Mixed-Integer SDP Relaxation-based Volt/Var Optimization for Unbalanced Distribution Systems

Author(s):  
Ibrahim Alsaleh ◽  
Lingling Fan ◽  
Minyue Ma
Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3783
Author(s):  
Mateusz Andrychowicz

The paper shows a method of optimizing local initiatives in the energy sector, such as energy cooperatives and energy clusters. The aim of optimization is to determine the structure of generation sources and energy storage in order to minimize energy costs. The analysis is carried out for the time horizon of one year, with an hourly increment, taking into account various RES (wind turbines (WT), photovoltaic installations (PV), and biogas power plant (BG)) and loads (residential, commercial, and industrial). Generation sources and loads are characterized by generation/demand profiles in order to take into account their variability. The optimization was carried out taking into account the technical aspects of the operation of distribution systems, such as power flows and losses, voltage levels in nodes, and power exchange with the transmission system, and economic aspects, such as capital and fixed and variable operating costs. The method was calculated by sixteen simulation scenarios using Mixed-Integer Linear Programming (MILP).


Author(s):  
Mostafa Elshahed ◽  
Mahmoud Dawod ◽  
Zeinab H. Osman

Integrating Distributed Generation (DG) units into distribution systems can have an impact on the voltage profile, power flow, power losses, and voltage stability. In this paper, a new methodology for DG location and sizing are developed to minimize system losses and maximize voltage stability index (VSI). A proper allocation of DG has to be determined using the fuzzy ranking method to verify best compromised solutions and achieve maximum benefits. Synchronous machines are utilized and its power factor is optimally determined via genetic optimization to inject reactive power to decrease system losses and improve voltage profile and VSI. The Augmented Lagrangian Genetic Algorithm with nonlinear mixed-integer variables and Non-dominated Sorting Genetic Algorithm have been implemented to solve both single/multi-objective function optimization problems. For proposed methodology effectiveness verification, it is tested on 33-bus and 69-bus radial distribution systems then compared with previous works.


2019 ◽  
Vol 9 (2) ◽  
pp. 1-16
Author(s):  
Vannak Vai ◽  
Marie-Cécile Alvarez-Hérault ◽  
Long Bun ◽  
Bertrand Raison

This paper studies an optimal design of grid topology and integrated photovoltaic (PV) and centralized battery energy storage considering techno-economic aspect in low voltage distribution systems for urban area in Cambodia. This work aims at searching for an optimal topology including size of the battery energy storage by two different methods over the planning study of 15 years. Firstly, the shortest path algorithm (SPA) and first-fit bin-packing algorithm (FFBPA) are used to find out the topology which minimize the line and the load balancing. Secondly, mixed integer quadratically constrained programming (MIQCP) algorithms are developed to search for a topology which minimize conductor use and the load balancing improvement. Next, Genetic algorithm is developed to size the maximum PV peak power connected into LV network with respected to voltage and current constraints. Then, the size of battery energy storage procedure is established in order to eliminate the reverse power flow going on medium voltage (MV) grid and to improve the autonomous operation time of system. A discounted cost method is used to evaluate the solutions for different methods. Lastly, an urban area in Cambodia is chosen as a case study in this paper. Simulation results confirm the proposed method in this research.


Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3399 ◽  
Author(s):  
Marco Cruz ◽  
Desta Fitiwi ◽  
Sérgio Santos ◽  
Sílvio Mariano ◽  
João Catalão

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.


2014 ◽  
Vol 15 (5) ◽  
pp. 457-469 ◽  
Author(s):  
Mojtaba Khederzadeh ◽  
Mohammad Khalili

Abstract Given that the microgrid concept is the building block of future electric distribution systems and electrical vehicles (EVs) are the future of transportation market, in this paper, the impact of EVs on the performance of microgrids is investigated. Demand-side participation is used to cope with increasing demand for EV charging. The problem of coordination of EV charging and discharging (with vehicle-to-grid (V2G) functionality) and demand response is formulated as a market-clearing mechanism that accepts bids from the demand and supply sides and takes into account the constraints put forward by different parts. Therefore, a day-ahead market with detailed bids and offers within the microgrid is designed whose objective is to maximize the social welfare which is the difference between the value that consumers attach to the electrical energy they buy plus the benefit of the EV owners participating in the V2G functionality and the cost of producing/purchasing this energy. As the optimization problem is a mixed integer nonlinear programming one, it is decomposed into one master problem for energy scheduling and one subproblem for power flow computation. The two problems are solved iteratively by interfacing MATLAB with GAMS. Simulation results on a sample microgrid with different residential, commercial and industrial consumers with associated demand-side biddings and different penetration level of EVs support the proposed formulation of the problem and the applied methods.


2020 ◽  
Vol 12 (15) ◽  
pp. 6234 ◽  
Author(s):  
Sohail Sarwar ◽  
Hazlie Mokhlis ◽  
Mohamadariff Othman ◽  
Munir Azam Muhammad ◽  
J. A. Laghari ◽  
...  

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.


Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1441
Author(s):  
Saeid Esmaeili ◽  
Amjad Anvari-Moghaddam ◽  
Erfan Azimi ◽  
Alireza Nateghi ◽  
João P. S. Catalão

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.


Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1884 ◽  
Author(s):  
Saeid Esmaeili ◽  
Amjad Anvari-Moghaddam ◽  
Shahram Jadid ◽  
Josep Guerrero

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.


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