Peak Load Reduction in a Smart Building Integrating Microgrid and V2B-Based Demand Response Scheme

2019 ◽  
Vol 13 (3) ◽  
pp. 3274-3282 ◽  
Author(s):  
Hanane Dagdougui ◽  
Ahmed Ouammi ◽  
Louis A. Dessaint
Keyword(s):  
Demand Response ◽  
Peak Load ◽  
Load Reduction ◽  
Smart Building ◽  
Response Scheme

A Model of Continuous Optimized Power Flow with DR

2013 ◽  
Vol 805-806 ◽  
pp. 452-457
Author(s):  
Wen Bo Mao ◽  
Ke Wang ◽  
Jian Tao Liu
Keyword(s):  
Power System ◽  
Demand Response ◽  
Cost Reduction ◽  
Power Flow ◽  
Peak Load ◽  
Load Reduction ◽  
Interruptible Load ◽  
Time Price ◽  
The Cost ◽  
Reduction Cost

A model of continuous optimized power flow (COPF) is proposed, concluding demand response (DR). According to different implementation mechanisms, a series of DR models are built, such as: time of use (TOU), real time price (RTP), critical peak price (CPP), and interruptible load (IL). The influences of these kinds of DR on power system are analyzed, including peak load reduction, cost reduction, and reservation optimization. The results show that: DR can cut the cost, reduce the peak load, and promote the reservation optimization.

scholarly journals Developing an Algorithm to Consider Mutliple Demand Response Objectives

2018 ◽  
Vol 8 (1) ◽  
pp. 2621-2626 ◽  
Author(s):  
D. Behrens ◽  
T. Schoormann ◽  
R. Knackstedt
Keyword(s):  
Electric Vehicles ◽  
Demand Response ◽  
Peak Load ◽  
Cost Savings ◽  
Research Field ◽  
Multiple Objectives ◽  
Load Reduction ◽  
Solution Strategy ◽  
Research And Practice ◽  
Technological Improvement

Due to technological improvement and changing environment, energy grids face various challenges, which, for example, deal with integrating new appliances such as electric vehicles and photovoltaic. Managing such grids has become increasingly important for research and practice, since, for example, grid reliability and cost benefits are endangered. Demand response (DR) is one possibility to contribute to this crucial task by shifting and managing energy loads in particular. Realizing DR thereby can address multiple objectives (such as cost savings, peak load reduction and flattening the load profile) to obtain various goals. However, current research lacks algorithms that address multiple DR objectives sufficiently. This paper aims to design a multi-objective DR optimization algorithm and to purpose a solution strategy. We therefore first investigate the research field and existing solutions, and then design an algorithm suitable for taking multiple objectives into account. The algorithm has a predictable runtime and guarantees termination.

A Framework for Demand-Side Management With Demand Response Input

2020 ◽  
Author(s):  
Miguel A. Peinado-Guerrero ◽  
Nicolas A. Campbell ◽  
Jesus R. Villalobos ◽  
Patrick E. Phelan
Keyword(s):  
Demand Response ◽  
Production Scheduling ◽  
Energy Use ◽  
Peak Load ◽  
Load Reduction ◽  
Demand Side ◽  
End User ◽  
Physical Constraints ◽  
Side Load ◽  
To Receive

Abstract A framework is proposed for demand-side load management (DSLM) of manufacturers participating in demand response (DR) programs. Utilities are increasingly focused on enticing their portfolios of energy end-users to adjust their energy use patterns in a mutually beneficial manner such as with DR programs. DR programs allow the utility to receive bulk peak load reduction and the participating end-user to receive credit towards their electricity bills. Once an end-user is enrolled in a DR program, they receive periodic requests for some amount of load reduction, typically the day before. Failing to respond to a DR signal will usually cost the end-user handsomely. The end-user is often left to their own discretion on how to attain the level of load reduction requested by the utility. For a manufacturer, this means if the request in load reduction is high enough, they will need to figure out how to curtail production. On the other hand, if the load reduction requested is small enough to need no disruption to production, the utility may be missing out on untapped DR capabilities that could be offered from the ability of the manufacturer to reschedule their production. In either case, the availability of an optimal plan for the manufacturer to best schedule its production in response to a DR event can maximize the benefits for both parties. Most of the research found in literature addresses production scheduling with minimal energy use or cost with respect to a time-of-use price tariff. A system that communicates the desires of the utility to the end-user for a DR event and provides the end-user with support in the decision-making process remains to be developed. The framework proposed addresses these shortcomings, considering the introduction of IoT capabilities and the physical constraints of the manufacturer.

scholarly journals Optimal Price Based Demand Response of HVAC Systems in Commercial Buildings Considering Peak Load Reduction

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 862 ◽  
Author(s):  
Ah-Yun Yoon ◽  
Hyun-Koo Kang ◽  
Seung-II Moon
Keyword(s):  
Demand Response ◽  
Residential Buildings ◽  
Peak Load ◽  
Electric Utility ◽  
Hvac Systems ◽  
Commercial Buildings ◽  
Pricing Strategy ◽  
Load Reduction ◽  
Level Model ◽  
Photovoltaic Generators

Electric utility companies (EUCs) play an intermediary role of retailers between wholesale market and end-users, maximizing their profits. Retail pricing can be well deployed with the support of EUCs to promote demand response (DR) programs for heating, ventilating, and air-conditioning (HVAC) systems in commercial buildings. This paper proposes a pricing strategy to help EUCs and building operators achieve an optimal DR of price-elastic HVAC systems, considering peak load reduction. The proposed strategy is implemented by adopting a bi-level decision model. The nonlinear thermal response of an experimental building room is modeled using piecewise linear equations, which helps convert the bi-level model to the single-level model. The pricing strategy is implemented considering a time-of-use (TOU) pricing scheme, leading to low price volatility. Case studies are conducted for two types of load curves and the results demonstrate that the proposed strategy helps EUC promote the price-based DR of the commercial buildings for conventional load curves. However, EUC cannot reduce the peak load on duck curve caused by the large introduction of photovoltaic generators, even with price-sensitive HVAC systems in commercial building. This will be addressed in future studies by inducing DR participation of HVAC systems in residential buildings.

A Low Complexity and Secure Demand Response Technique for Peak Load Reduction

2019 ◽  
Vol 10 (3) ◽  
pp. 3259-3268 ◽  
Author(s):  
Ehsan Saeidpour Parizy ◽  
Hamid Reza Bahrami ◽  
Seungdeog Choi
Keyword(s):  
Demand Response ◽  
Peak Load ◽  
Low Complexity ◽  
Load Reduction

scholarly journals Optimizing the time of use tariff with different scenarios of load management

2018 ◽  
Vol 20 (K7) ◽  
pp. 15-20
Author(s):  
Binh Thi Thanh Phan ◽  
Qui Minh Le ◽  
Cuong Viet Vo
Keyword(s):  
Demand Response ◽  
Peak Load ◽  
Electricity Consumption ◽  
Pso Algorithm ◽  
Load Management ◽  
Load Reduction ◽  
Load Curve ◽  
Demand Response Program ◽  
Unit Of Measurement ◽  
Effective Instrument

Demand Response program is applied in many countries as an effective instrument to regulate the electricity consumption. In this program, time of use (TOU) tariff is used widely. Optimal TOU pricing according to different objectives was mentioned in this paper such as peak load reduction, improving load curve, energy conservation, avoiding a new peak load. This is a problem with multiobjective functions in different unit of measurement and is solved by PSO algorithm. An example to find optimal TOU tariff for one utility is also presented in this paper.

scholarly journals Price Based Demand Response for Optimal Frequency Stabilization in ORC Solar Thermal Based Isolated Hybrid Microgrid under Salp Swarm Technique

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2209
Author(s):  
Abdul Latif ◽  
Manidipa Paul ◽  
Dulal Chandra Das ◽  
S. M. Suhail Hussain ◽  
Taha Selim Ustun
Keyword(s):  
Demand Response ◽  
Frequency Control ◽  
Thermal Power ◽  
Peak Load ◽  
Energy System ◽  
Frequency Stabilization ◽  
Load Frequency Control ◽  
Solar Thermal ◽  
Proportional Integral ◽  
Hybrid Microgrid

Smart grid technology enables active participation of the consumers to reschedule their energy consumption through demand response (DR). The price-based program in demand response indirectly induces consumers to dynamically vary their energy use patterns following different electricity prices. In this paper, a real-time price (RTP)-based demand response scheme is proposed for thermostatically controllable loads (TCLs) that contribute to a large portion of residential loads, such as air conditioners, refrigerators and heaters. Wind turbine generator (WTG) systems, solar thermal power systems (STPSs), diesel engine generators (DEGs), fuel cells (FCs) and aqua electrolyzers (AEs) are employed in a hybrid microgrid system to investigate the contribution of price-based demand response (PBDR) in frequency control. Simulation results show that the load frequency control scheme with dynamic PBDR improves the system’s stability and encourages economic operation of the system at both the consumer and generation level. Performance comparison of the genetic algorithm (GA) and salp swarm algorithm (SSA)-based controllers (proportional-integral (PI) or proportional integral derivative (PID)) is performed, and the hybrid energy system model with demand response shows the supremacy of SSA in terms of minimization of peak load and enhanced frequency stabilization of the system.

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