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This paper is the second part of a two-paper set which comprehensively sets forth an innovative approach in transmission grid reinforcement studies in the presence of wind energy. Part I thoroughly defined the theory and algorithms. Here, to trace the feasibility of the proposed algorithm, three different case studies are implemented on the 24-Bus IEEE Reliability Test System (IEEE-RTS). The optimal solutions in Pareto fronts of different cases are reached, analyzed, and the final solution (optimal plan) of each case is obtained using the fuzzy decision making method. Moreover, in order to analyze the effects of variations in the large-scale wind farm generation on the transmission expansion... 

Deregulation in power systems creates new uncertainties and escalates the previous ones. The presence of these uncertainties causes the transmission network to remain a monopoly and the private investors not to be interested in investing in new transmission lines. This article presents a new merchant-based transmission network expansion planning algorithm from the viewpoint of private investors. The point estimation method is used to handle the uncertainties, and the genetic algorithm is used as the optimization tool. The proposed method provides insights for private investors to deal with the uncertainties and to find appropriate transmission projects in which to invest. Copyright  

As a matter of course, the unprecedented ascending penetration of distributed energy resources (DERs), mainly harvesting renewable energies (REs), is concomitant with environmentally friendly concerns. This type of energy resources are innately uncertain and bring about more uncertainties in the power system, consequently, necessitates probabilistic analyses of the system performance. Moreover, the uncertain parameters may have a considerable level of correlation to each other, in addition to their uncertainties. The two point estimation method (2PEM) is recognized as an appropriate probabilistic method in small scale or even medium scale problems. This paper develops a new methodology for... 

With increment in the penetration of wind energy in power systems, the necessity of considering its impacts on transmission expansion planning (TEP) studies, especially for large scale wind farms, is inevitable. A new multi-objective (MO) optimization transmission expansion planning algorithm considering wind farm generation is presented in this two-paper set. Part I is mainly devoted to derivation of the theory and algorithm. The objective functions used in the TEP studies take into account investment cost, risk cost and congestion cost. The combination of Monte Carlo simulation (MCS) and Point Estimation Method (PEM) is implemented to investigate the effects of network uncertainties. Due... 

As a matter of course, the unprecedented ascending penetration of distributed energy resources, mainly harvesting renewable energies such as wind and solar, is concomitant with environmentally friendly concerns. This type of energy resources are innately uncertain and bring about more uncertainties in the power system context, consequently, necessitates probabilistic analysis of the system performance. Moreover, the uncertain parameters may have a considerable level of correlation to each other, in addition to their uncertainties. The two point estimation method (2PEM) is recognised as an appropriate probabilistic method. This study proposes a new methodology for probabilistic power flow... 

PV generation variability and uncertainty significantly influence operation of the power systems with high penetration of PV sources. The potential impact of distributed PV generation on ramp rate requirements in the IEEE 24-bus system is evaluated in this paper. PV generation and load are, here, probabilistically modeled using actual data and curve fitting approach. Probabilistic unit commitment (UC) based on unit de-commitment method combined with two point estimate method (2-PEM) is used to determine the ramp rate required to compensate for the PV power fluctuations. The proposed method considers stochastic factors and their effects on the dispatch results. Two scenarios are studied to... 

This paper is the second part of a two-paper set which comprehensively sets forth an innovative approach in transmission grid reinforcement studies in the presence of wind energy. Part I thoroughly defined the theory and algorithms. Here, to trace the feasibility of the proposed algorithm, three different case studies are implemented on the 24-Bus IEEE Reliability Test System (IEEE-RTS). The optimal solutions in Pareto fronts of different cases are reached, analyzed, and the final solution (optimal plan) of each case is obtained using the fuzzy decision making method. Moreover, in order to analyze the effects of variations in the large-scale wind farm generation on the transmission expansion... 

In market-based planning studies, the financial aspects of transmission grids have been posed as a major challenge since these are important keys to provide a non-discriminative and competitive environment for energy market participants. In this respect, this paper proposes a probabilistic multi-objective transmission expansion planning algorithm considering private investors' preferences, technical concerns, and random nature of power system uncertainties. The combination of Non-Dominated Sorting Genetic Algorithm II, as a widely-used robust multi-objective optimization technique, and point estimation method is employed to handle non-commensurable probabilistic objective functions. The IEEE... 

In recent years, a great deal of attention has been paid to multi-energy systems that improve energy efficiency and reliability. In this respect, this paper examines the issue of energy flow of these systems in a probabilistic context in the presence of energy responsive programs. Responsive energy programs are provided by system operator of multi-carrier energy to manage these networks where energy customers can participate in it. The probabilistic method used is 2m + 1 point estimation method, which has high speed and high accuracy. The presented numerical results show the impact of each responsive energy program on the cost of operating a multi-carrier system. © 2019 IEEE  

This paper proposes a new framework for home energy management (HEM) in the context of renewable-based residential energy hub using a probabilistic optimization approach. Different energy converters and storages, including combined heat and power, a plug-in hybrid electric vehicle, a heat storage unit, solar panels, and generic household appliances, are considered in the energy hub. The customer's energy cost is considered as the objective of the HEM optimization problem and different operational limits of the energy hub components are modeled as the constraints. The two-point estimate method is incorporated in this paper to model the uncertainty associated with output power of the rooftop... 

Along with the increasing demand for electrical power, distributed generations (DGs) have so far found their pivotal roles in the restructured environment of power distribution systems. As an indispensable step toward a more reliable power system, the DGs optimal allocation strategy, deemed to be the most techno-economically efficient scheme, comes to the play and is profoundly taken under concentration in this study. This paper devises a comprehensive multi-objective (MO) optimization approach by which all the crucial and maybe contradictory aspects of great influence in the placement process can be accounted for. Total imposed costs, total network losses, customer outage costs as well as... 

With increment in the penetration of wind energy in power systems, the necessity of considering its impacts on transmission expansion planning (TEP) studies, especially for large scale wind farms, is inevitable. A new multi-objective (MO) optimization transmission expansion planning algorithm considering wind farm generation is presented in this two-paper set. Part I is mainly devoted to derivation of the theory and algorithm. The objective functions used in the TEP studies take into account investment cost, risk cost and congestion cost. The combination of Monte Carlo simulation (MCS) and Point Estimation Method (PEM) is implemented to investigate the effects of network uncertainties. Due... 

The rapid growth in use of renewable intermittent energy resources, like wind turbines (WTs) and solar panels, in distribution networks has increased the need for having an accurate and efficient method of handling the uncertainties associated with these technologies. In this paper, the unsymmetrical two point estimate method (US2PEM) is used to handle the uncertainties of renewable energy resources. The uncertainty of intermittent generation of WT, photo voltaic cells, and also electric loads, as input variables, are taken into account. The variation of active losses and imported power from the main grid are defined as output variables. The US2PEM is compared to symmetrical two point... 

In deregulated power systems, distribution network operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components. The event of distributed generation (DG) has introduced new challenges to these distribution networks. The role of DG units must be correctly assessed to optimise the overall operating and investment cost for the whole system. However, the distributed generation owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This study presents a long-term dynamic multi-objective model for planning of distribution... 

Hastening the power industry reregulation juxtaposed with the unprecedented utilization of uncertain renewable energies (REs), faces power system operation with sever uncertainties. Consequently, uncertainty assessment of system performance is an obligation. This paper reviews the probabilistic techniques used for probabilistic optimal power flow (P-OPF) studies and proposes a novel and powerful approach using the unscented transformation (UT) method. The heart of the proposed method lies in how to produce the sampling points. Appropriate sampling points are chosen to perform the P-OPF with a high degree of accuracy and less computational burden compared with features of other existing...