scholarly journals Optimal Operation of Soft Open Points-Based Energy Storage in Active Distribution Networks by Considering the Battery Lifetime

2021 ◽  
Vol 8 ◽  
Author(s):  
Jian Wang ◽  
Niancheng Zhou ◽  
Anqi Tao ◽  
Qianggang Wang
Keyword(s):  
Energy Storage ◽  
Reactive Power ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Operation Model ◽  
Battery Lifetime ◽  
Battery Degradation ◽  
Active Distribution Networks

Soft open point-based energy storage (SOP-based ES) can transfer power in time and space and also regulate reactive power. These characteristics help promote the integration of distributed generations (DGs) and reduce the operating cost of active distribution networks (ADNs). Therefore, this work proposed an optimal operation model for SOP-based ES in ADNs by considering the battery lifetime. First, the active and reactive power equations of SOP-based ES and battery degradation cost were modeled. Then, the optimal operation model that includes the operation cost of ADNs, loss cost, and battery degradation cost was established. The mixed integer nonlinear programming model was transformed to a mixed integer linear programming model derived through linearization treatment. Finally, the feasibility and effectiveness of the proposed optimization model are verified by the IEEE33 node system.

scholarly journals Parameterized Modeling and Planning of Distributed Energy Storage in Active Distribution Networks

2019 ◽  
Vol 9 (8) ◽  
pp. 1643 ◽  
Author(s):  
Tianyu Zhao ◽  
Hao Yu ◽  
Guanyu Song ◽  
Chongbo Sun ◽  
Peng Li
Keyword(s):  
Energy Storage ◽  
Programming Model ◽  
Linear Optimization ◽  
Close Correlation ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Distributed Energy ◽  
Distributed Energy Storage ◽  
Parameterized Model ◽  
Active Distribution Networks

In recent years, distributed energy storage (DES) has experienced rapid growth and has been widely applied in active distribution networks (ADNs). Owing to the close correlation between the characteristics and the application scenarios, DES modeling needs to be parameterized separately for various application demands. In this paper, a parameterized model for optimal DES planning in ADNs is proposed. The typical scenarios for DES planning are generated by the clustering technique, containing the patterns of load demand, wind turbine output and photovoltaic output. Secondly, an optimal planning model of DES considering parameterized characteristics is established, which is essentially a mixed integer non-linear optimization problem. Then, the model is converted to a mixed-integer second-order cone programming model, which can be solved efficiently by available commercial software. Finally, case studies on the modified IEEE 33-node system and IEEE 123-node system verify the efficiency of the proposed method, and the effects of DES planning are validated by two evaluation indexes.

scholarly journals Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA

2021 ◽  
Vol 11 (5) ◽  
pp. 2175
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Jesus C. Hernández
Keyword(s):  
Objective Function ◽  
Reactive Power ◽  
Programming Model ◽  
Search Algorithm ◽  
Solution Space ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Solution Vector ◽  
The Impact

The problem of reactive power compensation in electric distribution networks is addressed in this research paper from the point of view of the combinatorial optimization using a new discrete-continuous version of the vortex search algorithm (DCVSA). To explore and exploit the solution space, a discrete-continuous codification of the solution vector is proposed, where the discrete part determines the nodes where the distribution static compensator (D-STATCOM) will be installed, and the continuous part of the codification determines the optimal sizes of the D-STATCOMs. The main advantage of such codification is that the mixed-integer nonlinear programming model (MINLP) that represents the problem of optimal placement and sizing of the D-STATCOMs in distribution networks only requires a classical power flow method to evaluate the objective function, which implies that it can be implemented in any programming language. The objective function is the total costs of the grid power losses and the annualized investment costs in D-STATCOMs. In addition, to include the impact of the daily load variations, the active and reactive power demand curves are included in the optimization model. Numerical results in two radial test feeders with 33 and 69 buses demonstrate that the proposed DCVSA can solve the MINLP model with best results when compared with the MINLP solvers available in the GAMS software. All the simulations are implemented in MATLAB software using its programming environment.

scholarly journals A Decoupling Rolling Multi-Period Power and Voltage Optimization Strategy in Active Distribution Networks

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5789
Author(s):  
Xiaohui Ge ◽  
Lu Shen ◽  
Chaoming Zheng ◽  
Peng Li ◽  
Xiaobo Dou
Keyword(s):  
Benders Decomposition ◽  
Reactive Power ◽  
Distribution Networks ◽  
Voltage Regulation ◽  
Test System ◽  
Mixed Integer ◽  
Discrete Equation ◽  
Optimization Strategy ◽  
Short Period ◽  
Active Distribution Networks

With the increasing penetration of distributed photovoltaics (PVs) in active distribution networks (ADNs), the risk of voltage violations caused by PV uncertainties is significantly exacerbated. Since the conventional voltage regulation strategy is limited by its discrete devices and delay, ADN operators allow PVs to participate in voltage optimization by controlling their power outputs and cooperating with traditional regulation devices. This paper proposes a decoupling rolling multi-period reactive power and voltage optimization strategy considering the strong time coupling between different devices. The mixed-integer voltage optimization model is first decomposed into a long-period master problem for on-load tap changer (OLTC) and multiple short-period subproblems for PV power by Benders decomposition algorithm. Then, based on the high-precision PV and load forecasts, the model predictive control (MPC) method is utilized to modify the independent subproblems into a series of subproblems that roll with the time window, achieving a smooth transition from the current state to the ideal state. The estimated voltage variation in the prediction horizon of MPC is calculated by a simplified discrete equation for OLTC tap and a linearized sensitivity matrix between power and voltage for fast computation. The feasibility of the proposed optimization strategy is demonstrated by performing simulations on a distribution test system.

scholarly journals Genetic-Convex Model for Dynamic Reactive Power Compensation in Distribution Networks Using D-STATCOMs

2021 ◽  
Vol 11 (8) ◽  
pp. 3353
Author(s):  
Oscar Danilo Montoya ◽  
Harold R. Chamorro ◽  
Lazaro Alvarado-Barrios ◽  
Walter Gil-González ◽  
César Orozco-Henao
Keyword(s):  
Objective Function ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Energy Losses ◽  
Optimization Approach ◽  
Operative Costs

This paper proposes a new hybrid master–slave optimization approach to address the problem of the optimal placement and sizing of distribution static compensators (D-STATCOMs) in electrical distribution grids. The optimal location of the D-STATCOMs is identified by implementing the classical and well-known Chu and Beasley genetic algorithm, which employs an integer codification to select the nodes where these will be installed. To determine the optimal sizes of the D-STATCOMs, a second-order cone programming reformulation of the optimal power flow problem is employed with the aim of minimizing the total costs of the daily energy losses. The objective function considered in this study is the minimization of the annual operative costs associated with energy losses and installation investments in D-STATCOMs. This objective function is subject to classical power balance constraints and device capabilities, which generates a mixed-integer nonlinear programming model that is solved with the proposed genetic-convex strategy. Numerical validations in the 33-node test feeder with radial configuration show the proposed genetic-convex model’s effectiveness to minimize the annual operative costs of the grid when compared with the optimization solvers available in GAMS software.

scholarly journals An Approximate Mixed-Integer Convex Model to Reduce Annual Operating Costs in Radial Distribution Networks Using STATCOMs

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3102
Author(s):  
Oscar Danilo Montoya ◽  
Lázaro Alvarado-Barrios ◽  
Jesus C. Hernández
Keyword(s):  
Optimal Power Flow ◽  
Large Scale ◽  
Location Problem ◽  
Reactive Power ◽  
Programming Model ◽  
Search Algorithm ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Convex Model ◽  
Integer Quadratic Programming

The problem of optimal siting and sizing of distribution static compensators (STATCOMs) is addressed in this research from the point of view of exact mathematical optimization. The exact mixed-integer nonlinear programming model (MINLP) is decoupled into two convex optimization sub-problems, named the location problem and the sizing problem. The location problem is addressed by relaxing the exact MINLP model, assuming that all the voltages are equal to 1∠0∘, which allows obtaining a mixed-integer quadratic programming model as a function of the active and reactive power flows. The solution of this model provides the best set of nodes to locate all the STATCOMs. When all the nodes are selected, it solves the optimal reactive power problem through a second-order cone programming relaxation of the exact optimal power flow problem; the solution of the SOCP model provides the optimal sizes of the STATCOMs. Finally, it refines the exact objective function value due to the intrinsic non-convexities associated with the costs of the STATCOMs that were relaxed through the application of Taylor’s series expansion in the location and sizing stages. The numerical results in the IEEE 33- and 69-bus systems demonstrate the effectiveness and robustness of the proposed optimization problem when compared with large-scale MINLP solvers in GAMS and the discrete-continuous version of the vortex search algorithm (DCVSA) recently reported in the current literature. With respect to the benchmark cases of the test feeders, the proposed approach reaches the best reductions with 14.17% and 15.79% in the annual operative costs, which improves the solutions of the DCVSA, which are 13.71% and 15.30%, respectively.

scholarly journals Optimal Capacity Allocation of Energy Storage in Distribution Networks Considering Active/Reactive Coordination

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1611
Author(s):  
Tao Xu ◽  
He Meng ◽  
Jie Zhu ◽  
Wei Wei ◽  
He Zhao ◽  
...  
Keyword(s):  
Energy Storage ◽  
Life Cycle Cost ◽  
Large Scale ◽  
Reactive Power ◽  
Supply And Demand ◽  
Distribution Networks ◽  
Capacity Allocation ◽  
Mixed Integer ◽  
Optimal Capacity ◽  
Network Losses

Energy storage system (ESS) has been advocated as one of the key elements for the future energy system by the fast power regulation and energy transfer capabilities. In particular, for distribution networks with high penetration of renewables, ESS plays an important role in bridging the gap between the supply and demand, maximizing the benefits of renewables and providing various types of ancillary services to cope the intermittences and fluctuations, consequently improving the resilience, reliability and flexibility. To solve the voltage fluctuations caused by the high permeability of renewables in distribution networks, an optimal capacity allocation strategy of ESS is proposed in this paper. Taking the life cycle cost, arbitrage income and the benefit of reducing network losses into consideration, a bilevel optimization model of ESS capacity allocation is established, the coordination between active/reactive power of associate power conversion system is considered, and the large scale nonlinear programming problem is solved using genetic algorithm, simulated annealing and mixed integer second-order cone programming method. The feasibility and effectiveness of the proposed algorithm have been verified.

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

scholarly journals Using Energy Storage Inverters of Prosumer Installations for Voltage Control in Low-Voltage Distribution Networks

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1121
Author(s):  
Rozmysław Mieński ◽  
Przemysław Urbanek ◽  
Irena Wasiak
Keyword(s):  
Energy Storage ◽  
Control Strategy ◽  
Reactive Power ◽  
Low Voltage ◽  
Storage System ◽  
Distribution Networks ◽  
Energy Storage System ◽  
Voltage Regulation ◽  
Active Power ◽  
Total Power

The paper includes the analysis of the operation of low-voltage prosumer installation consisting of receivers and electricity sources and equipped with a 3-phase energy storage system. The aim of the storage application is the management of active power within the installation to decrease the total power exchanged with the supplying network and thus reduce energy costs borne by the prosumer. A solution for the effective implementation of the storage system is presented. Apart from the active power management performed according to the prosumer’s needs, the storage inverter provides the ancillary service of voltage regulation in the network according to the requirements of the network operator. A control strategy involving algorithms for voltage regulation without prejudice to the prosumer’s interest is described in the paper. Reactive power is used first as a control signal and if the required voltage effect cannot be reached, then the active power in the controlled phase is additionally changed and the Energy Storage System (ESS) loading is redistributed in phases in such a way that the total active power set by the prosumer program remains unchanged. The efficiency of the control strategy was tested by means of a simulation model in the PSCAD/EMTDC program. The results of the simulations are presented.

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