m. doostizadeh

The scheduling of electricity distribution networks has changed dramatically by integrating renewable energy sources (RES) as well as energy storage systems (ESS). The sizing and placement of these resources have significant technical and economic impacts on the network. Whereas the utilization of these resources in the active distribution network (ADN) has several advantages, accordingly, the undesirable effects of these resources on ADN need to be analyzed and recovered. In this paper, a hybrid ADN, including wind, PV, and ESS, is investigated in 33 buses IEEE standard system. First of all, optimal energy management and sizing of the RES and ESS are the purposes. Secondly, as demand response (DR) is another substantial option in ADNs for regulating production and demand, an incentive-based DR program is applied for peak shaving. Forasmuch as this method has uncertainty, due to its dependence on customer consumption patterns, the use of inappropriate incentives will not be able to stimulate customers to reduce their consumption at peak times. Accordingly, the climatic condition uncertainty, which is another factor of variability on the production side, is minimized in this paper by relying on the Monte Carlo estimation method. Besides, the optimization problem, which is formulated as optimal programming, is solved to calculate the optimal size and place of each RESs and ESS conditions regarding power loss, voltage profile, and cost optimization. Furthermore, a geometric, energy source and network capacity, and cost constraints, are considered. The results confirm the effectiveness of proposed energy management and cost reduction in the studied test system.

In this paper, an online optimal coordinated solution for the voltage regulation of a distribution smart grids including an on-load tap changer (OLTC) and multiple distributed generators (DG) is presented. The proposed strategy sets reactive power points of distributed generators as well as tap position of the OLTC hierarchically. In the first stage, a distributed sub-gradient method in order to find the optimal reactive powers for the DGs is implemented to minimize the power losses subject to voltage limits. If the first stage could not regulate voltage profile inside acceptable limits, in the second stage tap position of the OLTC will change optimally. The proposed solution is verified by studying suddenly load change and DGs’ active power output. An IEEE 123-bus unbalanced test system is used for the verification of the proposed method. Fast response, responsibility to different suddenly changes in the operating condition, and reduction in the number of needed taps are the results of this study. Moreover, analogous steady state results in comparison with another centralized method i.e. interior point algorithm demonstrate the ability and efficiency of the proposed solution.