This paper presents a mixed-integer second-order cone programing (MISOCP) model to solve the optimal operation problem of radial distribution networks (DNs) with energy storage. The control variables are the active and reactive generated power of dispatchable distributed generators (DGs), the number of switchable capacitor bank units in operation, the tap position of the voltage regulators and on-load tap-changers, and the operation state of the energy storage devices. The objective is to minimize the total cost of energy purchased from the distribution substation and the dispatchable DGs. The steady-state operation of the DN is modeled using linear and second-order cone programing. The use of an MISOCP model guarantees convergence to optimality using existing optimization software. A mixed-integer linear programing (MILP) formulation for the original model is also presented in order to show the accuracy of the proposed MISOCP model. An 11-node test system and a 42-node real system were used to demonstrate the effectiveness of the proposed MISOCP and MILP models.

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Optimal Operation of Distribution Networks Considering Energy Storage Devices

An optimal stochastic energy management system for resilient microgrids

AC load flow based model for transmission expansion planning

This paper presents an approach procedure based on binary bat algorithm (BBA) for solving the transmission system expansion planning (TSEP) problem. The proposed BBA is applied to achieve the comprehensive objective function with the lowest investment and operation costs by finding the optimal distributions of new transmission lines at different operating conditions. The suggested operating conditions are the normal and the contingency such as any single line outage (one by one). The AC optimal power flow (AC-OPF) using MATPOWER is utilized to find the OPF calculations. The proposed BBA is tested on Garver’s 6-bus test system and the west Delta system (WDS) 21-bus as a part of the Egyptian electricity transmission network (EETN) to solve the TSEP problem and the results are compared with other techniques to prove the robustness of the proposed procedure for solving the TSEP problem considering different technical and economic benefits.

Optimal Transmission System Expansion Planning Via Binary Bat Algorithm

Due to the increasing penetration of large-scale renewable energy generation at transmission level, hybrid AC/DC transmission expansion is becoming more relevant by the day, especially if the considered renewable generation is far away from existing AC grid infrastructure. This paper presents a multi-period hybrid AC/DC network expansion planning model that incorporates node voltages, reactive power and network losses. Since the operation of a high voltage DC link is influenced considerably by the converter stations, converter transformer, filter, and phase reactor are modeled in each converter station. Since the AC power flow equations render a non-convex problem whose solution algorithms do not always guarantee convergence or optimality, a second-order conic relaxation is utilized. The resulting model is a mixed-integer convex problem with a convergence guarantee that embodies a better approximation of system operation than its DC linear counterpart. Three case studies are considered to illustrate the proposed model. 

Multi-Period AC/DC Transmission Expansion Planning Including Shunt Compensation

The Transmission Expansion Planning (TEP) problem is not a new issue, however, most research works presented so far use DC modeling, which can lead to very unrealistic transmission expansion plans. In order to deal with this problem, the use of the AC network model has been proposed recently by very few research works. Solving the TEP using the AC model is an extremely difficult task to deal with. Achieving this task is becoming more important due to the complexity of smart grids. In this work, it is proposed an approach to solve the TEP problem using the AC model and taking into account the (N-1) security assessment criterion. This new approach is based on a new full AC formulation, which takes into account contingencies. The optimization tool used to solve the problem is Differential Evolution (DE) and some tests are performed using the Garver 6-bus test system.

Security constrained transmission expansion planning for smart transmission grids based on the AC network model

In this paper, two algorithms for solving the problem of operation planning of electric power distribution systems are presented. This problem consists in defining the values of a set of continuous and discrete control variables to obtain better system performance. Given the large number of possible combinations of the settings of the control variables, the problem presents combinatorial explosion. To work around it, two procedures are proposed. In the first one, the genetic algorithm developed by Chu and Beasley (GACB) is used with a special mechanism of creation of the initial population. In the second procedure, a simplified algorithm which is capable of obtaining good quality solutions at a much lower computational time complexity than GACB is proposed. The results for the 34- and 70-bus IEEE test systems show that the proposed algorithms are promising.

Algorithms for Operation Planning of Electric Distribution Networks

Significant technological advances in the electric sector have led to complexity increase and created new challenges to transmission expansion planners. On the one hand, the increasing penetration of renewable energy sources impacts the entire network. On the other hand, DC systems have become a favorable and viable option to link some of these sources of energy to the consumer centers. Thus, new models of the network equipment must be incorporated to the Transmission Expansion Planning (TEP) model to take such changes into account in a more accurate way. This research work aims to include AC and multi-terminal DC transmission lines as candidates in the expansion planning process. The AC network model is used and shunt compensation is also taken into account to allow more flexibility to the expansion options. The TEP problem is solved using a combination of nonlinear programming and differential evolution (DE). The results obtained using a 9-bus test network and a modified IEEE-118 bus show the feasibility of this approach.

Integrated AC/DC transmission expansion planning model considering VSC-MTDC systems

Unified AC Transmission Expansion Planning Formulation incorporating VSC-MTDC, FACTS devices, and Reactive Power compensation

With the increasing power generation from the wind, safe operation is a constant concern for wind turbine engineering and manufacturers. Within this scenario are important studies on lightning strikes protection for generators and wind turbine blades. Thus, this work analyzed the interaction between the electric field generated by lightning strikes and two different protection models of wind turbines using computer simulations. Furthermore, simulations are conducted with a complete model of wind generator, analyzing the performance of the receptor for different blades angles. Based on the electric field intensity, the results obtained show the performance of two protection models, verifying whether the lightning is more likely to hit the blade or its protection device. In the complete model, it is possible to observe the difference in the interaction of the electric field when three blades are installed in a turbine.

Ricardo A. de Araujo

Papers

Security constrained transmission expansion planning for smart transmission grids based on the AC network model

Algorithms for Operation Planning of Electric Distribution Networks

Integrated AC/DC transmission expansion planning model considering VSC-MTDC systems

Unified AC Transmission Expansion Planning Formulation incorporating VSC-MTDC, FACTS devices, and Reactive Power compensation

Interaction Between Different Lightning Protection Models for Wind Turbine Blades Under a High-Intensity Electric Field