Application of dynamic programming for distributed generation allocation

Khalesi, Navid; Haghifam, M-R.

doi:10.1109/epec.2009.5420876

Cited by 4 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To solve this problem, Artificial Intelligence-based algorithms have been widely used in DG planning. In [13] the authors established a multi-objective optimization model of power loss, cost, and voltage deviation, and used the multi-objective shuffled bat algorithm (MOShBAT) to determine the location and capacity of DG. In [14] studies the energy storage placement problem for voltage stability by using the GA algorithm.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Probabilistic Approach Based on Area Grey Incidence Decision Making for Optimal Distributed Generation Planning

Huang

Cai

et al. 2019

IEEE Access

View full text Add to dashboard Cite

The increase in the scale of distribution networks significantly reduces the efficiency of intelligent planning for distributed generation (DG). To improve the efficiency of intelligent DG planning and avoid the impact of uncertainty concerning renewable energy on it, this paper proposes a sensitivity index for the bus-embedded multi-objective estimation of distribution algorithm (MEDA) based on the semiinvariant probabilistic power flow approach to achieve an optimal solution. The sensitivity indices of the buses are comprehensively enabled to obtain a new index and determine their sensitivity sequences based on the area grey incidence decision-making method. Subsequently, according to the uncertainty of wind turbine generators and photovoltaics, a probability model is established, and the semi-invariant method is used to solve for the probabilistic power flow according to a correlation model. Finally, the sensitivity of the proposed bus-embedded MEDA to enhancing the efficiency of the solution is examined. The optimal DG allocation scheme is obtained with the goal of achieving the lowest total cost in the planning year. Finally, the feasibility and effectiveness of the proposed model and method are verified using simulations of the IEEE 33-bus, IEEE 69-bus, and IEEE 118-bus test systems. INDEX TERMS Distributed generation, sensitivity index, multi-objective estimation of distribution algorithm, area grey incidence decision making, probabilistic power flow.

show abstract

Section: Introductionmentioning

confidence: 99%

An Efficient Probabilistic Approach Based on Area Grey Incidence Decision Making for Optimal Distributed Generation Planning

Huang

Cai

et al. 2019

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In [45] operation of a micro-grid featuring both DG, heat supply and storage is optimised through DP. In [46] DP is applied to the multi-objective problem of optimally allocating DG to an existing network.…”

Section: Introductionmentioning

confidence: 99%

Constrained coordinated distributed control of smart grid with asynchronous information exchange

Millar

Jiang

Haque

2015

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

Smart grid constrained optimal control is a complex issue due to the constant growth of grid complexity and the large volume of data available as input to smart device control. In this context, traditional centralized control paradigms may suffer in terms of the timeliness of optimization results due to the volume of data to be processed and the delayed asynchronous nature of the data transmission. To address these limits of centralized control, this paper presents a coordinated, distributed algorithm based on distributed, local controllers and a central coordinator for exchanging summarized global state information. The proposed model for exchanging global state information is resistant to fluctuations caused by the inherent interdependence between local controllers, and is robust to delays in information exchange. In addition, the algorithm features iterative refinement of local state estimations that is able to improve local controller ability to operate within network constraints. Application of the proposed coordinated, distributed algorithm through simulation shows its effectiveness in optimizing a global goal within a complex distribution system operating under constraints, while ensuring network operation stability under varying levels of information exchange delay, and with a range of network sizes.

show abstract

Objectives and Constraints for Optimal Allocation of Distributed Energy Sources—A Review

Shankar¹,

Kathirvel²

2023

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

Application of dynamic programming for distributed generation allocation

Cited by 4 publications

References 17 publications

An Efficient Probabilistic Approach Based on Area Grey Incidence Decision Making for Optimal Distributed Generation Planning

An Efficient Probabilistic Approach Based on Area Grey Incidence Decision Making for Optimal Distributed Generation Planning

Constrained coordinated distributed control of smart grid with asynchronous information exchange

Objectives and Constraints for Optimal Allocation of Distributed Energy Sources—A Review

Contact Info

Product

Resources

About