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M. Zarif, M. H. Javidi, M. S. Ghazizadeh,
Volume 8, Issue 2 (6-2012)
Abstract

This paper presents a decision making approach for mid-term scheduling of large industrial consumers based on the recently introduced class of Stochastic Dominance (SD)- constrained stochastic programming. In this study, the electricity price in the pool as well as the rate of availability (unavailability) of the generating unit (forced outage rate) is considered as uncertain parameters. The self-scheduling problem is formulated as a stochastic programming problem with SSD constraints by generating appropriate scenarios for pool price and self-generation unit's forced outage rate. Furthermore, while most approaches optimize the cost subject to an assumed demand profile, our method enforces the electricity consumption to follow an optimum profile for mid-term time scheduling, i.e. three months (12 weeks), so that the total production will remain constant.
B. Adineh, H. Rajabi Mashhadi, M. E. Hajiabadi,
Volume 10, Issue 2 (6-2014)
Abstract

The main goal of this paper is to structurally analyze impact of DSM programs on reliability indices. A new approach is presented to structurally decompose reliability index Expected Energy Not Supplied (EENS) by using Monte Carlo simulation. EENS is decomposed into two terms. The first term indicates EENS which is caused by generation contingencies. The second term indicates EENS which is caused by transmission and generation contingencies. The proposed approach can be used to indicate appropriate buses for applying DSM. Furthermore, networks are studied at two levels HLI and HLII. Studies show that in some networks reliability indices are affected mostly at the HLI level. While in some other networks, reliability indices are influenced mostly at the HLII level. It means that in these networks, reliability indices are affected by transmission contingencies. Then, it is shown that the implementation of load shifting is effective in some networks and buses. These are the ones which their EENS is more influenced by generation contingencies. However it is not effective in the ones which their EENS is more influenced by transmission contingencies. The simulation results on the IEEE-RTS and Khorasan network show the efficiency of the proposed approach.
H. Rajabi Mashhadi, H. Safari Farmad,
Volume 11, Issue 1 (3-2015)
Abstract

The main goal of this paper is to present a new day-ahead energy acquisition model for a distribution company (Disco) in a competitive electricity market environment with Interruptible Load (IL). The work formulates the Disco energy acquisition model as a bi-level optimization problem with some of real issues, and then studies and designs a Genetic Algorithm (GA) of this optimization problem too. To achieve this goal, a novel two-step procedure is proposed. At the first step, a realistic model for an industrial interruptible load is introduced, and it is shown that Interruptible load model may affect the problem modeling and solving. At the second step, Disco energy acquisition program is formulated and solved with this realistic model. As a result, this paper shows energy acquisition programming model with ILs, by considering real assumptions. The introduced method shows a good performance of problem modeling and solving algorithm both in terms of solution quality and computational results. In addition, a case study is carried out considering a test system with some assumptions. Subsequently results show the general applicability of the proposed model with potential cost saving for the Disco
N. Eskandari, S. Jalilzadeh,
Volume 12, Issue 4 (12-2016)
Abstract

Load side management is the basic and significant principle to keeping the balance between generation side and consumption side of electrical power energy. Load side management on typical medium voltage feeder is the power energy consumption control of connected loads with variation of essential parameters that loads do reaction to their variation. Knowing amount of load's reaction to each parameters variation in typical medium voltage feeder during the day, leads to gain Load Manageability Factor (LMF) for that specific feeder that helps power utilities to manage their connected loads. Calculating this LMF needs to find out each types of load with unique inherent features behavior to each parameters variation. This paper results and future work results will help us to catch mentioned LMF. In this paper analysis of residential load behavior due to temperature variation with training artificial neural network will be done. Load behavior due to other essential parameters variations like energy pricing variation, major event happening, and power utility announcing to the customers, and etc will study in future works. Collecting all related works results in a unit mathematical equation or an artificial neural network will gain LMF.


S. G. M. Rokni, M. Radmehr, A. Zakariazadeh,
Volume 15, Issue 1 (3-2019)
Abstract

In this paper, a new energy management method is proposed for residential consumers based on a distributed algorithm. Consumers could participate in demand response programs by managing their schedulable and deferrable loads as well as using of photovoltaic (PV) systems. In the proposed method, the Alternating Direction Method of Multiplier (ADMM) is used to model the distributed management and scheduling of buildings electricity consumption. By implementing the distributed algorithm, a large number of residential consumers can update their consumption parameters by online communication with the central controller in parallel. The results confirm that residential customers are able to reduce their electricity bill by modifying their electricity consumption patterns without reducing their welfare.

M. Aghamohamadi, M. Samadi, M. Pirnahad,
Volume 15, Issue 1 (3-2019)
Abstract

The integration of different energy types and new technological advances in multi-energy infrastructures, enable energy hubs (EH) to supply load demands at a lower cost which may affect the price responsive loads, since the energy could be offered with a lower price at the EH output ports, compared to the upstream energy markets. In this paper a new EH operation model is proposed by which the optimal responsive load modifications against the obtained EH output energy prices as well as the EH schedules are determined. To achieve this goal, a tri-step approach is proposed. At the first step the EH output energy prices are obtained for each energy type in each hour of the scheduling horizon. These energy prices are based on the EH hourly operation and would change as the EH operation changes. At the second step, the optimal responsive load modifications against the obtained EH output energy prices are simulated using the new proposed integrated responsive load model which is capable to model the price responsive loads in multi-energy systems for any type of energy carrier. Since, any changes in load demand (due to its responsiveness) can jeopardize the EH power balance constraint, the obtained EH operation would be infeasible, considering the new modified load pattern. To cope with this interdependency, a new iterative methodology is proposed at the third step in which, the EH optimal operation + EH output energy price determination + responsive load modification is implemented in a loop till the 24 hour aggregated load modification becomes lower than the pre-determined convergence tolerance. Based on the obtained results from solving the proposed methodology through a comprehensive case study, the aggregated supplied energy has been increased by 7.3%, while, the customers payments has reduced by 14.6%. Accordingly, the customer’s satisfaction has increased.

M. Mozaffari Legha, E. Farjah,
Volume 16, Issue 2 (6-2020)
Abstract

This paper aims to establish an Arduino and IoT-based Hierarchical Multi-Agent System (HMAS) for management of loads’ side with incentive approach in a micro-grid. In this study, the performance of the proposed algorithm in a micro-grid has been verified. The micro-grid contains a battery energy storage system (BESS) and different types of loads known as residential consumer (RC), commercial consumer (CC), and industrial consumer (IC). The user interface on a smartphone directly communicates with the load management system via an integrated Ethernet Shield server which uses Wi-Fi communication protocol. Also, the communication between the Ethernet Shield and the Arduino microcontroller is based on Wi-Fi communication. A simulation model is developed in Java Agent Development Environment (JADE) for dynamic and effective energy administration, which takes an informed decision and chooses the most feasible action to stabilize, sustain, and enhance the micro-grid. Further, the environment variable is sensed through the Arduino microcontroller and sensors, and then given to the MAS agents in the IoT environment. The test results indicated that the system was able to effectively control and regulate the energy in the micro-grid.

Akanksha Jain, S.c. Gupta,
Volume 20, Issue 3 (9-2024)
Abstract

Due to the anticipated increase in loads, the power grid will encounter the issue of system peak loads in the future, which is typically addressed through grid reinforcement. However, implementing a flexibility service option can prevent the need for grid development. As the overall load continues to rise, the distribution transformer becomes overloaded. The presented work focuses on enhancing one of the parameters that define the insulation life of the transformer, known as the Loss-of-Life (LOL). Transactive approach involves the rescheduling of the battery and photovoltaic generation. Dominated Group Search Optimization (DGSO) algorithm is utilized to optimize the objective function of reducing the peak transformer load under the power flow and voltage constraints of the network. Experimental validation of the proposed method is conducted using MATLAB 2018 software. Modified IEEE 34-bus system is used to implement the proposed methodology. Numerical results obtained from various cases elucidate that the proposed model reduces the LOL of the transformer from 0.0103 to 0.0017 p.u.Comparative analysis of the proposed method with the already used methods of voltage-control and Volt-Var control have been presented.

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.