Eloy Díaz-Dorado

An improved branch-exchange algorithm for large-scale distribution network planning

Design of optimal layout for medium-voltage (MV) power networks is a common issue in electrical distribution planning. Technical constraints (radial structure, voltage drops, and equipment capacity) and reliability limits must be fulfilled. The function for minimizing includes investments, power losses, and quality of supply costs. We present an improved algorithm based on a branch exchange technique to solve large-scale problems. A heuristic algorithm for solving a Euclidean Steiner problem is used to improve the network by including transshipment nodes.

Influence of the shadows in photovoltaic systems with different configurations of bypass diodes

The IU characteristic curve of a photovoltaic module is affected by shadows, depending on the shaded area of the PV module, and the radiation received by the shaded areas. Another factor in the shape of the I-V curve of a PV module, is the configuration of the electrical connection between its cells and bypass diodes. Bypass diodes are installed in the modules to prevent power consumption when they are shaded or damaged; they also prevent cells from working near the avalanche zone. This paper examines the performance of a photovoltaic array. A PV array consists of modules connected between them. Particularly, the configuration with bypass diodes overlapped is analysed, showing that totally or partially shaded modules can consume some of the power generated by other modules of the PV array. This effect is also present in low power PV arrays. In these cases, the power dissipated by a diode is small; but if there are many diodes, the power dissipated by all the diodes can be comparable with the power produced by various PV modules. Additionally, this article deals with the influence of the inverter in the MPP tracking.

Planning of large rural low-voltage networks using evolution strategies

This paper presents a method based on evolution strategies for designing large rural low-voltage (LV) distribution networks. Planning rural LV distribution networks involves radial configuration design, location of medium-voltage/low-voltage substations, and minimum cost. In this work, these goals are considered by taking into account different conductors, voltage drop and conductor capacity constraints, power losses in lines, and deterministic loads. The algorithms developed in this paper are based on evolution strategies (ES) and were implemented on large-scale rural LV distribution networks, but they could also be used in general network optimization.

Optimal planning of unbalanced networks using dynamic programming optimization

This paper presents a method based on dynamic programming optimization to design distribution and industrial networks with unbalanced customers. Low-voltage and medium-voltage network customers can be three-phase (i.e., industrial and commercial) and single-phase (e.g,. residential and rural areas). Moreover, American medium-voltage distribution networks have single-phase lines (rural areas) and three-phase lines (urban and primary feeders). Optimization of an unbalanced network implies optimal assignation of single-phase customers to each phase. This works considers different conductor types, tapering, power losses in lines, capacity and voltage drop constraints and deterministic loads, all employing single-phase and three-phase lines. The necessary modifications to apply it by single-wire earth return systems is presented.

Design of Large Rural Low-Voltage Networks Using Dynamic Programming Optimization

The purpose of this paper is to establish algorithms in the design of rural low-voltage (lv) distribution networks. Planning of rural lv distribution networks involves the optimal design of radial configuration and location of mv/lv substations considering cost functions. In this work both goals are considered by taking into account different conductors, voltage drop constraints, power losses in lines, and deterministic loads. The algorithms developed in this paper are based on dynamic programming and were implemented on large-scale rural lv distribution networks, but they could also be used for other network optimization.

An application of an evolution strategy in power distribution system planning

The optimal location and sizing of power distribution substations and feeder layouts is a common problem in new expansion planning. This paper is an application of a type of evolutionary algorithm called an evolution strategy (ES), to obtain optimal locations and sizes for power distribution substations such that the demand is met at minimum cost. The cost function for minimization includes substation investments, medium-voltage network costs and power losses.

Estimation of energy losses in a Wind Park

The study of energy losses in any electric installation is closely related to energy efficiency. Its calculation depends on the number and the quality of the available electrical measurements. Typically, every wind park has electrical measurements in all its wind turbines and its HV point of connection. However, it is difficult to calculate in an easy way these losses due to problems like redundancy, inaccuracy, lack of data, etc. A state estimation (SE) method will be proposed in this article, in order to calculate the power losses. By means of available measurements (power, voltage, current...) and parameters of the network (cables, transformers...), the losses taking place in each element can be obtained. SE also allows detecting errors in measurement and calculating the wind park state when certain measurement equipments are unavailable. Wind speed measurements are used to get pseudo-measurement if necessary and to filter errors. Finally, an economic study will be done taking into account the different ways of selling wind energy in the Spanish network. Consequently, the economic importance of losses will be evaluated too. The location of this project is The Sotavento Wind Park, Serra da Loba, Spain. The results shown throughout this article have been applied there with the aim of analysing its energy efficiency.

Evolutive algorithm to optimize the power flow in a network using series compensators

The actual lines have many operation problems like oscillations, a important reactive power flow in the lines… other kind of problems are the planification of the network (power of the generators, reactive power flow in the lines…) or the bad distribution of the power flow in the lines of the network, for example one line overloaded and the other lines below their nominal power, this case happens, for example, in a network when a line falls. Many techniques have been used to solve this second type of problems, actually techniques based in the evolution and natural selection (like genetic algorithms or evolutionary algorithms) are being used combined with electronic equipment. The FACTS are a good electronic equipment to be used in these problems, because the converter can stay in bypass until a line falls, in this moment the converter can be used to solve the problem. The line impedance can be changed using SSSC converters, because they can inject a voltage in quadrature with the line current, so the effect of the converter is a capacitive or a inductive reactance in series with the line impedance. This paper presents an evolutive algorithm that solves the problem of placing SSSC converters in a network to optimize the power flow across all the lines of those network, minimizing the total installed power. The number of converters to be placed and their power will be chosen by the algorithm too.

Coordinated reactive compensation in a Wind Park

In wind energy, an incentive payment related to the reactive power compensation is applied. In the past, the maximum incentive was achieved when the cos phi, that was calculated as a monthly mean, was almost unitary (cos phi = 1.00). The payment is a percentage of the average reference tariff (ART). Since the 1st of January 2007, the Spanish regulation RD 436 /2004 has modified the incentive payment. Nowadays, it is calculated each 15 minutes from the energy during this period, and its maximum value depends on the achievement of a objective power factor (cos phi) which is defined in three time frames: peak hours (cos phi < 0,95 cap.), valley hours (cos phi < 0.95 ind.) and flat hours (cos phi = 1.00). To maximize the incentive payment, in the Sotavento Experimental Wind Park (Spain) a configuration with a central controller that coordinates the actuation over all the capacitor steps in the wind park has been installed. In this article, a central controller algorithm which is based on a dynamic programming is proposed. Its main objectives are: to maximize the incentive payment, or achieve the equivalent objective PF, and to minimize the number of connection operations over the capacitor steps (especially those in substation). At the present time, the algorithm is being tested in the wind park.

Evolutive algorithm for power flow optimization

The actual lines have many operation problems like power flow distribution, oscillations, etc. A bad power flow distribution on the network lines appears for example during a fault, in this case is possible that some lines of the network would be overloaded and other lines under their thermal value. A possible solution of the problem is using series compensators to redistribute the power flow, the converters are bypassed until the fault appears and after this, it start to compensate. Evolutive algorithms can solve the problem of the ubication in the network of these converters and to chose the power of it too, minimizing the total installed power to make that power flow redistribution. This paper presents an evolutive algorithm that solves the problem of placing SSSC converters in a network to optimize the power flow across all the lines of those network, minimizing the total installed power when a line of the network falls. The number of converters to be placed and their power will be chosen by the algorithm too.