Optimal reactive power dispatch with wind power integrated using group search optimizer with intraspecific competition and lévy walk

Li, Yuanzheng; Li, Mengshi

doi:10.1007/s40565-014-0076-9

Cited by 24 publications

(12 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Through offline and online case studies over a modified IEEE 34-bus test distribution system, the experimental results gave evidence that, (1). Reactive power optimization based on load curve prediction and segmentation is able to reduce reactive power compensation device adjustment times effectively, reduce network losses during a duty cycle to some extent, and at the same time improve computational efficiency; (2). Compared with using individual load curve for segmentation, using integrated load curve is adequate to produce better optimization performance w.r.t.…”

Section: Discussionmentioning

confidence: 99%

“…The second filtering method [17], noted as method 2, refers to a different calculation of the filtered curve, as shown in (2).…”

Section: Of 12mentioning

confidence: 99%

“…Reactive power optimization aims to produce optimal reactive power-compensation device control strategies in order to achieve minimum delivery losses and at the same time to satisfy specific operating constraints such as requirements for voltage deviations [1,2]. The problem in essence is a mixed-integer non-linear programming problem.…”

Section: Introductionmentioning

confidence: 99%

“…The problem in essence is a mixed-integer non-linear programming problem. Various optimization methods have been applied to address this issue, including linear programming [3], non-linear programming [4], quadratic programming [5], interior point programming [6,7], and artificial intelligence (AI) methods [2,8,9]. Reference [10] used second-order cones to relax the non-convex power flow equations, and then applied a sensitivity-based decomposition method to improve computational efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An Online Reactive Power-Optimization Strategy Based on Load-Curve Prediction and Segmentation

Wang

Deng

2020

Applied Sciences

View full text Add to dashboard Cite

Due to fluctuating characteristics of loads, dynamic reactive power optimization over a certain time period is essential to provide effective strategies to maintain the security and economic operation of distribution systems. In operation, reactive power compensation devices cannot be adjusted too frequently due to their lifetime constraints. Thus, in this paper, an online reactive power optimization strategy based on the segmentation of multiple predicted load curves is proposed to address this issue, aiming to minimize network losses and at the same time to minimize reactive power-compensation device adjustment times. Based on forecasted time series of loads, the strategy first segments each load curve into several sections by means of thresholding a filtered signal, and then optimizes reactive power dispatch based on average load in each section. Through case studies using a modified IEEE 34-bus system and field measurement of loads, the merits of the proposed strategy is verified in terms of both optimization performance and computational efficiency compared with state-of-the-art methods. optimization is of importance, which optimizes for a time period and makes the adjustment times of devices one of the optimization objectives.Dynamic reactive power optimization is a large-scale multi-period mix-integer non-linear programming problem. The classical methods such as non-linear programming [4] require differentiable objective function and are thus not applicable for dynamic optimization.A number of attempts have been made to conquer the problem of dynamic optimization. Reference [13] made daily reactive power optimization considering network losses, adjustment times of on-load tap changer (OLTC) and switchable capacitor banks, using an improved multi-population ant colony algorithm. Reference [14] used mixed integer non-linear programming to optimize transmission losses only, considering constraints of reactive power equipment operation limits and power grid security. Using a filter collaborative state transition algorithm (FCSTA), reference [15] built a two-objective dynamic reactive power optimization model, with one objective to minimize the actual power losses and voltage deviations, the other to minimize incremental system loss compared with the last time stamp. The objectives can be exchanged during dynamic optimization.Generally, state-of-the-art attempts include reducing scales of objectives or constraints, optimizing for increments at continuous time stamp, and using AI methods. However, much computational burden will be introduced when using AI methodology.Aiming to maintain objectives and constraints, as well as to reduce computational complexity, this paper proposes to segment load curves in a duty cycle into several stable time series first, and then conduct optimization for each segment. Based on online load predictions, the method can be applied in an online mode. Since the whole time series of loads need to be segmented into parts with lowest inner deviation, the methods of wind ramp extraction ...

show abstract

Section: Discussionmentioning

confidence: 99%

“…The second filtering method [17], noted as method 2, refers to a different calculation of the filtered curve, as shown in (2).…”

Section: Of 12mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Online Reactive Power-Optimization Strategy Based on Load-Curve Prediction and Segmentation

Wang

Deng

2020

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…(a) MGSO [62][63][64]. It is based on a finder-searcher model, possessing a high efficiency regarding high-dimension multimodal optimization issues, so it has a broad application prospect in Pareto multi-object dynamic optimization field.…”

Section: Distribution Sidementioning

confidence: 99%

Local Energy Management and Optimization: A Novel Energy Universal Service Bus System Based on Energy Internet Technologies

et al. 2018

View full text Add to dashboard Cite

This paper develops a novel energy universal service bus system (EUSBS) based on emerging energy Internet (E-net) technologies. This EUSBS is a unified identification and plug-and-play interface platform to which high penetration distributed energy and equipment (DEE), including photovoltaic (PV), fans, electric vehicle charging stations (EVCSs), energy storage equipment (ESE), and commercial and residential users (CRUs), can access in a coordinated control and optimized utilization mode. First, the functions design, overall framework and topology architecture design of the EUSBS are expounded, among which the EUSBS is mainly composed of a hardware system and a software platform. Moreover, several future application scenarios are presented. Then, the hardware part of EUSBS is designed and developed, including the framework design of this hardware subsystem, and development of the hardware equipment for PV access, fans access, EVCS access, ESE access, and CRU access. The hardware subsystem consists of smart socket, and household/floor/building concentrators. Based on this, the prototypes development of EUSBS hardware equipment is completely demonstrated. Third, the software part of the EUSBS is developed as a cloud service platform for electricity use data analysis of DEE. This software subsystem contains the power quality & energy efficiency analysis module, optimization control module, information and service module, and data monitoring and electricity behavior analysis module. Based on this design, the software interfaces are developed. Finally, an application study on energy management and optimization of a smart commercial building is conducted to evaluate the functions and practicality of this EUSBS. The EUSBS developed in this paper is able to overcome difficulties in big data collection and utilization on sides of distribution network and electricity utilization, and eventually implement a deep information-energy fusion and a friendly supply-demand interaction between the grid and users. This contribution presents a detailed and systematic development scheme of the EUSBS, and moreover, the laboratory prototypes of the hardware and software subsystems have been developed based on E-net technologies. This paper can provide some thoughts and suggestions for the research of active distribution network and comprehensive energy management and optimization in power systems, as well as references and guidance for researchers to carry out research regarding energy management, optimization and coordinated control of the smart buildings.

show abstract

Data Center Flexible Load Control for Renewable Energy Integration

Li,

Zeng

2024

Power Systems

View full text Add to dashboard Cite

Optimal reactive power dispatch with wind power integrated using group search optimizer with intraspecific competition and lévy walk

Cited by 24 publications

References 41 publications

An Online Reactive Power-Optimization Strategy Based on Load-Curve Prediction and Segmentation

An Online Reactive Power-Optimization Strategy Based on Load-Curve Prediction and Segmentation

Local Energy Management and Optimization: A Novel Energy Universal Service Bus System Based on Energy Internet Technologies

Data Center Flexible Load Control for Renewable Energy Integration

Contact Info

Product

Resources

About