Abstract
In this paper, a new methodology for the optimal investment in distributed generation is presented, based on an optimal allocation of combined DG and capacitor units to alleviate network voltage constraints and reduce the interconnection cost of renewable generation integration in public medium voltage distribution networks. An analytical optimization method is developed, with the inclusion of practical considerations that are typically neglected in developed works: network topology reconfiguration and the geographical data of the generation land-use and network infrastructure. Powerful results concluded from a sensitivity analysis study of the most impacted parts of the network by the variation of active and reactive power injection under network topology reconfiguration are used as a basis for capacitor units placement. A case study, with two meshed IEEE 15-bus feeders and a new DG to connect, geographical dispersed, are used to simulate the performance of the proposed approach. A cost evaluation of the obtained results proves the effectiveness of the proposed approach to reduce the required charges for connecting new renewable generation units in medium voltage distribution system.
Highlights
Several optimization efforts had been presented in literature with a main aim of maximizing the benefits expected from connecting DGs to electrical networks, by optimizing their location with a defined specific capacity [1], optimizing their size with a defined location [2], optimization of combined location and size [3], and the identification of the optimal type of DGs to connect [4]
To improve a particular objective or a combination of objectives, the principal searched benefits in literature are minimization of power losses [5], enhancement in voltage profile [6], voltage stability improvement [7], cost minimization [8], maximization of profit [9], reliability enhancement [10], social welfare maximization [11], system average interruption duration index SAIDI improvement [12], and the maximization of the distributed generation capacity [13]. To solve their optimization problem, authors had developed several methods and approaches, which can be classified in four principal categories: analysis approaches [14], mathematical programming algorithms, heuristic methods
Several investment models were presented in literature, investment costs, substation expansion investment cost, operation and maintenance costs, energy losses cost, and the cost of the power purchased from the transmission system
Summary
Several optimization efforts had been presented in literature with a main aim of maximizing the benefits expected from connecting DGs to electrical networks, by optimizing their location with a defined specific capacity [1], optimizing their size with a defined location [2], optimization of combined location and size [3], and the identification of the optimal type of DGs to connect [4]. (i) Introduction of a novel objective to the research field area of optimal allocation of distributed generation (ii) Inclusion of practical considerations that are typically neglected in already developed works (iii) Incorporating constraints related to geographical generation land use (iv) Report results that have the potential to incite researches to develop efficient efforts and encourage private investors to build renewable distributed generation by minimizing the costs of interconnecting their generation units in public networks (v) e presentation of a powerful tool that could be used directly by distribution electric utilities for the orientation study, as tool able to offer more options to connect a new DG to their electrical networks
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