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This paper presents an economical approach for reliability improvement, harmonic mitigation, and loss reduction in microgrids and active distribution networks, including distributed generations (DGs). By controlling the direction of power flow in the network in proportion to the purposeful change in the generation of the DGs, the three mentioned objective can be improved. Purposeful reduction of line currents and releasing part of the capacity of lines and feeders following flow control reduces loss and improves overall network reliability. Further, the targeted use of storage and power electronic converters in renewable DGs can reduce the harmonic distortions of the network. The proposed method is a stochastic approach based on the locational marginal price (LMP) calculation in DG bus as game-theoretic problem, according to the contributions of DGs on aforementioned objectives. In this method, each player acquires a financial incentive as incremental price, based on a game-theoretic sharing strategy. In other words, each DG that aligns its generation with the aforementioned objectives will increase the price of selling energy. This increase in prices will lead to higher profits. The incentives allocation procedure to each DGs is performed based on a cooperative coalition game-theoretic strategy to guarantee the fairness of the proposed method. As a tool for managing system, the proposed method can control the impact of the pricing in the form of incentives to satisfy each objective depending on its decision in the incentive allocation procedure. To obtain a more realistic framework, demands and generations of renewable DGs are considered as the uncertainty parameters. To validate the proposed method, it is evaluated on the real Taiwan Power Company (TPC) network and, the promising results indicate that the total loss decreased 54.4%, harmonic mitigated 12.3% and the reliability is improved by 12.6% without any budget extension, add/remove equipment or network reconfiguration.

Wind and solar (photovoltaic) power generations have rapidly evolved over the recent decades. Efficient and reliable planning of power system with significant penetration of these resources brings challenges due to their fluctuating and uncertain characteristics. In this paper, incorporation of both PV and wind units in the unit commitment of power system is investigated and a risk-constrained solution to this problem is presented. Considering the contribution of PV and wind units, the aim is to determine the start-up/shut-down status as well as the amount of generating power for all thermal units at minimum operating cost during the scheduling horizon, subject to the system and unit operational constraints. Using the probabilistic method of confidence interval, the uncertainties associated with wind and PV generation are modeled by analyzing the error in the forecasted wind speed and solar irradiation data. Differential evolution algorithm is proposed to solve the two-stage mixed-integer nonlinear optimization problem. Numerical results indicate that with indeterminate information about the wind and PV generation, a reliable day-ahead scheduling of other units is achieved by considering the estimated dependable generation of PV and wind units.