Abstract
Security Constraint Generation Scheduling (SCGS) is one of the most important issues in modern power system shortterm operation. In the SCGS the optimal and secure operation of power system has been taken into account. SCGS includes the timing and production of available energy resources in order to maintaining customer demands. In this paper, we present a new approach for SCGS in Day-Ahead market considering both heat and power demands entire the system. Harmony Search Algorithm, (HSA) which is a recent meta-heuristic optimization algorithms is addressed in this paper to solve the SCGS problem which is a large-scale, non-convex, nonlinear with both continuous and discrete variables. It is shown that HSA, as a meta-heuristic optimization algorithm, may solve power system scheduling problem (Heat and Power) in a better fashion in comparison with the other evolutionary search algorithm that are implemented in such complicated issue. HSA was conceptualized using the musical process of searching for a perfect state of harmony. Compared to the earlier meta-heuristic optimization algorithms, HSA imposes fewer mathematical requirements that can be easily adopted for various types of engineering optimization problems, such as Combined Heat and Power SCGS (CHP-SCGS). An adopted case study is conducted to facilitate the effectiveness of the proposed method. This case study is recently presented in order to analysis the Day-Ahead power system studies with a 24-h scheduling horizon, which considers the Hydro-Thermal and conventional Unit Commitment (UC) problem. Simulation results show the effectiveness and fastness of the proposed method. © Indian Society for Education and Environment (iSee).

Abstract
This paper presents a new approach for considering all possible contingencies in short-term power system operation. Based on this new approach, both generator and transmission line outages would be modelled in network-based power system analysis. Multi generator and also parallel transmission lines is modelled in this methodology. We also investigate this claim that feasibility and applicability of this approach is much more than the previous analytical methodologies. Security Constrained Unit commitment (SCUC) program which is carried out by Independent System Operator (ISO), is one of the complex problems which would be handled by this approach. In this paper, a DC-Optimal Power Flow (DCOPF) methodology has been considered for hourly Locational Marginal Price (LMP) calculations. This approach can be applied in market simulation and planning owing to its robustness and speed. Unlike, previous admittance based matrix methodologies, which solidly depended on the network topology, independency of network in the presented approach; it would be an effective tool for considering possible contingencies in the grid. The simulation results show that the presented method is both satisfactory and consistent with expectation. © Indian Society for Education and Environment (iSee).

Abstract
An incidence matrix approach for mitigating congestion in transmission network is presented in this paper. Based on this methodology, all congested power transmission lines is identified and main economical signals for investment planning is introduced. In this method, we can determine strong and weak transmission corridors in the network. The Flexible AC Transmission System (FACTS) device has been applied to enhance the controllability of power systems. New generations of FACTS device called Distributed FACTS such as distributed series impedance or distributed static series compensator have recently received increasing interests for power system control and are expected to be broadly deployed. This paper presents a detailed formulation and algorithm to find the best location and size of DFACTS to achieve the optimal utilization of transmission capacity to mitigate congestion. This approach can be applied in market simulation and planning owing to its robustness and speed. Unlike, previous admittance based matrix methodologies, which solidly depended on the network topology, independency of network in the presented approach; it would be an effective tool for long-term expansion planning criteria or implementing D-FACTS devices in modern power systems. The simulation results show that the presented method is both satisfactory and consistent with expectation. Simulation results are presented with the PJM 5-bus system to illustrate the capabilities of presented approach in compression with previous works. © Indian Society for Education and Environment (iSee).

Abstract
This paper, presents on the coordination of power system expansion planning including sustainable generation expansion planning (GEP) and transmission network expansion planning (TEP). For this purpose, a game theory based model is proposed to determine the dominant strategy of each investor entities in the generation and transmission sectors. In this model, all power producers compete with each other at the same level for maintaining the energy and reserve services. At this stage, after determining the Cournot equilibrium, the suggestions accepted in previous stage are evaluated in the transmission planning stage. Here, according to the existing units and the units proposed in the previous stage, transmission network expansion planning takes place based on cost, social welfare and reliability indices by independent system operator. Thereafter transmission expansion planning results announced, the accepted unit and not accepted units can offer their new strategies to the market. This iterative process continues until the dominant strategy of each entity is satisfied and the final equilibrium is obtained. To solve this game and finding its Nash equilibrium, the mixed integer non-linear programming (MINLP) optimization is used by all decision makers for optimizing their desirable strategies to invest in the power market. A conceptual test system is proposed to show the ability of the model. Simulation results verify the feasibility and capability of the proposed modeling of the long-term expansion planning. © Indian Society for Education and Environment (iSee).

Abstract

Abstract
This article provides a framework for coordinating the operation of multiple microgrids with hydrogen systems in a distribution network considering the uncertainties of wind and solar power generation as well as load demands. The model is based upon a bilevel stochastic programming problem. On the upper level, the distribution system is the leader with a profit-maximization goal, and the microgrids are followers with cost-minimization goals on the lower level. The problem is solved by transforming the model to a single-level model using Karush-Kuhn-Tucker (KKT) conditions and linearized using McCormick's relaxation and Fortuny-Amat techniques. Unlike previous studies, both levels are modeled as scenario-based stochastic problems. Moreover, the scenarios associated with uncertain variables are obtained from a real data set. After preparing the data set, scenarios are reduced using a machine learning-based clustering approach. An application of the coordinated operation model is developed for a distribution network containing several microgrids. By solving the problem, the optimal amount of power exchange and the clearing price between microgrids and distribution systems are determined. Moreover, the proposed bilevel model made 13% more profit for the distribution system than the centralized model. Also, the effects of integrating hydrogen systems with microgrids on increasing the flexibility of operators are investigated.