This research presents a mathematical model for oil and gas optimal ALLOCATION to different sectors in Iran using operations research techniques. Sectors are residential and commercial, transportation, industries, agriculture, exports, injection to oil reservoirs and power plans as a secondary ENERGY producer. Optimal ALLOCATION of ENERGY RESOURCES to end-uses from 2011 to 2021 has been done using a linear programming model regarding lifting of subsidies. The results provide scientific basic for the optimal ALLOCATION of ENERGY RESOURCES in Iran.This research presents a mathematical model for oil and gas optimal ALLOCATION to different sectors in Iran using operations research techniques. Sectors are residential and commercial, transportation, industries, agriculture, exports, injection to oil reservoirs and power plans as a secondary ENERGY producer. Optimal ALLOCATION of ENERGY RESOURCES to end-uses from 2011 to 2021 has been done using a linear programming model regarding lifting of subsidies. The results provide scientific basic for the optimal ALLOCATION of ENERGY RESOURCES in Iran.

In this paper, a microgrid including a solar panel, a battery ENERGY storage system and a diesel generator as the backup source are optimally is designed. The microgrid is considered as a part of a distribution network, that could be considered as local area. As microgrids can operate in grid-connected mode, the proposed algorithm investigates the minimization of the distribution network power loss, the amount of imported power from the utility and the curtailed load in case of emergency. The main purpose of the proposed algorithm is to minimize the overall investment, replacement and operation and maintenance costs for a microgrid. This article suggests a Lightning Attachment Procedure Optimization Algorithm to optimally design the problem of sitting and scheduling of microgrids in distribution systems. Both problems are solved simultaneously. The proposed approach is applied on 33-bus test system, and the results are discussed. Fast convergence, best global answer finding, and robustness are the characteristics of the proposed method, which are concluded from the results and discussion.

In this paper, we will try to examine the ENERGY efficiency by allocating RESOURCES in wireless powered communications networks (WPCNs). In this study, the several users initially receive ENERGY from the power station and then communicate with the information station. This paper deals with the fairness on the user's ENERGY efficiency while ensuring minimum throughput for users and fulfilling the ENERGY harvesting power constraints. The problem variables are the timing between receiving ENERGY and sending information per user, and the transmit power of each user, whereas in the previous works, it has not been considered as joint ALLOCATION. Due to the non-convex nature of the problem, the some simplifications are used for solving it. In order to solve simplified problem, we present an innovative iterative algorithm with far less complexity than exhaustive search algorithms. Simulation results indicate that the proposed method provides better ENERGY efficiency than other WPCN optimization methods and the only time ALLOCATION method. Also, the presented algorithm balances the ENERGY efficiency among users and simultaneously guarantees the minimum rate required for each user.

Mobile cloud computing (MCC) is a new technology that has been developed to overcome the restrictions of smart mobile devices (e. g. battery, processing power, storage capacity, etc. ) to send a part of the program (with complex computing) to the cloud server (CS). In this paper, we study a multi-cell with multi-input and multi-output (MIMO) system in which the cell-interior users request service for their processing from a common CS. Also, the problem of the optimum offloading is considered as an optimization problem with optimization parameters including communication RESOURCES (such as bandwidth, transmit power and backhaul link capacity) and computational RESOURCES (such as the capacity of cloud server) in the downlink network. The main goal is to minimize the total ENERGY consumption by mobile users (MUs) for processing with the delay limitation for each use. This issue leads to a non-convex problem and to solve the problem, we use successive convex approximation (SCA) method. We finally show that the joint optimization of these parameters leads to reducing the ENERGY consumption of the network with simulation examples.

Fault management optimization in electrical distribution networks especially in critical situations of multiple faults due to adverse weather conditions as an attempt to reduce the destructive social and economic consequences of extensive and long network blackouts in recent years has attracted the attention of researchers in this field. In this paper, an optimal load restoration with the focus on planning the dispatch of repair and operation crews and coordinating the automation system and mobile power generation RESOURCES with the operations of these crews is presented. The proposed model designs remedial actions to reduce customer outages while maintaining network operational constraints, including radial structure, allowable voltage range, and the thermal limits of network conductors. The mathematical formulations of the proposed model are stated in the framework of the mixed-integer linear problem (MILP). In the numerical results of this paper, in order to evaluate performance of the model, IEEE 69-bus network is employed. The obtained numerical results confirm the efficiency of the model in optimal decision making in fault situations.

The integration of Distributed ENERGY RESOURCES (DER) in the distribution network has plenty of advantages if their ALLOCATION and Penetration Level (PL) are done appropriately. Hence, the challenge of finding the best ALLOCATION and PL of DERs in large distribution networks is an important but intricate problem. This paper proposes a novel methodology to simultaneously determine the optimal location/capacity and PL of DERs based on both power losses and voltage deviation minimization, while constraints of voltage profile of feeders under light loading and short circuit capability of the CBs are met. Moreover, a Multi-Objective Mutation based PSO (MOMPSO) is presented that by introducing two modifications of dynamic inertia weight and utilizing a mutation operator improves exploration and exploitation searchability as well as convergence capability of the PSO algorithm. The proposed methodology is tested on a practical distribution network to evaluate its effectiveness in finding optimal location and capacity of DERs along with the feeders.

The purpose of this paper is to present a model for gas ALLOCATION to different sub-sectors in Iran by means of Non-Linear Programming method. Stochastic programming approach is applied to obtain the optimal system configuration meeting the gas demand in different subsectors based on available gas produced. The model considers possible threats would occur in natural gas supply. The solutions provide gas ALLOCATION to different sub-sectors at macro level taking the possible threats in to consideration. Research results show the significant percentage share of gas should be assigned to residential-commercial, power plants, industries, natural gas injection, exportation, petrochemical, rich gas injection, transportation and agriculture respectively. The novelty of this work is its ability to quantitate possible threats using stochastic programming approach in order to provide more holistic point of view on ENERGY security factors impacting gas ALLOCATION in Iran.

A Cooperative Water ALLOCATION Model (CWAM) as a comprehensive model for efficient and equitable ALLOCATION of water in a river basin is designed. This model comprised of two steps: first the initial ALLOCATION of water using Lexicographic Minimax Ratio of Water Shortage (LMWSR), and second, water reALLOCATION and net benefit for an efficient and optimal ALLOCATION of water transfer model. The second step can usethe followings: Irrigation Water Planning Model (IWPM); Hydrologic-Economic River Basin Model (HERBM) and Cooperative ReALLOCATION Game (CRG).This study is performed in order to optimize the ALLOCATION of water RESOURCES of Chahnimeh natural reservoirs in a 12 month term (April 2005 to March 2006) using Game Theory.The results of LMWSR model showed a satisfaction ratio of 1 to 0.89 for domestic water and 1 to 0.49 for agricultural sector. For allocating water to the reservoirs this ratio is less than 1 for all months.The HERBM model results showed that the total ALLOCATION and profit of domestic water is increased in the optimal ALLOCATION compared to the initial ALLOCATION. These are decreased for agricultural compared to the initial ALLOCATION.The reALLOCATION of benefits based on the concept of Shaply value showed that the maximum benefit obtained for the domestic water of Zahedan City which drew the maximum side payment and added value from other stakeholders in the whole period. The least benefit belongs to the agricultural sector.

This paper proposes a new method based on the ideal input vector to estimate inputs of a given decision making unit (DMU) when some or all of its outputs are increased to maintain its current efficiency level. In other words, this paper studied the following question: How much would be the increase in the inputs of the DMU if the decision maker increases certain outputs to a particular unit in which the DMU maintains its current efficiency level? In this study, unlike other proposed methods, the above question was addressed using just the single-objective linear programming (LP) problems. The problem of estimation of inputs was investigated based on the non-radial models. Necessary and sufficient conditions are proposed for estimation of inputs using just the single-objective LP problems. In addition, the level of deficiency (if any exists) in each of the output components is specified. An example with real data is presented to illustrate our proposed method.