scholarly journals Prospects of a Meshed Electrical Distribution System Featuring Large-Scale Variable Renewable Power

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3399 ◽  
Author(s):  
Marco Cruz ◽  
Desta Fitiwi ◽  
Sérgio Santos ◽  
Sílvio Mariano ◽  
João Catalão
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Large Scale ◽  
Global Climate ◽  
Mixed Integer ◽  
Programming Approach ◽  
Renewable Power ◽  
Electrical Distribution ◽  
Stochastic Framework ◽  
Distribution Grids

Electrical distribution system operators (DSOs) are facing an increasing number of challenges, largely as a result of the growing integration of distributed energy resources (DERs), such as photovoltaic (PV) and wind power. Amid global climate change and other energy-related concerns, the transformation of electrical distribution systems (EDSs) will most likely go ahead by modernizing distribution grids so that more DERs can be accommodated. Therefore, new operational strategies that aim to increase the flexibility of EDSs must be thought of and developed. This action is indispensable so that EDSs can seamlessly accommodate large amounts of intermittent renewable power. One plausible strategy that is worth considering is operating distribution systems in a meshed topology. The aim of this work is, therefore, related to the prospects of gradually adopting such a strategy. The analysis includes the additional level of flexibility that can be provided by operating distribution grids in a meshed manner, and the utilization level of variable renewable power. The distribution operational problem is formulated as a mixed integer linear programming approach in a stochastic framework. Numerical results reveal the multi-faceted benefits of operating distribution grids in a meshed manner. Such an operation scheme adds considerable flexibility to the system and leads to a more efficient utilization of variable renewable energy source (RES)-based distributed generation.

scholarly journals A Novel Linear Optimal Power Flow Model for Three-Phase Electrical Distribution Systems

2020 ◽  
Author(s):  
Juan Sebastian Giraldo ◽  
Pedro Pablo Vergara ◽  
Juan Camilo Lopez ◽  
Phuong Nguyen ◽  
Nikolaos Paterakis
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Flow Model ◽  
Mixed Integer ◽  
Electrical Distribution Systems ◽  
Optimal Power ◽  
Electrical Distribution ◽  
Three Phase

This paper presents a new linear optimal power flow model for three-phase unbalanced electrical distribution systems considering binary variables. The proposed formulation is a mixed-integer linear programming problem, aiming at minimizing the operational costs of the network while guaranteeing operational constraints. Two new linearizations for branch current and nodal voltage magnitudes are introduced. The proposed branch current magnitude linearization provides a discretization of the Euclidean norm through a set of intersecting planes; while the bus voltage magnitude approximation uses a linear combination of the L1 and the L∞ norm. Results were obtained for an unbalanced distribution system, in order to assess the accuracy of the linear formulation when compared to a nonlinear power flow with fixed power injections, showing errors of less than 4\% for currents and 0.005\% for voltages.

scholarly journals A Novel Linear Optimal Power Flow Model for Three-Phase Electrical Distribution Systems

2020 ◽  
Author(s):  
Juan Sebastian Giraldo ◽  
Pedro Pablo Vergara ◽  
Juan Camilo Lopez ◽  
Phuong Nguyen ◽  
Nikolaos Paterakis
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Flow Model ◽  
Mixed Integer ◽  
Electrical Distribution Systems ◽  
Optimal Power ◽  
Electrical Distribution ◽  
Three Phase

This paper presents a new linear optimal power flow model for three-phase unbalanced electrical distribution systems considering binary variables. The proposed formulation is a mixed-integer linear programming problem, aiming at minimizing the operational costs of the network while guaranteeing operational constraints. Two new linearizations for branch current and nodal voltage magnitudes are introduced. The proposed branch current magnitude linearization provides a discretization of the Euclidean norm through a set of intersecting planes; while the bus voltage magnitude approximation uses a linear combination of the L1 and the L∞ norm. Results were obtained for an unbalanced distribution system, in order to assess the accuracy of the linear formulation when compared to a nonlinear power flow with fixed power injections, showing errors of less than 4\% for currents and 0.005\% for voltages.

scholarly journals A Mixed Integer Linear Programming Based Load Shedding Technique for Improving the Sustainability of Islanded Distribution Systems

2020 ◽  
Vol 12 (15) ◽  
pp. 6234 ◽  
Author(s):  
Sohail Sarwar ◽  
Hazlie Mokhlis ◽  
Mohamadariff Othman ◽  
Munir Azam Muhammad ◽  
J. A. Laghari ◽  
...  
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Distribution System ◽  
Mixed Integer Linear Programming ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Stability Index ◽  
Load Shedding ◽  
Mixed Integer ◽  
System Frequency

In recent years significant changes in climate have pivoted the distribution system towards renewable energy, particularly through distributed generators (DGs). Although DGs offer many benefits to the distribution system, their integration affects the stability of the system, which could lead to blackout when the grid is disconnected. The system frequency will drop drastically if DG generation capacity is less than the total load demand in the network. In order to sustain the system stability, under-frequency load shedding (UFLS) is inevitable. The common approach of load shedding sheds random loads until the system’s frequency is recovered. Random and sequential selection results in excessive load shedding, which in turn causes frequency overshoot. In this regard, this paper proposes an efficient load shedding technique for islanded distribution systems. This technique utilizes a voltage stability index to rank the unstable loads for load shedding. In the proposed method, the power imbalance is computed using the swing equation incorporating frequency value. Mixed integer linear programming (MILP) optimization produces optimal load shedding strategy based on the priority of the loads (i.e., non-critical, semi-critical, and critical) and the load ranking from the voltage stability index of loads. The effectiveness of the proposed scheme is tested on two test systems, i.e., a 28-bus system that is a part of the Malaysian distribution network and the IEEE 69-bus system, using PSCAD/EMTDC. Results obtained prove the effectiveness of the proposed technique in quickly stabilizing the system’s frequency without frequency overshoot by disconnecting unstable non-critical loads on priority. Furthermore, results show that the proposed technique is superior to other adaptive techniques because it increases the sustainability by reducing the load shed amount and avoiding overshoot in system frequency.

scholarly journals Bi-Level Operation Scheduling of Distribution Systems with Multi-Microgrids Considering Uncertainties

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1441
Author(s):  
Saeid Esmaeili ◽  
Amjad Anvari-Moghaddam ◽  
Erfan Azimi ◽  
Alireza Nateghi ◽  
João P. S. Catalão
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Optimization Problem ◽  
Point Of View ◽  
Mixed Integer ◽  
Wholesale Market ◽  
System Operator ◽  
Level Model ◽  
Upper Level ◽  
Operation Scheduling

A bi-level operation scheduling of distribution system operator (DSO) and multi-microgrids (MMGs) considering both the wholesale market and retail market is presented in this paper. To this end, the upper-level optimization problem minimizes the total costs from DSO’s point of view, while the profits of microgrids (MGs) are maximized in the lower-level optimization problem. Besides, a scenario-based stochastic programming framework using the heuristic moment matching (HMM) method is developed to tackle the uncertain nature of the problem. In this regard, the HMM technique is employed to model the scenario matrix with a reduced number of scenarios, which is effectively suitable to achieve the correlations among uncertainties. In order to solve the proposed non-linear bi-level model, Karush–Kuhn–Tucker (KKT) optimality conditions and linearization techniques are employed to transform the bi-level problem into a single-level mixed-integer linear programming (MILP) optimization problem. The effectiveness of the proposed model is demonstrated on a real-test MMG system.

scholarly journals A Stochastic Model Predictive Control Approach for Joint Operational Scheduling and Hourly Reconfiguration of Distribution Systems

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1884 ◽  
Author(s):  
Saeid Esmaeili ◽  
Amjad Anvari-Moghaddam ◽  
Shahram Jadid ◽  
Josep Guerrero
Keyword(s):  
Linear Programming ◽  
Model Predictive Control ◽  
Stochastic Model ◽  
Predictive Control ◽  
Distribution System ◽  
Distribution Systems ◽  
Mixed Integer ◽  
Practical Implementation ◽  
Wholesale Market ◽  
Stochastic Model Predictive Control

Due to the recent developments in the practical implementation of remotely controlled switches (RCSs) in the smart distribution system infrastructure, distribution system operators face operational challenges in the hourly reconfigurable environment. This paper develops a stochastic Model Predictive Control (MPC) framework for operational scheduling of distribution systems with dynamic and adaptive hourly reconfiguration. The effect of coordinated integration of energy storage systems and demand response programs through hourly reconfiguration on the total costs (including cost of total loss, switching cost, cost of bilateral contract with power generation owners and responsive loads, and cost of exchanging power with the wholesale market) is investigated. A novel Switching Index (SI) based on the RCS ages and critical points in the network along with the maximum number of switching actions is introduced. Due to nonlinear nature of the problem and several existing binary variables, it is basically considered as a Mixed Integer Non-Linear Programming (MINLP) problem, which is transformed into a Mixed Integer Linear Programming (MILP) problem. The satisfactory performance of the proposed model is demonstrated through its application on a modified IEEE 33-bus distribution system.

ON OPTIMAL DESIGN AND EXPANSION OF ELECTRICAL POWER DISTRIBUTION SYSTEMS

2010 ◽  
Vol 19 (01) ◽  
pp. 45-58 ◽  
Author(s):  
SAJAD NAJAFI RAVADANEGH ◽  
ARASH VAHIDNIA ◽  
HOJAT HATAMI
Keyword(s):  
Optimal Design ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Large Scale ◽  
Minimum Spanning Tree ◽  
Optimization Problems ◽  
Distribution Networks ◽  
Coding Method ◽  
Real Size

Optimal planning of large-scale distribution networks is a multiobjective combinatorial optimization problem with many complexities. This paper proposes the application of improved genetic algorithm (GA) for the optimal design of large-scale distribution systems in order to provide optimal sizing and locating of the high voltage (HV) substations and medium voltage (MV) feeders routing, using their corresponding fixed and variable costs associated with operational and optimization constraints. The novel approach presented in the paper, solves hard satisfactory optimization problems with different constraints in large-scale distribution networks. This paper presents a new concept based on MST in graph theory and GA for optimal locating of the HV substations and MV feeders routing in a real-size distribution network. Minimum spanning tree solved with Prim's algorithm is employed to generate a set of feasible population. In the present article, to reduce computational burden and avoid huge search space leading to infeasible solutions, special coding method is generated for GA operators to solve optimal feeders routing. The proposed coding method guarantees the validity of the solution during the progress of the GA toward the global optimal solution. The developed GA-based software is tested in a real-size large-scale distribution system and the well-satisfactory results are presented.

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