Abstract
This paper focuses on the long-term planning of power systems considering the impacts of Electrical Energy Storage Devices (ESSD) as well as Demand Response Programs (DRPs). The proposed model incorporates a two-stage optimization strategy in order to reduce the computational burden of the nonlinear problem. The upper-level of optimization model includes investment decision variables (long-term planning) while in the lower-level, the optimal operation of the model for short-term horizon has been addressed. In the operational stage, the optimal scheduling of power system in the presence of suggested ESSD size and location from the upper level is evaluated. Moreover, the Time-of-Use (ToU) Demand Response (DR) pricing scheme has been applied in the operational stage to evaluate its capability to reduce the total operating costs. The simulation results on the standard 6-bus test system validates the applicability of the proposed two-stage optimization model and illustrates that the optimal sizing and location of ESSDs along with DRP implementation could effectively reduce the total systems costs and improve the power system load factor.

Abstract
Recently, demand response programmes (DRPs) have captured great attention in electric power systems. DRPs such as time-of-use (ToU) programme can be efficiently employed in the power system planning to reform the long-term behaviour of the load demands. The composite generation expansion planning (GEP) and transmission expansion planning (TEP) known as composite GEP–TEP is of high significance in power systems to meet the future load demand of the system and also integrate renewable energy sources (RESs). In this regard, this study presents a dynamic optimisation framework for the composite GEP–TEP problem taking into consideration the ToU programme and also, the incentive-based and supportive programmes. Accordingly, the performances of the capacity payment and feed-in tariff mechanisms and the ToU programme in integrating RESs and reducing the total cost have been evaluated in this study. The problem has been formulated and solved as a standard two-stage mixed-integer linear programming model aimed at minimising the total costs. In this model, the ToU programme is applied and the results are fed into the expansion planning problem as the input. The proposed framework is simulated on the IEEE Reliability Test System to verify the effectiveness of the model and discuss the results obtained from implementing the mentioned mechanisms to support the RESs integration.

Abstract
This article proposes the optimal coordination problem of protective relays within a hybrid optimisation framework which is presented based on integer coded genetic algorithm (ICGA) and non-linear programming (NLP). The optimal coordination problem of directional overcurrent relays (DOCRs) is implemented while aimed at finding the optimal plug setting multiplier (PSM) and time dial setting (TDS). In this respect, PSM is a function of the current transformer (CT) size and the tap of the relay which is discrete in nature. TDS is a function of the operating time of the relay for different short-circuit currents at different locations of the system. Here, the variables of the problem are decomposed into continuous and discrete variables. The first stage of the problem uses the ICGA to determine the size of CTs considering the permitted tap of relays while the second stage utilises the NLP method to evaluate the feasibility and optimality. The presented framework is then simulated on an 8-bus test system. The obtained results verify the effectiveness and the applicability of the optimisation technique to find the optimal settings of DOCRs.

Abstract
A multi-objective wind farm integration framework is proposed in this paper which considers the composite generation and reliability assessment and annualized operating and investment cost evaluation. An emission-controlled policy is adopted such that the amount of SOx and NOx decreases in line with renewable resource planning. Since the incorporation of large-scale distant wind farms is a problem of the multi-objective mixed-integer type with nonlinearities and non-convexities, this paper utilizes a fast elicit multi-objective Non-dominated Sorting Genetic Algorithm II (NSGA II) by probabilistic indices. It is noted that the impacts of the unavailability of the transmission system are modeled employing DC Optimal Power Flow (OPF) based on the incidence matrix together with the static security evaluation. Furthermore, in order to assess the performance of the suggested approach, the model is implemented on the Roy Billinton Test System (RBTS). Afterwards, distant wind farms integration into Iran's South-West Regional Grid (ISWRG) is studied. © 2019

Abstract
This paper presents an optimization framework to determine the optimal operating points of combined heat and power (CHP) units with nonlinear, nonconvex feasible operating region (FOR). The mentioned problem is the economic dispatch (ED) of heat-only units, thermal units, and CHP units. Also, the electric units are of thermal technology while their valve-point impact is taken into consideration. Also, the heat power curve of heat-only units is nonlinear. It is noted that the FOR of CHP units has been defined both as convex and nonconvex regions. For those with nonconvex characteristic, a method is proposed to convert it into a convex characteristic. Accordingly, a separate binary variable must be defined to determine the optimal operating point in each convex region. Thus, the presented problem in this paper is of mixed-integer nonlinear programming (MINLP) type modeled in General Algebraic Modeling System (GAMS) software. In this respect, different case studies have been presented to assess the optimality, feasibility, and the flexibility of the model. It is noteworthy that the valve-point effect of thermal units and different FORs of CHP units as well as the electrical power losses have been considered. © 2018 John Wiley & Sons, Ltd.

Abstract
The paper presents a multi-year, multi-objective framework for integrating Renewable Energy Sources (RESs) into the high voltage transmission network of Iran's National Power Grid (INPG). The objective functions in this study are the total cost, including the investment cost and operating cost for the planning horizon, and the system reliability. The first objective function is stated from the economic point of view, while the second objective function is considered as a security index in the expansion planning issue. The main purpose of this paper is to increase the RES penetration into the generation mix of INPG. Since the mentioned 230 to 400-kV INPG is a large-scale power system, the problem formulation is investigated in a mixed-integer programming, and then, the developed multi-objective problem has been solved using the augmented epsilon-constraint optimization method. In order to select the executive plan for installation, the fuzzy satisfying decision-making procedure is adopted in this study. © 2018 John Wiley & Sons, Ltd.