A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid particle swarm optimisation (PSO) is proposed. The obj...
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A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid particle swarm optimisation (PSO) is proposed. The objective is to minimise comprehensive cost, consisting of power loss and operation cost of transformers and capacitors, and subject to constraints such as minimum and maximum reactive power limits of distributed generators, maximum deviation of bus voltages and maximum allowable daily switching operation number. PSO is used to solve the corresponding mixedinteger non-linear programmingproblem and the hybrid PSO (HPSO) method, consisting of three PSO variants, is presented. In order to mitigate the local convergence problem, fuzzy adaptive inference is used to improve the searching process and the final fuzzy adaptive inference-based HPSO is proposed. The proposed algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33-node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods.
The reactive power coordinated optimisation problem for distribution network (DN) with the integration of renewable distributed generation (DG) is investigated in this study. By actively participating in reactive powe...
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The reactive power coordinated optimisation problem for distribution network (DN) with the integration of renewable distributed generation (DG) is investigated in this study. By actively participating in reactive power control together with an under-load tap changer and shunt capacitors, DG can operate more effectively in the DN. Non-dispatchable DG is considered in the coordinated optimisation method. The objective of the proposed reactive power coordinated optimisation method is to minimise active power loss and to decrease the number of switching device operations while maintaining the grid voltage within the allowable range. The optimisation problem is to solve a variable combination including integers and continuous variables, which will formulate a mixedinteger non-linear programming (MINLP) problem. The control variable includes operations of traditional reactive power control devices and the reactive power adjustments of DGs. To solve the MINLP problem, a heuristic searching method, an improved harmony search algorithm is proposed with adaptive parameters process. Numerical tests on a standard 10-kV distribution system and a real distribution system demonstrate the applicability of the proposed reactive power coordinated optimisation method.
This study discusses a security-constrained unit commitment (SCUC) based optimal power tracing approach, which adopts the proportional power tracing method to trace power flows of the network for simultaneously satisf...
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This study discusses a security-constrained unit commitment (SCUC) based optimal power tracing approach, which adopts the proportional power tracing method to trace power flows of the network for simultaneously satisfying physical contract paths and financial contract quantities of bilateral transactions. Thus, optimal solutions of the proposed model, including unit commitment and generation dispatch of generators and angle statuses of phase shifters, would simultaneously meet physical and financial requirements of bilateral transactions, and in turn reduce the impacts of loop flows induced by bilateral transactions to third parties of the networked system. The proposed model is a mixedinteger non-linear programmingproblem because of the non-linear proportional power tracing constraints, and the revised outer approximation algorithm is discussed to effectively solve the problem. The effectiveness of the proposed model is further evaluated via an integrated power-money flow analysis, based on the locational marginal price based energy payments and the min-max fairness policy based transmission usage charges. Numerical case studies show that the proposed model, as compared with traditional financial bilateral transaction models, presents potential advantages to avoid loop flows and reduce the impacts to third parties in terms of energy and transmission usage payments.
In this study, the authors examine resource allocation in an orthogonal frequency-division multiple-access-based cognitive radio (CR) network which dynamically senses primary users (PUs) spectrum and opportunistically...
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In this study, the authors examine resource allocation in an orthogonal frequency-division multiple-access-based cognitive radio (CR) network which dynamically senses primary users (PUs) spectrum and opportunistically uses available channels. The aim is resource allocation such that the CR network throughput is maximised under the PUs maximum interference constraint and cognitive users (CUs) transmission power budget. This problem is formulated as a mixed-integer non-linear programmingproblem which is MATHEMATICAL SCRIPT CAPITAL NP-hard in general and infeasible to solve in real-time. To reduce the computational complexity, the authors decouple the problem into two separate steps. After initial power allocation, in the first step, an adaptive algorithm is employed to assign subcarriers to the CUs toward throughput maximisation by using these initial powers. In the second step, power is allocated optimally to the assigned subcarriers. Simulation results show that the proposed method nearly achieves the optimal solution in a small number of iterations meaning significant reduction in the computational complexity.
This study proposes the use of a non-linear branch-and-bound (B&B) algorithm to solve the reactive power dispatch and planning problem of an electrical power system. The problem is formulated as a mixedinteger no...
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This study proposes the use of a non-linear branch-and-bound (B&B) algorithm to solve the reactive power dispatch and planning problem of an electrical power system. The problem is formulated as a mixedinteger non-linear programming (MINLP) problem. The MINLP is relaxed resulting in a set of non-linear programming (NLP) problems, which are solved at each node of the B&B tree through a primal dual-interior point algorithm. The non-linear B&B algorithm proposed has special fathoming criteria to deal with non-linear and multimodal optimisation models. The fathoming tests are redefined, adding a safety margin value to the objective function of each NLP problem before they are fathomed through the objective function criteria, avoiding convergence to local optimum solutions. The results are presented using three test systems from the specialised literature. The B&B algorithm found several optimum local solutions and the best solution was found after solving some NLP problems, with little computational effort.
A coordinated look-ahead reactive power optimisation method is proposed to minimise the required number of operating control devices for a time horizon of 24h. The aim is to determine, via solving a mixedinteger non-...
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A coordinated look-ahead reactive power optimisation method is proposed to minimise the required number of operating control devices for a time horizon of 24h. The aim is to determine, via solving a mixedinteger non-linear programming (MINLP) problem, optimum value settings of transformer taps, capacitor banks and reactive power output of distributed generators (DGs) based on the day-ahead load demand and active power output of DGs satisfying the engineering and operational constraints. The proposed method employs a three-stage method: assessment stage, time-period-partitioning stage, and coordinated reactive power optimisation stage. The first stage assesses the hourly voltage profile and available delivery capability margin of the system, while the time-period-partitioning stage uses clustering algorithm based on power-flow solution to partition time periods into coherent time durations. The MINLP problem is solved in the proposed coordinated optimisation stage. A modified IEEE13 case and IEEE123 case are used to verify the effectiveness of the proposed three-stage method.
This study proposes the convex model for active distribution network expansion planning integrating dispersed energy storage systems (DESS). Four active management schemes, distributed generation (DG) curtailment, dem...
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This study proposes the convex model for active distribution network expansion planning integrating dispersed energy storage systems (DESS). Four active management schemes, distributed generation (DG) curtailment, demand side management, on-load tap changer tap adjustment and reactive power compensation are considered. The optimisation of DESS for peak shaving and operation cost decreasing is also integrated. The expansion model allows alternatives to be considered for new wiring, new substation, substation expansion and DG installation. The distribution network expansion planning (DNEP) problem is a mixedinteger non-linear programmingproblem. Active management and uncertainties especially with the DG integration make the DNEP problem much complex. To find the suitable algorithm, this study converts the DNEP problem to a second-order cone programming model through distflow equations and constraints relaxation. A modified 50-bus application example is used to verify the proposed model.
A new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach is presented. The objective minimises power losses, balancing...
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A new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach is presented. The objective minimises power losses, balancing load among feeders and subject to constraints such as capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. A variant of the generalised Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages;the first one is the master problem and is formulated as a mixedinteger non-linear programmingproblem. This stage determines the radial topology of the distribution network. The second stage is the slave problem and is formulated as a non-linear programmingproblem. This stage is used to determine the feasibility of the master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS mathematical modelling language. The effectiveness of the proposal is demonstrated through two examples extracted from the specialised literature.
Security constrained optimal transmission switching (SC-OTS) can be an essential part of future smart grids with flexible topologies. Transmission switching, however, can have adverse impact on generators because of c...
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Security constrained optimal transmission switching (SC-OTS) can be an essential part of future smart grids with flexible topologies. Transmission switching, however, can have adverse impact on generators because of creating excessive torque on their rotor shafts. In this study, SC-OTS as an effective tool is applied to relieve congestion while considering AC constraints and generator rotor shaft impact caused by switching. As opposed to previously used simplified models based on standing phase angle, this study utilises dynamic response of generators to accurately calculate the actual stresses on rotors because of switching. In addition, network N-1 security criterion is taken into account. In the proposed model, OTS actions are obtained through a bi-level process. In the upper level, OTS set is determined and the applicability of each action is checked in the lower level. The proposed methodology leads to a mixedinteger non-linear programmingproblem, which is formulated and solved based on Benders decomposition. Test results for the IEEE 57 and 118-bus systems illustrate the effectiveness of the method in removing congestion while ensuring that destructive switching manoeuvres are avoided.
This study presents an optimisation model to achieve an optimal voltage sag monitoring programme. To cover the main uncertainty associated with fault impedance, a novel approach termed as probabilistic monitor reach a...
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This study presents an optimisation model to achieve an optimal voltage sag monitoring programme. To cover the main uncertainty associated with fault impedance, a novel approach termed as probabilistic monitor reach area (PMRA) is developed. Moreover, PMRA is employed to consider reliability of the monitoring equipment impact. Additionally, several indices based on PMRA are defined to distinguish the optimal programme when outage of generators, loading level, line outage and feeder reconfiguration may result in several programmes. Besides, the other advantage of the proposed method is aptitude of modelling large load switching as an influential source of voltage sags. The model determines the number and the location of monitors in such a way that a pre-defined probability of observability is satisfied. Capability of the proposed methodology is checked for several test systems and illustrated here on the 24-bus reliability test system and on the 34-node test feeder. Numerical results and their comparison with the commonly used MRA method reveal that the proposed optimal voltage sag monitoring programme is robust against uncertainties including fault impedance, load variations and outage of the generators/lines.
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