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.

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

scholarly journals Research on low-carbon power planning with gas turbine units based on carbon transactions

2021 ◽  
Vol 252 ◽  
pp. 03060
Author(s):  
Lu Yu ◽  
Shi Shengyao ◽  
Zhang Dachi ◽  
Feng Shunqiang ◽  
Zhang Yuanmei ◽  
...  
Keyword(s):  
Power System ◽  
Gas Turbine ◽  
Carbon Emission ◽  
Peak Load ◽  
Carbon Trading ◽  
Planning Model ◽  
Low Carbon ◽  
Bacterial Colony ◽  
The Cost ◽  
Low Carbon Emission

In the context of low carbon economy, introducing carbon trading and developing low-carbon energy generation is an important means to realize low-carbon development of the power system. Because gas power generation has the advantages of high efficiency, low carbon emission and strong peak load capability, the gas generator unit is added to the planning plan and a low carbon power planning model based on carbon trading is established. The goal of the model is to minimize the cost of the system integration. The cost includes investment operation cost and carbon transaction cost. And the natural gas supply constraints and carbon trading constraints are increased in the constraint condition. Finally, the discrete bacterial colony chemotaxis algorithm is adopted to solve this model. Through the model comparison and sensitivity analysis, it is concluded that the addition of gas turbine unit and carbon trading mechanism can optimize the power supply structure, promote the construction of low carbon unit. and realize the conclusion of low carbon emission reduction of power system. And the results verify the effectiveness of the proposed power planning model.

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 Analysis of Challenges Due to Changes in Net Load Curve in South Korea by Integrating DERs

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1310
Author(s):  
Chi-Yeon Kim ◽  
Chae-Rin Kim ◽  
Dong-Keun Kim ◽  
Soo-Hwan Cho
Keyword(s):  
South Korea ◽  
Power System ◽  
Demand Response ◽  
Renewable Energy Sources ◽  
Peak Load ◽  
Demand Forecast ◽  
Load Curve ◽  
Target Values ◽  
Load Pattern ◽  
Net Load

The development of Distributed Energy Resources (DERs) is essential in accordance with the mandatory greenhouse gas (GHG) emission reduction policies, resulting in many DERs being integrated into the power system. Currently, South Korea is also focusing on increasing the penetration of renewable energy sources (RES) and EV by 2030 to reduce GHGs. However, indiscriminate DER development can give a negative impact on the operation of existing power systems. The existing power system operation is optimized for the hourly net load pattern, but the integration of DERs changes it. In addition, since ToU (Time-of-Use) tariff and Demand Response (DR) programs are very sensitive to changes in the net load curve, it is essential to predict the hourly net load pattern accurately for the modification of pricing and demand response programs in the future. However, a long-term demand forecast in South Korea provides only the total amount of annual load (TWh) and the expected peak load level (GW) in summer and winter seasons until 2030. In this study, we use the annual photovoltaic (PV) installed capacity, PV generation, and the number of EV based on the target values for 2030 in South Korea to predict the change in hourly net load curve by year and season. In addition, to predict the EV charging load curve based on Monte Carlo simulation, the EV users’ charging method, charging start time, and State-of-Charge (SoC) were considered. Finally, we analyze the change in hourly net load curve due to the integration of PV and EV to determine the amplification of the duck curve and peak load time by year and season, and present the risks caused by indiscriminate DERs development.

A unique mathematical optimization approach for examination of failure effects on electric power transmission grids by combined environmental and economic indicators

2017 ◽  
Vol 14 (3) ◽  
pp. 237-248
Author(s):  
Ali Azadeh ◽  
Maryam Sattarian ◽  
Azadeh Arjmand
Keyword(s):  
Power System ◽  
Electric Power ◽  
Power Flow ◽  
Power Transmission ◽  
Environmental Issues ◽  
Influential Factors ◽  
Optimization Approach ◽  
Content Type ◽  
Total Cost ◽  
The Cost

Purpose To achieve the optimum performance of electric transmission power system performance, the possibility of generators’ failure and the consequences are amongst the most important and real assumptions which should be taken into consideration. This paper aims to recognize the most influential factors on generators’ failures that can have a deep effect on the total cost and environmental issues. The integrated proposed approach is useful for investigating the generators’ failure effects on the performance of electric power transmission grids from the economic and environmental perspectives. In other words, the cost and pollution minimization policies are considered to decrease the unfavorable generators’ failure effects on electric power flow. Design/methodology/approach The data used in this study are gathered from a real case in USA in first step, the influential generator points that their failure has a significant effect on the objective function, have been recognized. Then, different failure scenarios are defined, and the optimum values in each of these scenarios through the GAMS modeling software are found. Consequently, by using a two-level factorial design approach, the critical generators across the power grid are determined. Findings The results show that by using such information, it is possible to detect the significant nodes in the power system grid and have a better maintenance plan. In addition, by means of this analysis and changing the capacity of main generators, it is possible to significantly reduce the operation costs. By comparing the indexes in case of the generator’s location, it seems that some of them are critical because of their capacity and position in the network (as their failure causes infeasibility in the model). Also, some of these deficiencies caused considerable index changes and critical consequences. Practical implications The integrated proposed approach is useful for investigating the generators’ failure effects on the performance of electric power transmission grids from the economic and environmental perspectives. In other words, the cost and pollution minimization policies are considered to decrease the unfavorable generators’ failure effects on electric power flow. Social implications This paper endeavors to recognize the most influential factors on generators’ failures that can have a deep effect on the total cost and environmental issues. Originality/value The integrated proposed approach is useful for investigating the generators’ failure effects on the performance of electric power transmission grids from the economic and environmental perspectives. In other words, the cost and pollution minimization policies are considered to decrease the unfavorable generators’ failure effects on electric power flow.

scholarly journals Optimized placement of multiple FACTS devices using PSO and CSA algorithms

2020 ◽  
Vol 10 (4) ◽  
pp. 3350
Author(s):  
Basanagouda Patil ◽  
S. B. Karajgi
Keyword(s):  
Power System ◽  
Power Distribution ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Search Algorithm ◽  
Optimization Algorithms ◽  
Cost Calculation ◽  
Facts Devices ◽  
Deregulated Power System ◽  
The Cost

This paper is an attempt to develop a multi-facts device placementin deregulated power system using optimization algorithms. The deregulated power system is the recent need in the power distribution as it has many independent sellers and buyers of electricity. The problem of deregulation is the quality of the power distribution as many sellers are involved. The placement of FACTS devices provides the solution for the above problem. There are researches available for multiple FACTS devices. The optimization algorithms like Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) are implemented to place the multiple FACTS devices in a power system. MATLAB based implementation is carried out for applying Optimal Power Flow (OPF) with variation in the bus power and the line reactance parameters. The cost function is used as the objective function. The cost reduction of FACTS as well as generation by placement of different compensators like, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC). The cost calculation is done on the 3-seller scenario. The IEEE 14 bus is taken here as 3-seller system.

scholarly journals Optimal Allocation of FACTS Devices by using multi-Objective Optimal Power Flow and Genetic Algorithms

2012 ◽  
pp. 218-224
Author(s):  
Aditya Tiwari ◽  
K.K. Swarnkar ◽  
Dr.S. Wadhwani ◽  
Dr.A.K. Wadhwani
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Allocation ◽  
Cost Effective ◽  
Transmission System ◽  
Flexible Ac Transmission ◽  
Flexible Ac Transmission System ◽  
Ac Transmission ◽  
The Cost

The introduction of the flexible AC transmission system (FACTS) in the power system reduces the losses, reduces the cost of the generation, improves the stability and also improves the load capability of the system. Some application of the Flexible AC transmission system (FACTS) technologies to existing high voltage power system has proves the use of FACTS technology may be a cost effective option for power delivery system enhancement. Amongst various power electronic devices unified power flow controller (UPFC) may be considered to be a capable of regulating the power flow and minimizing the power loss simultaneously. Since for the cost effective application of the FACTS technology a proper selection of the number and the placement of these devices is required. The main aim of this paper is to propose the methodology based on the genetic algorithm, able to identify the optimal number and the location of the UPFC devices in an assigned power system network for maximizing system capabilities. In order to validate the usefulness of the approach suggested here is , a case study using a IEEE 30-bus power system is presented and discussed.

scholarly journals Generation-Load Coordinative Scheduling considering the Demand-Response Uncertainty of Inverter Air Conditioners

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Wei Hu ◽  
Jin Yang ◽  
Yi Wu ◽  
Weiguo Zhang ◽  
Xueming Li ◽  
...  
Keyword(s):  
Power System ◽  
Demand Response ◽  
Load Scheduling ◽  
Air Conditioners ◽  
Power Scheduling ◽  
Scheduling Model ◽  
Conditioning Equipment ◽  
The Cost ◽  
First Time

Inverter air conditioners (IACs) have gradually become the mainstream of resident air-conditioning equipment. Similar to traditional fixed-frequency air conditioners, IACs have the potential for demand response and load scheduling. However, the uncertainty of IACs is nonnegligible in generation-load scheduling. In this paper, the uncertain demand-response cost of IACs is studied for the first time. Meanwhile, based on the cost, a generation-load coordinative day-ahead scheduling model is proposed. In the scheduling, an IACs aggregator and traditional generators are coordinately dispatched to minimize the expected scheduling cost of the power system. The case study shows that the coordinative scheduling model can reduce the scheduling cost of the power system and encourage the IACs aggregator to improve their responsiveness or reduce their uncertainty, so as to improve the economy and reliability of power scheduling.

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