Abstract
An increasing implementation of renewable sources and electric vehicles can be of help in reducing the total operational cost of a power system, affecting power system technical operation. To this end, a multi-objective optimisation method using Normalised Normal Constraint (NNC) is applied in this paper by which two competitive objectives are considered: Minimisation of Active Distribution System (ADS) operational cost and minimisation of ADS power losses. Meanwhile, the uncertain behaviour of wind, photovoltaic units, and arrival and departure time of electric vehicles are considered. The proposed model is a multi-objective problem which comprises two stochastic stages and is simulated under GAMS environment on a modified IEEE 18-bus test system. The results clearly represent the trade-off between economic and technical benefits of the considered ADS. Furthermore, the effect of electric vehicles charging and discharging tariffs on the operational cost of the system are shown.

Abstract
This paper demonstrates day-ahead operation of power systems in the presence of a Demand Response Program (DRP) for serving exact amounts of demanded energy over the operational horizon. The proposed two-stage model features a here-and-now framework for shaping the aggregated demands during operation. First, the day-ahead scheduling problem is solved by adopting Unit Commitment (UC) to determine the generation level of power generation units as well as the Locational Marginal Prices (LMPs). Afterwards, the obtained LMPs are considered as the Time of Use (ToU) for the second step of the scheduling and reshaping the demanded loads of each aggregator. A new methodology is provided in this paper to estimate the reaction of consumers behavior in terms of encouraging their participation in DRPs. Unlike classical models which adopt load reduction over the operational horizon, this model ensures that the total demanded loads will be served. Therefore, the total supplied energy for the operational period before and after DRP implementation remains unchanged. Meanwhile, the total payment of consumers will be considerably reduced by adopting this strategy. The simulation results on the 6-bus test system clarify that the proposed model can reduce the total operational cost as well as smoothen the load profile and nodal prices over the operational horizon.

Abstract
Distribution networks are more active due to demand response programs which causes flexible behavior of end-users. This paper proposes an iterative algorithm to transact electricity based on interplay between aggregators and the Distribution Company (DisCo) considering the amount which the bottom-layer of a distribution system can provide from the aggregated end-users. The performance of the proposed trading algorithm was tested on a 33-bus test system for a distribution network. Similations for different scenarios were made to analyze the impact of different flexibility constraints on sustainability of the system and expected cost on distribution grid's player.

Abstract
Integration of renewable generation in distribution systems aims to reduce consumption of energy from conventional sources such as coal and oil in order to minimize the negative impacts of the human ecological footprint. Massive incorporation of renewables can produce reverse power flow at distribution substations, which is against the operating philosophy and design of energy systems. To deal with this problem, the installation of a battery energy storage system (BESS) is proposed in this work. Incorporation of BESS at distribution substations can manage the excess of renewable power generation flowing in reverse, adding flexibility to the power system and allowing increased distributed generation capacity to be installed. Optimal sizing of vanadium redox flow batteries (VRFBs) is carried out by using golden section search algorithm considering capital costs as well as operating and maintenance costs over the project lifetime. The effectiveness of the proposed technique is evaluated through the analysis of a case study. A significant reduction of both reverse flow and the power to be supplied by the substation has been observed.

Abstract
This paper proposes a novel method for solving the Optimal Power Flow (OPF) problem in conditions close to realtime. The linearized cost function of the generating units is used to this end. Besides, the presented linear model is solved using the Consensus Alternating Direction Method of Multipliers (C-ADMM) approach. This technique would provide the possibility of modeling the problem both in centralized and decentralized manners. The suggested method exploits the power flow results obtained from the previous iteration to considerably improve the rate of convergence. As the C-ADMM method uses an iterative technique, Lagrange multipliers, and the norm function, the rate of convergence highly depends upon assigning the initial conditions and the optimality gap. Thus, using the operating points of the previous instant due to being close to the operating point of the current instant would enhance the results. The proposed model has been implemented on two case studies including the Pennsylvania-New Jersey-Maryland (PJM) network to verify the results and the 9-bus system to evaluate the performance of the model for the daily operation. © 2019 IEEE.

Abstract
In power system static security analysis, it often requires to calculate continuous power flow from a certain load condition to a bifurcation point along a given direction, which is referred to as the maximum loadability problem. This paper proposes a convex optimization method for maximum loadability problem over meshed power grids based on the semidefinite relaxation approach. Because the objective is to maximize the load increasing distance, convex relaxation model is generally inexact, unlike the situation in cost-minimum optimal power flow problem. Inspired by the rank penalty method, this paper proposes an iterative procedure to retrieve the maximum loadability. The convex quadratic term representing the penalty on the rank of matrix variable is updated in each iteration based on the latest solution. In order to expedite convergence, generator reactive power is also included in the objective function, which has been reported in literature. Numeric tests on some small-scale systems validate its effectiveness. Any sparsity-exploration and acceleration techniques for semidefinite programming can improve the efficiency of the proposed approach. © 2019 IEEE.