Distribution Systems
S. Behzadi; N. Osali; A. Younesi; A. Bagheri
Abstract
Nowadays, with the detrimental impacts of air pollution on human health and its significant societal expenses, it has been imperative to utilize renewable energy sources (RESs) and energy storage systems (ESSs). This study introduces a new objective function aimed at achieving a long-term optimal plan ...
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Nowadays, with the detrimental impacts of air pollution on human health and its significant societal expenses, it has been imperative to utilize renewable energy sources (RESs) and energy storage systems (ESSs). This study introduces a new objective function aimed at achieving a long-term optimal plan where it contrasts the outcomes of meeting network load demand with and without the integration of renewable/non-renewable distributed energy resources (DERs). The analysis considers installation and operational costs, addressing uncertainties through Monte-Carlo and scenario-based methodologies. The proposed problem is structured as a convex optimization model. Simulations are conducted on the IEEE 33-bus system, showcasing the model’s efficacy through cost efficiency and reduced emission expenses. The study confirms that the investment in renewable energy resources and ESS units can be recouped in less than five years. It was observed that in the long-term, there is a cost reduction of 29.4\% when DER units are incorporated. Also, the emission cost for the horizon year is diminished by 43.2\% compared to the case where the DERs are absent.
Energy Management
Sh. Shadi; J. Salehi; A. Safari
Abstract
Energy management (EM) in smart distribution networks (SDN) is to schedule the power transaction between the SDN and the existing distributed energy resources (DERs) e.g., distributed generations, especially renewable resources and electrical vehicles, from an eco-technical viewpoint. Due to the dual ...
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Energy management (EM) in smart distribution networks (SDN) is to schedule the power transaction between the SDN and the existing distributed energy resources (DERs) e.g., distributed generations, especially renewable resources and electrical vehicles, from an eco-technical viewpoint. Due to the dual role of electric vehicles (EVs) acting as a power source and load, they presented both challenges and opportunities in EM. The complexity of EM increases as DERs become more prevalent in SDN. Moreover, the uncertainties of renewable resources, price, and load besides the uncertainties related to the place, amount, and time of EV’s charging makes EM a more intricate field. This supports the necessity of extensive tools and approaches to manage EM in SDNs. In this respect, this paper proposes an optimum scenario-based stochastic energy management scheme for intelligent distribution networks. The proposed approach is modeled as a MINLP problem and solved in GAMS software under the DICOPT solver. The test is conducted on a 33-bus SDN with and without factoring in uncertainties.
H. Farahbakhsh; I. Pourfar; A. Lashkar Ara
Abstract
In this paper, virtual power plant (VPP) planning is done using distributed generation sources to create a safe platform for electricity exchange and to increase the profitability and sustainability of electricity. In the proposed model, the effect of micro-grid interaction with the electricity market ...
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In this paper, virtual power plant (VPP) planning is done using distributed generation sources to create a safe platform for electricity exchange and to increase the profitability and sustainability of electricity. In the proposed model, the effect of micro-grid interaction with the electricity market in the presence of distributed generation resources and storage is investigated. To solve this problem, an improved artificial bee colony algorithm using the accept-reject method (AR-ABC) is used. The AR method is employed to limit the initial search space as well as for the scenario reduction process. Also, uncertainties related to loads and renewable sources are formulated in a sample micro-grid including micro-turbine (MT), fuel cell (FC), wind turbine (WT), photovoltaic cells (PV) and batteries for storage; the results are compared with those of other methods, which shows this method works better than others. The software simulations of this research are done in the MATLAB software environment.
G. Derakhshan; H. Shahsavari; A. Safari
Abstract
Distributed generators (DGs) facilitate minimizing a monetary objective for controlling overload or low-voltage obstacles. In conjunction with controlling such complications, a DG unit can be allocated for maximum reliability or efficiency. This study presents a new method based on a new index for locating ...
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Distributed generators (DGs) facilitate minimizing a monetary objective for controlling overload or low-voltage obstacles. In conjunction with controlling such complications, a DG unit can be allocated for maximum reliability or efficiency. This study presents a new method based on a new index for locating and sizing DGs in electricity distribution systems. Stable node voltages which are known as power stability index (PSI) are considered in developing the index. An analytical method is applied in visualizing the effect of DG on losses, voltage profile, and voltage stability of the system. In this study, a new approach using co-evolutionary multi-swarm particle swarm optimization (CMPSO) algorithm is purposed for locating DGs in radial electrical distribution systems considering the uncertainty of solar power as well as load and wind power. In this paper, the optimal locations and sizes of DG units are calculated by considering the active power loss, reliability index, and PSI as objective functions. The presented algorithm is tested on 33-bus and 274-bus real distribution networks. The results of the simulation show the effectiveness of the proposed method.
B. Sheykhloei; T. Abedinzadeh; L. Mohammadiyan; B. Mohammadi-Ivatloo
Abstract
The increment integration of renewable distributed energies means the desired operation of the electric power system will significantly depend on the performance of primary energy. In this order, an integrated approach for mutual interaction between the electricity and natural gas systems has been considered ...
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The increment integration of renewable distributed energies means the desired operation of the electric power system will significantly depend on the performance of primary energy. In this order, an integrated approach for mutual interaction between the electricity and natural gas systems has been considered for the purpose of ensuring optimal energy exchanging between the electric power system and the natural gas network. We propose a scenario based optimal operation approach to optimize the operation of integrated power and gas systems (IPGS). Regarding the unpredictable nature of wind speed and solar radiation as well as uncertain load demand, random scenarios are generated by a normal probability density function. Then, Latin hypercube sampling is applied to realize the stochastic framework of IPGS operation. The proposed model minimizes the operation cost of conventional power system generators and gas wells over a 24 h operation horizon. In addition, the conditional value-at-risk is utilized to manage financial risks and uncertainties due to the operation cost-minimizing in the proposed IPGS optimal operation problem. The proposed integrated operating approach is applied to a 24-Bus power system with renewable resources of a photovoltaic, wind turbine, energy storage, with a 7-node natural gas network and two gas wells.
Energy Management
E. Shahryari; H. Shayeghi; B. Mohammadi-ivatloo; M. Moradzadeh
Abstract
Recently, economic and environmental problems have created a strong attitude toward utilizing renewable energy sources (RESs). Nevertheless, uncertainty of wind and solar power leads to a more complicated energy management (EM) of RESs in microgrids. This paper models and solves the EM problem of microgrid ...
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Recently, economic and environmental problems have created a strong attitude toward utilizing renewable energy sources (RESs). Nevertheless, uncertainty of wind and solar power leads to a more complicated energy management (EM) of RESs in microgrids. This paper models and solves the EM problem of microgrid from the generation point of view. To do this, mathematical formulation of a grid- connected microgrid including wind turbine (WT), photovoltaic (PV), micro turbine (MT), fuel cell (FC) and energy storage system (ESS) is presented. Furthermore an improved incentive-based demand response program (DRP) is applied in microgrid EM problem to flatten the load pattern. Comprehensive studying of EM in both intra-day and day-ahead markets is another contribution of this paper. However, the main novelty of this paper is proposing a new uncertainty modeling technique which is based on copula function and scenario generation. This paper tries to optimize operational cost and environmental pollution as the objective functions and solve them using group search optimization (GSO) algorithm. Numerical results approve the efficiency of the proposed method in solving microgrid EM problem.
Energy Management
K. Masoudi; H. Abdi
Abstract
This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity ...
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This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity market prices, unpredictable load demand, and uncertain wind and solar power values, due to intrinsically stochastic weather changes, were also considered in the proposed method. To cope with uncertainties, the scenario-based stochastic approach was utilized, and the reduction of the environmental emissions generated by the power resources was regarded as the second objective, besides the cost of units’ operation. The ɛ-constraint method was employed to deal with the presented multi-objective optimization problem, and the simulations were performed on a sample MG with one month of real data. The results demonstrated the applicability and effectiveness of the proposed techniques in real-world conditions.
Micro Grid
A. Marami Dizaji; M. Saniee; K. Zare
Abstract
Resilient operation of microgrid is an important concept in modern power system. Its goal is to anticipate and limit the risks, and provide appropriate and continuous services under changing conditions. There are many factors that cause the operation mode of micogrid changes between island and grid-connected ...
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Resilient operation of microgrid is an important concept in modern power system. Its goal is to anticipate and limit the risks, and provide appropriate and continuous services under changing conditions. There are many factors that cause the operation mode of micogrid changes between island and grid-connected modes. On the other hand, nowadays, electric vehicles (EVs) are desirable energy storage systems (ESSs) because of clean transportation. Besides, energy storage systems are helpful to decrease power generation fluctuations arising from renewable energy sources (RESs) in new power systems. In addition, both sides (EV and RESs’ owners) can gain a good profit by integrating EVs and RESs. Therefore, in this paper, a resilient operation model for microgrid is presented considering disasters and islands from the grid. In the proposed formulation, microgrid (MG) operator schedules its energy resources, EVs and ESSs in minimum cost considering demand response (DR) program and resiliency of the microgrid to islanding and uncertainties in market price, load, and generation of RESs. The impact of uncertainties is modeled in the scenario based framework as stochastic programming. The efficiency of presented method is validated on IEEE standard test system and discussed in two cases.
Energy Management
A. Dolatabadi; R. Ebadi; B. Mohammadi-Ivatloo
Abstract
Ships play the major role in bulk transportation and they need their special energy system. This paper proposes a stochastic programing method for optimal sizing of a hybrid ship power system with energy storage system (ESS), photovoltaic power (PV) and diesel generator. To account for uncertainties, ...
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Ships play the major role in bulk transportation and they need their special energy system. This paper proposes a stochastic programing method for optimal sizing of a hybrid ship power system with energy storage system (ESS), photovoltaic power (PV) and diesel generator. To account for uncertainties, in this study a two-stage stochastic mixed-integer non-linear programing is used to model the optimal design problem of hybrid system for ships. The uncertainty of the hourly global solar irradiation and its effect on the output power of the PV system is taken into account. The probability density function of the global solar radiation follows a normal distribution. The Monte Carlo sampling approach is used to generate the scenarios with a specified probability and a proper scenario reduction method is used to decrease the computational burden of problem. Three cases are studied and the results are presented and compared.
Distribution Systems
A. Najafi; R. Aboli; H. Falaghi; M. Ramezani
Volume 4, Issue 2 , December 2016, , Pages 153-164
Abstract
Utilizing capacitor banks is very conventional in distribution network in order for local compensation of reactive power. This will be more important considering uncertainties including wind generation and loads uncertainty. Harmonics and non-linear loads are other challenges in power system which complicates ...
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Utilizing capacitor banks is very conventional in distribution network in order for local compensation of reactive power. This will be more important considering uncertainties including wind generation and loads uncertainty. Harmonics and non-linear loads are other challenges in power system which complicates the capacitor placement problem. Thus, uncertainty and network harmonics have been considered in this paper, simultaneously. Capacitor placement has been proposed as a probabilistic harmonic problem with different objectives and technical constraints in the capacitor placement problem. Minimizing power and energy loss and capacitor prices are considered as objectives. Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms have been used to solve the optimization problem. Loads are subjected to uncertainty with normal probabilistic distribution function (PDF). Auto Regressive and Moving Average (ARMA) time series and two point estimate method have also been utilized to simulate the wind speed and to perform the probabilistic load flow, respectively. Finally, the proposed method has been implemented on standard distorted test cases in different scenarios. Monte Carlo Simulation (MCS) has also been used to verify the probabilistic harmonic power flow. Simulation results demonstrate the efficiency of the proposed method.
Dynamics
M. Sadeghi; M. Kalantar
Volume 4, Issue 1 , June 2016, , Pages 1-15
Abstract
This study presents a dynamic way in a DG planning problem instead of the last static or pseudo-dynamic planning point of views. A new way in modeling the DG units’ output power and the load uncertainties based on the probability rules is proposed in this paper. A sensitivity analysis on the stochastic ...
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This study presents a dynamic way in a DG planning problem instead of the last static or pseudo-dynamic planning point of views. A new way in modeling the DG units’ output power and the load uncertainties based on the probability rules is proposed in this paper. A sensitivity analysis on the stochastic nature of the electricity price and global fuel price is carried out through a proposed model. Six types of clean and conventional DG units are included in the planning process. The presented dynamic planning problem is solved considering encouraging and punishment functions. The imperialist competitive algorithm (ICA) as a strong evolutionary strategy is employed to solve the DG planning problem. The proposed models and the proposed problem are applied on the 9-bus and 33-bus test distribution systems. The results show a significant improvement in the total revenue of the distribution system in all of the defined scenarios.
