scholarly journals Demand response model for TOU (Time of Use) analysis

2016 ◽  
Vol 19 (4) ◽  
pp. 5-13
Author(s):  
Binh Thi Thanh Phan ◽  
Thao Thi Thu Huynh
Keyword(s):  
Demand Response ◽  
Demand Elasticity ◽  
Analytical Models ◽  
Cost Share ◽  
The Third ◽  
Knowing That ◽  
The Neural Network ◽  
Demand Response Program ◽  
The Cost ◽  
Electrical Consumption

The demand response program is focused on changing the electrical consumption as the response to the time of use tariff changing. This program is considered by utilities currently. To estimate the effectiveness of TOU changing, the works try to find the analytical models expressing the changing of electrical consumption and electrical prices. All models are based on the assumption about the optimal response. This paper proposed three ways to find the models. The first way is based on the cost-share function knowing that the response is optimal. The second way is an approximately estimation of demand elasticity coefficients. The third is based on the neural network. The two first ways tried to find the analytical model, the third focused on the consumption response by prices of day.

scholarly journals Modelling Demand Response to Alleviate Congestion in Active Power Market

2021 ◽  
Vol 10 (2) ◽  
pp. , 1277-1283
Keyword(s):  
Demand Response ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Power Market ◽  
Congestion Management ◽  
Demand Elasticity ◽  
Willingness To Participate ◽  
Optimal Power ◽  
Demand Response Program ◽  
The Cost

A new method of congestion management in deregulated and competitive power system based on a combination of Demand Response (DR) program and generation re-dispatch is proposed in this research. One of DR program called Emergency Demand Response Program (EDRP) is carried out through customer's willingness to participate in this program in order to reduce their consumption during congestion. EDRP is modeled based on demand elasticity of the load and considering incentives. Different level of demand elasticity values is introduced to the customers to observe their contribution in congestion relief. The proposed method is examined on IEEE 30 bus system by using the Optimal Power Flow tool and it indicates that by integrating the customer’s elasticity for EDRP can decrease the cost to relieve the congestion and lead more benefit for all participants. The obtained results are the cost to manage congestion problem and optimal re-dispatch of generators by involving the participation of customers in EDRP.

Customer reward-based demand response program to improve demand elasticity and minimise financial risk during price spikes

2018 ◽  
Vol 12 (15) ◽  
pp. 3764-3771 ◽  
Author(s):  
Dao H. Vu ◽  
Kashem M. Muttaqi ◽  
Ashish P. Agalgaonkar ◽  
Abdesselam Bouzerdoum
Keyword(s):  
Demand Response ◽  
Financial Risk ◽  
Demand Elasticity ◽  
Demand Response Program ◽  
Price Spikes

scholarly journals An enhanced operation model for energy storage system of a typical combined cool, heat and power based on demand response program: The application of mixed integer linear programming

2018 ◽  
Vol 40 (1) ◽  
pp. 47-74 ◽  
Author(s):  
Amirhossein Eshraghi ◽  
Gholamreza Salehi ◽  
Seyedmohammadreza Heibati ◽  
Kamran Lari
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Demand Response ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Residential Building ◽  
Mixed Integer ◽  
Demand Response Program ◽  
Micro Grid ◽  
The Cost

A model for operating an energy hub-based multiple energy generation micro-grid is optimized using the demand response program. The optimized objective model is validated against energy demand of a residential building in Tehran, Iran. The mathematical model and optimal analysis of the proposed tri-generation micro-grid are implemented by using a real-world modelling and considering the constraints of the storage system, demand response program and the performance of the devices and the power and gas grids. The dynamic optimal operation model is prepared on the basis of the mixed integer linear programming on the subsequent day and is solved to minimize the costs of energy supply. To demonstrate the improvements, different scenarios are developed so that the renewable energy resources and storages are fed into the combined cool, heat and power system gradually. The results reveal that the inclusion of each element results in a significant improvement in the operational parameters of the micro energy grid. Scenario 1 includes a combined cool, heat and power system alone, Scenario 2 is supplemented with renewable wind and solar energy resources in addition to combined cool, heat and power system and Scenario 3 includes electrical, heat and cold storages in addition to combined cool, heat and power system and renewable energy sources. Scenario 4 is similar to Scenario 3 in terms of equipment, but the only difference lies in the use of the demand response program in the former. Total operational cost is 12.7% lower in Scenario 2 than in Scenario 1, 9.2% lower in Scenario 3 than in Scenario 2 and 8.6% lower in Scenario 4 than in Scenario 3. Practical application: An optimized operation method is prepared for combined cool, heat and power systems running in different operation modes in which renewable energy sources and storages are added to the combined cool, heat and power and the demand response program is applied. The results reveal that the cost of energy supply, including the cost of electricity, gas and pollutant emissions, is reduced and the qualitative parameters of the operation, including efficiency and reliability of building micro-grid, are increased. The proposed algorithm and the evaluation method will enable building operators to plan demand response activity on the residential building in Tehran, while this can be extended to other buildings too.

Case Study—Failure Analysis of a Multiplexer

2016 ◽  
Author(s):  
Michael Woo ◽  
Marcos Campos ◽  
Luigi Aranda
Keyword(s):  
Failure Analysis ◽  
High Reliability ◽  
Component Failure ◽  
Root Cause ◽  
Knowing That ◽  
Cause Of Failure ◽  
The Cost

Abstract A component failure has the potential to significantly impact the cost, manufacturing schedule, and/or the perceived reliability of a system, especially if the root cause of the failure is not known. A failure analysis is often key to mitigating the effects of a componentlevel failure to a customer or a system; minimizing schedule slips, minimizing related accrued costs to the customer, and allowing for the completion of the system with confidence that the reliability of the product had not been compromised. This case study will show how a detailed and systemic failure analysis was able to determine the exact cause of failure of a multiplexer in a high-reliability system, which allowed the manufacturer to confidently proceed with production knowing that the failure was not a systemic issue, but rather that it was a random “one time” event.

scholarly journals Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4597
Author(s):  
Zi-Xuan Yu ◽  
Meng-Shi Li ◽  
Yi-Peng Xu ◽  
Sheraz Aslam ◽  
Yuan-Kang Li
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Positive Impact ◽  
Environmental Aspects ◽  
Component Size ◽  
Cost Of Energy ◽  
Four Seasons ◽  
Demand Response Program ◽  
Real Time Pricing

The optimal planning of grid-connected microgrids (MGs) has been extensively studied in recent years. While most of the previous studies have used fixed or time-of-use (TOU) prices for the optimal sizing of MGs, this work introduces real-time pricing (RTP) for implementing a demand response (DR) program according to the national grid prices of Iran. In addition to the long-term planning of MG, the day-ahead operation of MG is also analyzed to get a better understanding of the DR program for daily electricity dispatch. For this purpose, four different days corresponding to the four seasons are selected for further analysis. In addition, various impacts of the proposed DR program on the MG planning results, including sizing and best configuration, net present cost (NPC) and cost of energy (COE), and emission generation by the utility grid, are investigated. The optimization results show that the implementation of the DR program has a positive impact on the technical, economic, and environmental aspects of MG. The NPC and COE are reduced by about USD 3700 and USD 0.0025/kWh, respectively. The component size is also reduced, resulting in a reduction in the initial cost. Carbon emissions are also reduced by 185 kg/year.

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