving the pessimistic variant of the problem. First, key properties of optimal solutions are formally proven and efficiently solvable special cases are identified. Then, a detailed investigation of the optimistic and pessimistic variants of the problem is presented. It is demonstrated that the set of optimal consumption schedules typically contains various responses that are equal for the follower, but bring radically different profits for the leader. The main procedure for solving the pessimistic variant reduces the problem to solving the optimistic variant with slightly perturbed problem data. A numerical case study shows that the optimistic solution may perform poorly in practice, while the pessimistic solution gives very close to the highest profit that can be achieved theoretically. To the best of the authors’ knowledge, this paper is the first to propose an exact solution approach for the pessimistic variant of the problem.

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