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The expansion of distributed generations (DG) in the distribution networks brings visible technical and economic benefits to the grid. On the other hand, the place and size for DGs in a grid are very important, and optimal selection can decrease voltage profile volatility, system losses, and increase reliability indices especially. The issue of reliability in the distribution system is one of the important parameters in selecting the optimal location of DG. In other words, by considering this parameter, DG location will change in the distribution system and by installing it at this point; the reliability of the network has improved. Therefore, this paper proposes an analytical index to determine the optimal size and siting of DGs in a distribution network. The proposed index has consisted of loss sensitivity factor, voltage stability index, and reliability based factors. To evaluate the efficiency of the proposed method in the previous section, the simulation procedure has been implemented on the IEEE 33 and 69 bus distribution systems. The effectiveness of the suggested index is clarified by using different test systems, and the results have been compared with other proposed methods. The results indicated that the proposed simple index could be acceptable in finding the optimal location and size of DG better than complicated optimization methods. K E Y W O R D S DG placement system, distributed generation, distributed networks, placement and sizing, reliability index 1 INTRODUCTION Nowadays, distributed generations (DG) play an essential role in electricity networks as one of the sources of energy that connected to the distribution system directly or on the customer side. 1,2 These resources are reducing network losses, improving voltage profile, power factor and network stability, reducing operating and maintenance costs, enhancing system reliability, and favorable economic and environmental effects. 3-5 However, inappropriate selection of size and location of DG makes network conditions such as network losses, voltage profiles, stability, etc. worse than without DG. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

In order to reduce energy loss and improve voltage stability index in a distribution system, two di erent approaches, voltage and reactive power control (volt/var control) and distribution network recon guration, were proposed and employed. In the present paper, volt/var control and network recon guration in a distribution system considering voltage security constraints were modeled as a multi-objective optimization problem. Total electrical energy loss, voltage deviation, and voltage stability were considered as objectives. In addition, a new method for the distribution network recon guration was utilized to implement these two problems simultaneously. In this way, the two problems could be solved in a less amount of time. In addition, loads of di erent nature in each bus were considered in network load modeling. Non-dominated sorting genetic algorithm-II was used to solve this problem. Finally, the e ectiveness of the proposed method was evaluated by its implementation on the IEEE 33-bus system and a real 77-bus distribution system.

Nowadays, renewable energies are important sources for supplying electric power demand and a key entity of future energy markets. Therefore, wind power producers (WPPs) in most of the power systems in the world have a key role. On the other hand, the wind speed uncertainty makes WPPs deferent power generators, which in turn causes adequate bidding strategies, that leads to market rules, and the functional abilities of the turbines to penetrate the market. In this paper, a new bidding strategy has been proposed based on optimal scenario making for WPPs in a competitive power market. As known, the WPP generation is uncertain, and different scenarios must be created for wind power production. Therefore, a prediction intervals method has been improved in making scenarios and increase the accuracy of the presence of WPPs in the balancing market. Besides, a new optimization algorithm has been proposed called the grasshopper optimization algorithm to simulate the optimal bidding problem of WPPs. A set of numerical examples, as well as a case-study based on real-world data, allows illustrating and discussing the properties of the proposed method.