A novel load transfer scheme for peak load management in rural areas

This paper proposes a novel peak load management scheme for rural areas. The scheme transfers certain customers onto local nonembedded generators during peak load periods to alleviate network under voltage problems. This paper develops and presents this system by way of a case study in Central Queensland, Australia. A methodology is presented for determining the best location for the nonembedded generators as well as the number of generators required to alleviate network problems. A control algorithm to transfer and reconnect customers is developed to ensure that the network voltage profile remains within specification under all plausible load conditions. Finally, simulations are presented to show the performance of the system over a typical maximum daily load profile with large stochastic load variations.

Intelligent distribution planning and control incorporating microgrids

This paper proposes a comprehensive approach to the planning of distribution networks and the control of microgrids. Firstly, a Modified Discrete Particle Swarm Optimization (MDPSO) method is used to optimally plan a distribution system upgrade over a 20 year planning period. The optimization is conducted at different load levels according to the anticipated load duration curve and integrated over the system lifetime in order to minimize its total lifetime cost. Since the optimal solution contains Distributed Generators (DGs) to maximize reliability, the DG must be able to operate in islanded mode and this leads to the concept of microgrids. Thus the second part of the paper reviews some of the challenges of microgrid control in the presence of both inertial (rotating direct connected) and non-inertial (converter interfaced) DGs. More specifically enhanced control strategies based on frequency droop are proposed for DGs to improve the smooth synchronization and real power sharing minimizing transient oscillations in the microgrid. Simulation studies are presented to show the effectiveness of the control.

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

Economía política de la planificación de los sectores agrícola y rural en las sociedades del Caribe = Polítical economy of agricultural and rural sector planning in Caribbean societies

Incluye Bibliografía

Unmasking problems in rural health planning /

Mode of access: Internet.

Optimization of long rural feeders using a genetic algorithm

This paper describes the optimization of conductor size and the voltage regulator location & magnitude of long rural distribution lines. The optimization minimizes the lifetime cost of the lines, including capital costs and losses while observing voltage drop and operational constraints using a Genetic Algorithm (GA). The GA optimization is applied to a real Single Wire Earth Return (SWER) network in regional Queensland and results are presented.

Effectiveness of reactive power capability of photo voltaic inverters to maintain voltage profile in a residential distribution feeder

Large penetration of rooftop PVs has resulted in unacceptable voltage profile in many residential distribution feeders. Limiting real power injection from PVs to alleviate over voltage problem is not feasible due to loss of green power and hence corresponding revenue loss. Reactive capability of the PV inverter can be a solution to address over voltage and voltage dip problems to some extent. This paper proposes an algorithm to utilize reactive capability of PV inverters and investigate their effectiveness for voltage improvement based on R/X ratio of the feeder. The length and loading level of the feeder for a particular R/X ratio to have acceptable voltage profile is also investigated. This can be useful for suburban design and residential distribution planning. Furthermore, coordination among different PVs using residential smart meters via a substation based controller is also proposed.

Effectiveness of reactive power capability of photo voltaic inverters to maintain acceptable voltage profile in a residential distribution system

Integration of rooftop PVs and increasing peak demand in the residential distribution networks has resulted in unacceptable voltage profile. Curtailing PV generation to alleviate overvoltage problem and making regular network investment to cater peak demand is not always feasible. Reactive capability of the PV inverter can be a solution to address voltage dip and over voltage problems to some extent. This paper proposes an algorithm to utilize reactive capability of PV inverters and investigate their effectiveness on feeder length and R/X ratio of the line. Feeder loading level for a particular R/X ratio to have acceptable voltage profile is also investigated. Furthermore, the need of appropriate feeder distances and R/X ratio for acceptable voltage profile, which can be useful for suburban design and distribution planning, is explored.

Planning of secondary distribution circuits through evolutionary algorithms

In this work, the planning of secondary distribution circuits is approached as a mixed integer nonlinear programming problem (MINLP). In order to solve this problem, a dedicated evolutionary algorithm (EA) is proposed. This algorithm uses a codification scheme, genetic operators, and control parameters, projected and managed to consider the specific characteristics of the secondary network planning. The codification scheme maps the possible solutions that satisfy the requirements in order to obtain an effective and low-cost projected system-the conductors' adequate dimensioning, load balancing among phases, and the transformer placed at the center of the secondary system loads. An effective algorithm for three-phase power flow is used as an auxiliary methodology of the EA for the calculation of the fitness function proposed for solutions of each topology. Results for two secondary distribution circuits are presented, whereas one presents radial topology and the other a weakly meshed topology. © 2005 IEEE.

Integrated planning of electric power distribution networks

In this work, a heuristic model for integrated planning of primary distribution network and secondary distribution circuits is proposed. A Tabu Search (TS) algorithm is employed to solve the planning of primary distribution networks. Evolutionary Algorithms (EA) are used to solve the planning model of secondary networks. The planning integration of both networks is carried out by means a constructive heuristic taking into account a set of integration alternatives between these networks. These integration alternatives are treated in a hierarchical way. The planning of primary networks and secondary distribution circuits is carried out based on assessment of the effects of the alternative solutions in the expansion costs of both networks simultaneously. In order to evaluate this methodology, tests were performed for a real-life distribution system taking into account the primary and secondary networks.

Short-term planning of electric power distribution networks using multiobjective genetic algorithim

The high active and reactive power level demanded by the distribution systems, the growth of consuming centers, and the long lines of the distribution systems result in voltage variations in the busses compromising the quality of energy supplied. To ensure the energy quality supplied in the distribution system short-term planning, some devices and actions are used to implement an effective control of voltage, reactive power, and power factor of the network. Among these devices and actions are the voltage regulators (VRs) and capacitor banks (CBs), as well as exchanging the conductors sizes of distribution lines. This paper presents a methodology based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II) for optimized allocation of VRs, CBs, and exchange of conductors in radial distribution systems. The Multiobjective Genetic Algorithm (MGA) is aided by an inference process developed using fuzzy logic, which applies specialized knowledge to achieve the reduction of the search space for the allocation of CBs and VRs.

Multiobjective short-term planning of electric power distribution systems using NSGA-II

This paper presents a mixed integer nonlinear programming multiobjective model for short-term planning of distribution networks that considers in an integrated manner the following planning activities: allocation of capacitor banks; voltage regulators; the cable replacement of branches and feeders. The objective functions considered in the proposed model are: to minimize operational and investment costs and minimize the voltage deviations in the the network buses, subject to a set of technical and operational constraints. A multiobjective genetic algorithm based on a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve this model. The proposed mathematical model and solution methodology is validated testing a medium voltage distribution system with 135 buses. © 2013 Brazilian Society for Automatics - SBA.

Load frequency control for rural distributed generation

In rural low-voltage networks, distribution lines are usually highly resistive. When many distributed generators are connected to such lines, power sharing among them is difficult when using conventional droop control, as the real and reactive power have strong coupling with each other. A high droop gain can alleviate this problem but may lead the system to instability. To overcome4 this, two droop control methods are proposed for accurate load sharing with frequency droop controller. The first method considers no communication among the distributed generators and regulates the output voltage and frequency, ensuring acceptable load sharing. The droop equations are modified with a transformation matrix based on the line R/X ration for this purpose. The second proposed method, with minimal low bandwidth communication, modifies the reference frequency of the distributed generators based on the active and reactive power flow in the lines connected to the points of common coupling. The performance of these two proposed controllers is compared with that of a controller, which includes an expensive high bandwidth communication system through time-domain simulation of a test system. The magnitude of errors in power sharing between these three droop control schemes are evaluated and tabulated.