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.
Distribution Systems
H. Yousefi; S.A. Gholamian; A. Zakariazadeh
Abstract
In this paper, a distributed method for reactive power management in a distribution system has been presented. The proposed method focuses on the voltage rise where the distribution systems are equipped with a considerable number of photovoltaic units. This paper proposes the alternating direction method ...
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In this paper, a distributed method for reactive power management in a distribution system has been presented. The proposed method focuses on the voltage rise where the distribution systems are equipped with a considerable number of photovoltaic units. This paper proposes the alternating direction method of multipliers (ADMMs) approach for solving the optimal voltage control problem in a distributed manner in a distribution system with high penetration of PVs. Also, the proposed method uses a clustering approach to divide the network into partitions based on the coupling degrees among different nodes. The optimal reactive power control strategy is conducted in each partition and integrated using ADMM. The proposed method is tested on a 33 bus IEEE distribution test system and a modified IEEE 123-node system. The result evidence that the proposed method has used the lower reactive power if compared to the conventional method.
Distribution Systems
H. Fateh; A. Safari; S. Bahramara
Abstract
Distributed energy resources (DERs) including distributed generators (DGs) and controllable loads (CLs) are managed in the form of several microgrids (MGs) in active distributions networks (ADNs) to meet the demand locally. On the other hand, some loads of distribution networks (DNs) can be supplied ...
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Distributed energy resources (DERs) including distributed generators (DGs) and controllable loads (CLs) are managed in the form of several microgrids (MGs) in active distributions networks (ADNs) to meet the demand locally. On the other hand, some loads of distribution networks (DNs) can be supplied by retailers which participate in wholesale energy markets. Therefore, there are several decision makers in DNs which their cooperation should be modeled for optimal operation of the network. For this purpose, a bi-level optimization approach is proposed in this paper to model the cooperation between retailers and MGs in DNs. In the proposed model, the aim of the upper level (leader) and lower level (follower) problems are to maximize the profit of retailers and to minimize the cost of MGs, respectively. To solve the proposed multi-objective bi-level optimization model, multi-objective Particle Swarm Optimization (MOPSO) algorithm is employed. The effectiveness of the proposed bi-level model and its solution methodology is investigated in the numerical results.
Distribution Systems
O. Eghbali; R. Kazemzadeh; K. Amiri
Abstract
State estimation in the energy management center of active distribution networks has attracted many attentions. Considering an increase in complexity and real-time management of active distribution networks and knowing the network information at each time instant are necessary. This article presents ...
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State estimation in the energy management center of active distribution networks has attracted many attentions. Considering an increase in complexity and real-time management of active distribution networks and knowing the network information at each time instant are necessary. This article presents a two-step multi-area state estimation method in balanced active distribution networks. The proposed method is based on the location of PMU measurements of the network. The network is divided into several sub-areas about PMUs in the first step. A local sate estimation is implemented in each sub-area. The estimated values of the first step along with real measurements are used as measurements for second step estimation. The measurements are located in each sub-area using these values based on the ellipse area method, and the best location of measurements is extracted. Therefore, a second step state estimation including integrated state estimation of the whole network is performed by using the measurements obtained and located from the first step. The estimation results of the first step are used in the second step which improve the estimation accuracy. Simulations are performed on a standard IEEE 69-bus network to validate the proposed method.
Distribution Systems
R. Afshan; J. Salehi
Abstract
This paper proposes a novel hybrid Monte Carlo simulation-genetic approach (MCS-GA) for optimal operation of a distribution network considering renewable energy generation systems (REGSs) and battery energy storage systems (BESSs). The aim of this paper is to design an optimal charging /discharging scheduling ...
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This paper proposes a novel hybrid Monte Carlo simulation-genetic approach (MCS-GA) for optimal operation of a distribution network considering renewable energy generation systems (REGSs) and battery energy storage systems (BESSs). The aim of this paper is to design an optimal charging /discharging scheduling of BESSs so that the total daily profit of distribution company (Disco) can be maximized. In this study, the power generation of REGSs such as photovoltaic resources (PVs) and the network electricity prices are studied through their uncertainty natures. The probability distribution function (PDF), is used to account for uncertainties in this paper. Also, the Monte Carlo simulation (MCS) is applied to generate different scenarios of network electricity prices and solar irradiation of PVs. Optimal scheduling of BESSs can be performed by genetic algorithm (GA). In this paper, firstly, the charging and discharging state of BESSs (positive or negative sign of battery power) is determined according to the variable amount of the electricity prices and power produced from PVs, which have been obtained from the Monte Carlo simulation. Then by using the GA, optimal amount of BESSs is determined. Therefore, a hybrid MCS-GA is used to solve this problem. Numerical examples are presented to illustrate the optimal charging/discharging power of the battery for maximizing the total daily profit.
Distribution Systems
Soheil Derafshi Beigvand; Hamdi Abdi,
Volume 3, Issue 2 , December 2015, , Pages 102-115
Abstract
This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel ...
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This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel flexible load curtailment cost associated with DLC programs. The load curtailment cost is based on a virtual generator for each load (which participates in DLC program). To implement the load curtailment in the objective function, we consider incentive payments for participants and a load shedding priority list in some events. The proposed OPF methodology is applied to IEEE 14, 30-bus, and 13-node industrial power systems as three examples of the smart grids, respectively. The numerical results of the proposed algorithm are compared with the results obtained by applying MATPOWER to the nominal case by using the DLC programs. It is shown that the suggested approach converges to a better quality solution in an acceptable computation time.
