Scalable and Robust Demand Response With Mixed-Integer Constraints

Abstract This paper demonstrates the impact of demand response (DR) on optimal multi-energy systems (MES) design with building integrated photovoltaics (BIPV) on roofs and façades. Building loads and solar potentials are assessed using bottom-up models; the MES design is determined using a Mixed-Integer Linear Programming model (energy hub). A mixed-use district of 170,000 m2 floor area including office, residential, retail, education, etc. is studied under current and future climate conditions in Switzerland and Singapore. Our findings are consistent with previous studies, which indicate that DR generally leads to smaller system capacities due to peak shaving. We further show that in both the Swiss and Singapore context, cost and emissions of the MES can be reduced significantly with DR. Applying DR, the optimal area for BIPV placement increases only marginally for Singapore (~1%), whereas for Switzerland, the area is even reduced by 2-8%, depending on the carbon target. In conclusion, depending on the context, DR can have a noticeable impact on optimal MES and BIPV capacities and should thus be considered in the design of future, energy efficient districts.

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A mixed-integer-linear-logical programming interval-based model for optimal scheduling of isolated microgrids with green hydrogen-based storage considering demand response

Journal of Energy Storage ◽

10.1016/j.est.2022.104028 ◽

2022 ◽

Vol 48 ◽

pp. 104028

Author(s):

Marcos Tostado-Véliz ◽

Salah Kamel ◽

Hany M. Hasanien ◽

Rania A. Turky ◽

Francisco Jurado

Keyword(s):

Demand Response ◽

Optimal Scheduling ◽

Mixed Integer ◽

Logical Programming

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Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract

Energies ◽

10.3390/en12142810 ◽

2019 ◽

Vol 12 (14) ◽

pp. 2810 ◽

Cited By ~ 2

Author(s):

Keon Baek ◽

Woong Ko ◽

Jinho Kim

Keyword(s):

Demand Response ◽

Management System ◽

Reference Model ◽

Storage System ◽

Operating Cost ◽

Energy Resource ◽

Residential Building ◽

Mixed Integer ◽

Distributed Energy ◽

Proposed Model

This study proposes optimal day-ahead demand response (DR) participation strategies and distributed energy resource (DER) management in a residential building under an individual DR contract with a grid-system operator. First, this study introduces a DER management system in the residential building for participation to the day-ahead DR market. The distributed photovoltaic generation system (PV) and energy-storage system (ESS) are applied to reduce the electricity demand in the building and sell surplus energy on the grid. Among loads in the building, lighting (LTG) and heating, ventilation, and air conditioning (HVAC) loads are included in the DR program. In addition, it is assumed that a power management system of an electric vehicle (EV) charging station is integrated the DER management system. In order to describe stochastic behavior of EV owners, the uncertainty of EV is formulated based on their arrival and departure scenarios. For measuring the economic efficiency of the proposed model, we compare it with the DER self-consuming operation model without DR participation. The problem is solved using mixed integer linear programming to minimize the operating cost. The results in summer and winter are analyzed to evaluate the proposed algorithm’s validity. From these results, the proposed model can be confirmed as reducing operation cost compared to the reference model through optimal day-ahead DR capacity bidding and implementation.

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Research on Economic Operation Strategy of CHP Microgrid Considering Renewable Energy Sources and Integrated Energy Demand Response

Sustainability ◽

10.3390/su11184825 ◽

2019 ◽

Vol 11 (18) ◽

pp. 4825 ◽

Cited By ~ 1

Author(s):

Jun Dong ◽

Shilin Nie ◽

Hui Huang ◽

Peiwen Yang ◽

Anyuan Fu ◽

...

Keyword(s):

Renewable Energy ◽

Demand Response ◽

Energy Demand ◽

Renewable Energy Sources ◽

Rapid Development ◽

Utilization Efficiency ◽

Energy Output ◽

Mixed Integer ◽

Energy Structure ◽

Economic Operation

Renewable energy resources (RESs) play an important role in the upgrading and transformation of the global energy structure. However, the question of how to improve the utilization efficiency of RESs and reduce greenhouse gas emissions is still a challenge. Combined heating and power (CHP) is one effective solution and has experienced rapid development. Nevertheless, with the large scale of RESs penetrating into the power system, CHP microgrid economic operation faces great challenges. This paper proposes a CHP microgrid system that contains renewable energy with considering economy, the environment, and system flexibility, and the ultimate goal is to minimize system operation cost and carbon dioxide emissions (CO2) cost. Due to the volatility of renewable energy output, the fuzzy C-means (FCM) and clustering comprehensive quality (CCQ) models were first introduced to generate clustering scenarios of the renewable energy output and evaluate the clustering results. In addition, for the sake of improving the flexibility and reliability of the CHP microgrid, this paper considers the battery and integrated energy demand response (IEDR). Moreover, the strategy choices of microgrid operators under the condition of grid-connected and islanded based on environment and interest aspects are also developed, which have rarely been involved in previous studies. Finally, this stochastic optimization problem is transformed into a mixed integer linear programming (MILP), which simplifies the calculation process, and the results show that the operation mode under different conditions will have a great impact on microgrid economic and environmental benefits.

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Demand Response Optimization Model to Energy and Power Expenses Analysis and Contract Revision

Energies ◽

10.3390/en13112803 ◽

2020 ◽

Vol 13 (11) ◽

pp. 2803 ◽

Cited By ~ 1

Author(s):

Filipe Marangoni ◽

Leandro Magatão ◽

Lúcia Valéria Ramos de Arruda

Keyword(s):

Mathematical Model ◽

Demand Response ◽

Electric Energy ◽

Electric Utility ◽

Mixed Integer ◽

Energy Billing ◽

Response Optimization ◽

Alternative Sources ◽

Local Generation

This paper proposes a mathematical model based on mixed integer linear programming (MILP). This model aids the decision-making process in local generation use and demand response application to power demand contract adequacy by Brazilian consumers/prosumers. Electric energy billing in Brazil has some specificities which make it difficult to consider the choice of the tariff modality, the determination of the optimal contracted demand value, and demand response actions. In order to bridge this gap, the model considers local generation connected to the grid (distributed generation) and establishes an optimized solution indicating power energy contract aspects and the potential reduction in expenses for the next billing period (12 months). Different alternative sources already available or of interest to the consumer can be considered. The proposed mathematical model configures an optimization tool for the feasibility analysis of local generation use and, concomitantly, (i) checking the tariff modality, (ii) revising the demand contract, and (iii) suggesting demand response actions. The presented result shows a significant reduction in the energy and power expenses, which confirms the usefulness of this proposal. In the end, the optimized answers promote benefits for both, the consumer/prosumer and the electric utility.

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Optimal Operation for Economic and Exergetic Objectives of a Multiple Energy Carrier System Considering Demand Response Program

Energies ◽

10.3390/en12203995 ◽

2019 ◽

Vol 12 (20) ◽

pp. 3995 ◽

Cited By ~ 4

Author(s):

Yu Huang ◽

Shuqin Li ◽

Peng Ding ◽

Yan Zhang ◽

Kai Yang ◽

...

Keyword(s):

Demand Response ◽

Test System ◽

Optimal Operation ◽

Energy Carrier ◽

Mixed Integer ◽

Selection Strategy ◽

Operation Strategy ◽

Carrier System ◽

Energy Carriers ◽

Scheduling Model

An MECS (multiple energy carrier system) could meet diverse energy needs owing to the integration of different energy carriers, while the distinction of quality of different energy resources should be taken into account during the operation stage, in addition the economic principle. Hence, in this paper, the concept of exergy is adopted to evaluate each energy carrier, and an economic–exergetic optimal scheduling model is formulated into a mixed integer linear programming (MILP) problem with the implementation of a real-time pricing (RTP)-based demand response (DR) program. Moreover, a multi-objective (MO) operation strategy is applied to this scheduling model, which is divided into two parts. First, the ε-constraint method is employed to cope with the MILP problem to obtain the Pareto front by using the state-of-the-art CPLEX solver under the General Algebraic Modeling System (GAMS) environment. Then, a preferred solution selection strategy is introduced to make a trade-off between the economic and exergetic objectives. A test system is investigated on a typical summer day, and the optimal dispatch results are compared to validate the effectiveness of the proposed model and MO operation strategy with and without DR. It is concluded that the MECS operator could more rationally allocate different energy carriers and decrease energy cost and exergy input simultaneously with the consideration of the DR scheme.

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Hydro-reservoir management and unit-commitment in energy optimization

10.33774/miir-2021-6qw7r ◽

2021 ◽

Author(s):

Flávio Leite Loução Junior ◽

Marlon Sproesser Mathias ◽

Claudia Sagastizábal ◽

Luiz-Rafael Santos ◽

Francisco Nogueira Calmon Sobral

Keyword(s):

Power Systems ◽

Demand Response ◽

Power Plants ◽

Unit Commitment ◽

Thermal Power ◽

Point Of View ◽

Mixed Integer ◽

Thermal Power Plants ◽

Hydro Power ◽

Optimal Dispatch

In partnership with CCEE, CEPEL and RADIX as industrial partners, in 2021 the study group focused on the dynamics of hourly prices when industrial consumers are demand responsive, as a follow-up of the industrial problem tackled in 2018 and 2019, on ``Day-ahead pricing mechanisms for hydro-thermal power systems''. Demand response is currently being tested by the Brazilian independent system operator and by the trading chamber, ONS. The program considers reductions of consumption of some clients as an alternative to dispatching thermal power plants out of the merit order. The day-ahead problem of finding optimal dispatch and prices for the Brazilian system is modelled as a mixed-integer linear programming problem, with non-convexities related to fixed costs and minimal generation requirements for some thermal power plants. The work focuses on the point of view of an individual hydro-power generator, to determine business opportunities related to adhering to a demand response program.

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Matching of Local Load with On-Site PV Production in a Grid-Connected Residential Building

Energies ◽

10.3390/en11092409 ◽

2018 ◽

Vol 11 (9) ◽

pp. 2409 ◽

Cited By ~ 7

Author(s):

Arslan Bashir ◽

Mahdi Pourakbari Kasmaei ◽

Amir Safdarian ◽

Matti Lehtonen

Keyword(s):

Demand Response ◽

Programming Model ◽

Residential Building ◽

Hot Water ◽

Mixed Integer ◽

Efficient Utilization ◽

Space Cooling ◽

Pv Generation ◽

Heating Loads ◽

And Storage

Efficient utilization of renewable generation inside microgrids remains challenging. In most existing studies, the goal is to optimize the energy cost of microgrids by working in synergy with the main grid. This work aimed at maximizing the self-consumption of on-site photovoltaic (PV) generation using an electrical storage, as well as demand response solutions, in a building that was also capable of interacting with the main grid. Ten-minute resolution data were used to capture the temporal behavior of the weather. Extensive mathematical models were employed to estimate the demand for hot-water consumption, space cooling, and heating loads. The proposed framework is cast as mixed-integer linear programming model while minimizing the interaction with the grid. To evaluate the effectiveness of the proposed framework, it was applied to a typical Finnish household. Matching indices were used to evaluate the degree of overlap between generation and demand under different PV penetrations and storage capacities. Despite negative correlation of PV generation with Finnish seasonal consumption, a significant portion of demand can be satisfied solely with on-site PV generation during the spring and summer seasons.

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A set of comprehensive indicators to assess energy flexibility: a case study for residential buildings

E3S Web of Conferences ◽

10.1051/e3sconf/201911104044 ◽

2019 ◽

Vol 111 ◽

pp. 04044

Author(s):

Francesco D’Ettorre ◽

Marcus Brennenstuhl ◽

Anjukan Kathirgamanathan ◽

Mattia De Rosa ◽

Malcolm Yadack ◽

...

Keyword(s):

Demand Response ◽

Residential Buildings ◽

Renewable Energy Sources ◽

Residential Building ◽

Heating System ◽

Mixed Integer ◽

Programming Approach ◽

Building Model ◽

Capacity Change ◽

External Signals

The increasing share of renewable energy sources in the power industry poses challenges for grid management due to the stochastic nature of their production. Besides the traditional supplyside regulation, grid flexibility can also be provided by the demand side. Demand-Response is an attractive approach based on adapting user demand profiles to match grid supply constraints. Nevertheless, defining the flexibility potential related to buildings is not straightforward and continues to pose challenges. Commonly accepted and standardized indicators for quantifying flexibility are still missing. The present paper proposes a new quantification methodology to assess the energy flexibility of a residential building. A set of comprehensive indicators capturing three key elements of building energy flexibility for demand response, notably, capacity, change in power consumption and cost of the demand response action have been identified. The proposed methodology is applied to a residential building, whose heating system is controlled by means of a model predictive control algorithm. The building model is developed on the basis of the experimental data collected in the framework of a European Commission supported H2020 research project Sim4Blocks, which deals with the implementation of demand response in building clusters. The optimal control problem has been investigated by means of mixed-integer linear programming approach. Real time prices are considered as external signals from the grid driving the DR actions. Results show that the proposed indicators, presented in the form of daily performance maps, allow to effectively assess the energy flexibility potential through its main dimensions and can be easily used either by an end-user or a grid-operator perspective to identify day by day the best DR action to be implemented.

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