The Dispatch Method Based on Demand Response under the Pressure of Energy-Saving

2013 ◽  
Vol 860-863 ◽  
pp. 746-753
Author(s):  
Shu Xiang Wang ◽  
Ji Chun Liu ◽  
Chuang Deng ◽  
Wei Dong Zheng ◽  
Hou Dong Xu ◽  
...  
Keyword(s):  
Energy Saving ◽  
Demand Response ◽  
Optimal Allocation ◽  
Demand Side ◽  
Thermal Unit ◽  
Nsga Ii ◽  
On Demand ◽  
Unit Output ◽  
Grid Operation

To promote the development of energy-saving dispatch under the pressure of energy saving and environmental protection, this paper proposes an energy-saving dispatch method based on considering demand response, which establishes a bi-level optimization model based on the optimal allocation plan of thermal units and interruptible loads, and solve the problem with improved NSGA-II and sensitivity analysis between unit interrupt capacity and thermal unit output. The case study shows that this model can decrease the pollutants at both generation side and demand side significantly with guaranteeing the economic of power grid operation. The model can also give the dispatch schedule of thermal units and interruptible loads accurately and thus has some use value.

Parameter Based Multi-Objective Optimization of Video CODECs

2011 ◽  
pp. 288-308
Author(s):  
F. Al-Abri ◽  
E.A. Edirisinghe ◽  
C. Grecos
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Formulation ◽  
Video Codec ◽  
Video Content ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Video Codecs ◽  
Multi Objective ◽  
On Demand

This chapter presents a generalised framework for multi-objective optimisation of video CODECs for use in off-line, on-demand applications. In particular, an optimization scheme is proposed to determine the optimum coding parameters for a H.264 AVC video codec in a memory and bandwidth constrained environment, which minimises codec complexity and video distortion. The encoding/decoding parameters that have a significant impact on the performance of the codec are initially obtained through experimental analysis. A mathematical formulation by means of regression is subsequently used to associate these parameters with the relevant objectives and define a Multi-Objective Optimization (MOO) problem. Solutions to the optimization problem are reached through a Non-dominated Sorting Genetic Algorithm (NSGA-II). It is shown that the proposed framework is flexible on the number of objectives that can jointly be optimized. Furthermore, any of the objectives can be included as constraints depending on the requirements of the services to be supported. Practical use of the proposed framework is described using a case study that involves video content transmission to a mobile hand.

Research on Demand Side Response System of Electricity Price Under Electricity Market Incentive Mechanism

2021 ◽  
Author(s):  
Fu Xianyu ◽  
Zhou Hongmei ◽  
Qi-jie Jiang ◽  
Ke Fan
Keyword(s):  
Power System ◽  
Demand Response ◽  
Electricity Market ◽  
Incentive Mechanism ◽  
Operating Cost ◽  
Electricity Price ◽  
Demand Side ◽  
Peak Shaving ◽  
Optimal Dispatch ◽  
Grid Operation

Aiming at the traditional day-ahead dispatching scheme of power generation, the paper proposes a power system security optimization dispatching model that considers the demand response of electricity prices under the electricity market incentive mechanism. Based on the peak and valley time-of-use electricity price, the paper establishes an incentive compensation mechanism to encourage users to be active. Participating in demand-side resource scheduling makes the effect of “peak shaving and valley filling” more pronounced. Simultaneously, to rationally configure the reserve capacity of grid operation, the system incorporates the expected power outage loss into the proposed model to ensure the grid operation safety. The analysis of calculation examples based on IEEE24 nodes shows that the power optimal dispatch model proposed in the paper considering demand response and expected outage loss can reduce the operating cost of the power grid under the premise of ensuring a certain level of reliability and realize the economy of the power system in the market environment and safe operation.

scholarly journals Implementation of Advanced Demand Side Management for Microgrid Incorporating Demand Response and Home Energy Management System

2018 ◽  
Vol 3 (4) ◽  
pp. 50 ◽  
Author(s):  
Izaz Zunnurain ◽  
Md. Maruf ◽  
Md. Rahman ◽  
GM Shafiullah
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Energy Cost ◽  
Energy Savings ◽  
Energy Management System ◽  
Demand Side ◽  
Case Study Analysis ◽  
Home Energy Management ◽  
Home Energy Management System

To facilitate the possible technology and demand changes in a renewable-energy dominated future energy system, an integrated approach that involves Renewable Energy Sources (RES)-based generation, cutting-edge communication strategies, and advanced Demand Side Management (DSM) is essential. A Home Energy Management System (HEMS) with integrated Demand Response (DR) programs is able to perform optimal coordination and scheduling of various smart appliances. This paper develops an advanced DSM framework for microgrids, which encompasses modeling of a microgrid, inclusion of a smart HEMS comprising of smart load monitoring and an intelligent load controller, and finally, incorporation of a DR strategy to reduce peak demand and energy costs. Effectiveness of the proposed framework is assessed through a case study analysis, by investigation of DR opportunities and identification of energy savings for the developed model on a typical summer day in Western Australia. From the case study analysis, it is evident that a maximum amount of 2.95 kWh energy can be shifted to low demand periods, which provides a total daily energy savings of 3%. The total energy cost per day is AU$2.50 and AU$3.49 for a house with and without HEMS, respectively. Finally, maximum possible peak shaving, maximum shiftable energy, and maximum standby power losses and energy cost savings with or without HEMS have been calculated to identify the energy saving opportunities of the proposed strategy for a microgrid of 100 houses with solar, wind, and a back-up diesel generator in the generation side.

scholarly journals Determinants of Willingness to Participate in Urban Incentive-Based Energy Demand-Side Response: An Empirical Micro-Data Analysis

2020 ◽  
Vol 12 (19) ◽  
pp. 8052
Author(s):  
Bing Wang ◽  
Qiran Cai ◽  
Zhenming Sun
Keyword(s):  
Energy Saving ◽  
Demand Response ◽  
Energy Demand ◽  
Public Perception ◽  
Policy Implications ◽  
Policy Framework ◽  
Level Energy ◽  
Willingness To Participate ◽  
Demand Side ◽  
The Public

Demand-side management provides important opportunities to integrate renewable sources and enhance the flexibility of urban power systems. With the continuous advancement of the smart grid and electricity market reform, the potential for residential consumers to participate in energy demand response is significantly enhanced. However, not enough is known about the public perception of energy demand response, and how sociopsychological and external factors could affect public willingness to participate. This study investigates the public perception of and willingness to participate in urban energy demand response through a questionnaire survey and employs multiple linear regression models to explore the determinants of public willingness to participate. The results suggest that income level, energy-saving attitudes, behaviors, external motivation factors, and energy-saving technologies are the key factors that determine public willingness to participate. Although most respondents are willing to participate, the effects of monetary incentives are more significant than the effect of spiritual inducements, and respondents are more sensitive to compensation than to dynamic electricity prices. The further improvement of residential responsiveness requires continuous infrastructure building by technical support, public energy-saving awareness, and public perception of energy demand response. Policy implications are proposed to achieve a sufficient residential response from an aggressive policy framework and energy-saving behavioral guidance.

Coordinated Charging of EVs Based on Demand-Side Management

2014 ◽  
Vol 596 ◽  
pp. 760-765
Author(s):  
Yu Kai Li ◽  
Hong Ouyang ◽  
Jia Kui Zhao ◽  
Xiu Kai Rong ◽  
Yi Dong
Keyword(s):  
Large Scale ◽  
Peak Load ◽  
Demand Side Management ◽  
Optimal Number ◽  
Demand Side ◽  
Nsga Ii ◽  
On Demand ◽  
Load Fluctuation ◽  
Power Load ◽  
Coordinated Charging

Electric vehicles (EVs) are adopted as an effective way to reduce the pollution of atmosphere. However, if EVs are implemented in a large scale without control, peak load would increase significantly and the grid may be overloaded. Based on Demand-Side Management (DSM), an coordinated charging method for EVs to address the problem of that is proposed. Considering load fluctuation of power grid as well as time-of-use (TOU) power price, a multi-objective optimization model is formulated to minimize the charging cost and restrain the load fluctuation. Overall power load is composed of original daily load and EV charging load, which is obtained through Monte Carlo simulations. On the basis of this, the optimal number of charging EVs in each period is worked out with NSGA-II algorithm. At last, the case study carried out shows the reasonability of this method.

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