A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system

Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques

To extract the maximum potential advantages in light of environmental, economical and technical aspects, the optimum installation and sizing of Distributed Generation (DG) in distribution network has always been challenging for utilities as well as customers. The installation of DG would be of maximum benefit where setting up of central power generating units are not practical, or in remote and small areas where the installation of transmission lines or availability of unused land is out of question. The objective of optimal installation of DG in distribution system is to achieve proper operation of distribution networks with minimization of the system losses, improvement of the voltage profile, enhanced system reliability, stability and loadability etc. In this respect analytical (classical) methods, although well-matched for small systems, perform adversely for large and complex objective functions. Unlike the analytical (classical) methods, the intelligent techniques for optimal sizing and siting of DGs are speedy, possess good convergence characteristics, and are well suited for large and complex systems. However, to find a global optimal solution of complex multi-objective problems, a hybrid of two or more meta-heuristic optimization techniques give more effective and reliable solution. This paper presents the fundamentals of DG and DG technologies review the classical and heuristic approaches for optimal sizing and placement of DG units in distribution networks and study their impacts on utilities and customers. An attempt has also been made to compare the analytical (classical) and meta-heuristic techniques for optimal sizing and siting of DG in distribution networks. The present study can contribute meaningful knowledge and assist as a reference for investigators and utility engineers on issues to be considered for optimal sizing and siting of DG units in distribution systems.

Optimal sizing and siting techniques for distributed generation in distribution systems: A review

Optimal distributed generation planning in active distribution networks considering integration of energy storage

Optimization and integration of hybrid renewable energy hydrogen fuel cell energy systems – A critical review

An improved nondominated sorting genetic algorithm–II (INSGA-II) has been proposed for optimal planning of multiple distributed generation (DG) units in this paper. First, multiobjective functions that take minimum line loss, minimum voltage deviation, and maximal voltage stability margin into consideration have been formed. Then, using the proposed INSGA-II algorithm to solve the multiobjective planning problem has been described in detail. The improved sorting strategy and the novel truncation strategy based on hierarchical agglomerative clustering are utilized to keep the diversity of population. In order to strengthen the global optimal searching capability, the mutation and recombination strategies in differential evolution are introduced to replace the original one. In addition, a tradeoff method based on fuzzy set theory is used to obtain the best compromise solution from the Pareto-optimal set. Finally, several experiments have been made on the IEEE 33-bus test case and multiple actual test cases with the consideration of multiple DG units. The feasibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been proved.

Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II

In this study, a new pinning-based distributed cooperative control scheme is proposed for multi-agent system (MAS)-based autonomous microgrids. By pinning parts of selected agents, only a small fraction of the pinned agents are controlled by simple feedback controllers, while the other DGAs in the MAS synchronize through the communication coupling among the pinned agents in a distributed manner. The main contributions of this study are as follows: 1) the proposal of a fully distributed control for autonomous microgrids where each agent shares its operation information only with its neighbors, which obviates the requirement for a central controller and complex communication topology; 2) the proposal of a pinning-based control scheme, which reduces the number of controllers, for a predefined consensus can be reached if a small fraction of the pinned agents is controlled; and 3) the proposal of the pinning consensus under uncertain communication topologies that can meet the requirements of line switches and plug-and-play operation. Simulation results are demonstrated to verify the effectiveness and adaptability of the proposed scheme.

Pinning-Based Distributed Cooperative Control for Autonomous Microgrids Under Uncertain Communication Topologies

Optimal sitting and sizing of DGs in distribution system considering time sequence characteristics of loads and DGs

The invention provides a uniform data acquisition and monitoring system of a low-medium voltage power distribution network, which comprises an intelligent acquisition terminal, a data communication and transmission system, a real-time data processing module, a data interface service module, a user power consumption information management and monitoring module and an intelligent power distribution station area management and monitoring module, wherein the intelligent acquisition terminal acquires user power consumption information and information on power distribution station area operation, state and the like, transmits the information to a real-time/historical database in the real-time data processing module through the data communication and transmission network for uniform management, uses the real-time/historical data to provide real-time comprehensive data support for the user power consumption information management and monitoring module, the intelligent power distribution station area management and monitoring module and other related application system through the data interface service module according to needs, and by the real-time acquisition and analysis of the operation information and the state parameters of power users and the power distribution station areas, brings the intelligent power distribution station areas into the self-control and economic operation range of the low-medium voltage power distribution network to realize the real-time load analysis and real-time electrovalence management of the terminal users and interactive application functions such demander response.

Uniform data acquisition and monitoring system of low-medium voltage power distribution network

The energy crisis and increasing concerns about the environment in modern society have fostered the development of the integrated energy system (IES) in smart grid. The energy hub (EH) is a minimum construction of the IES. The chief purpose of this paper is to propose a Lyapunov optimization-based energy management strategy for the energy hub with an energy router. First, this paper describes a configuration of the EH with an energy router and sets the basic operating principles of the energy router. Second, a method is proposed to analyze the energy balance equations of the EH. Furthermore, the problem of energy management is formulated considering the constraints of energy balance equations, energy storage, flexible loads, and other constraints of operation. Finally, energy storage and flexible electric loads are modeled as stochastic processes, and three virtual queues are constructed to relax these constraints. The Lyapunov drift-plus-penalty function is applied to formulate a relaxed form of the energy management problem. Case studies of a single EH and two-connected EHs are performed to test the effectiveness of the proposed strategy, and the results are compared with a greedy algorithm.

Wanxing Sheng

Papers

Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II

Pinning-Based Distributed Cooperative Control for Autonomous Microgrids Under Uncertain Communication Topologies

Optimal sitting and sizing of DGs in distribution system considering time sequence characteristics of loads and DGs

Uniform data acquisition and monitoring system of low-medium voltage power distribution network

A Lyapunov Optimization-Based Energy Management Strategy for Energy Hub With Energy Router