Research On System State Characterization And Application To Dynamic Optimization For Distribution Networks

Time-process oriented theory has great significance to promote technological development of distribution network analysis and control method and introduce a new breakthrough point for the related basic theoretical fields. Usually, the traditional energy loss computation in electrical networks demands for numerous metered data and great amount of computational time when the accurate energy loss evaluation is required. On the other hand, electrical network is a wide-area fast dynamic system in engineering practice, so conventional feedback control methods based on the time-point information are impossible to solve such a typical problem, that is control variables usually can not respond to all system operation states at each time point following the changed load, considering some potential economic or security constraints. Furthermore, the time-process oriented control approach can also be used to solve such contradiction: most human-involved decision-makings for system operating manners cannot be made quickly, but the system state is continually changing rapidly and demands instant responses from the control center. Therefore, solving the time-process oriented control problem is particularly significant because making a real-time control scheme is extremely unlikely in most cases even if all the information we need is probably available today. It is necessary to introduce the time-process oriented theory into the distribution network analysis and control fields so that the core objective of power system operation can be further achieved in a more secure, more reliable, higher quality and more economical way. This paper presents a concept of system process state characterization to deal with the huge dynamic information heaps. As we know, the common time-domain analysis method based on information at a certain point in time will neglect the relationship among contiguous time series, and corresponding computational efforts upon each point in time will become more unacceptable when more time series information is offered. So, the concept of system state characterization can help people avoid performing power flow calculations for every interval of the load curves and finish the endless tolerance of the iterative procedures, because its idea successfully converts the complex dynamic optimization problem into a relatively simple static optimization problem. The whole process of system behavior could be optimized simultaneously while the characteristic state is optimized by some approaches such as capacitor placement and network reconfiguration.Firstly, this paper introduces a novel concept about time-series fusion, and develops the sensitivity relationship model between the network energy loss and load curve based on the conception of system process state characterization, and establishes a new energy loss formula for electrical networks. In this formula, electric components'energy losses in a given duration are divided into three parts. The primary energy losses can be quantified by the power flow calculation with average loads at nodes, and its linear and quadratic correction value can be produced by using an approximate algorithm whose accuracy is determined by the current system's actual measurement configuration. The categorization of load nodes according to the type of installed measurements further improves the adaptability of this algorithm and makes it suitable for networks with incomplete measurements as well as those advanced networks with modern measurements.Secondly, this paper takes the network energy loss as a major economic indicator to construct a dynamic capacitor placement and switching control principle on the premise of security restriction. Considering the mathematical model for dynamic capacitor placement and switching control is similar in nature, these two issues are combined for discussion in this paper. In most cases, the control scheme of capacitor placement will be made out of the following considerations: Subject to some security and economic factors, the installation number, location and type of capacitors can not be changed without restraint, and that means control variables should not be adjusted too often. However, since loads change on an hourly basis or even shorter, the optimal number, location and size of capacitors or even the network configuration may change accordingly in order to achieve the greatest energy conservation. Consequently, the action number of discrete control system makes the original reactive power optimal problem strong-coupling in time and space, which significantly increases complexity for direct solution. So the proposed method in this paper take the maximum energy saving as major objective in which the regulating costs of control variables are also converted into the forms of energy loss, and a optimal static control scheme of capacitor placement can be made in a given period. On this basis, time series fusion algorithm will provide the suitable sub-time dividing scheme so that the whole time interval of dynamic optimal control solution series will be obtained. Specifically, multi-node capacitor dynamic switching problem is decomposed into a series of single-node capacitor dynamic switching subproblem in this paper so as to simplify the process of time series fusion, and then the problem will be solved in an iteration manner.Thirdly, this paper presents static and dynamic distribution network reconfiguration algorithms based on time interval according to the conception of system process state characterization. In the optimization process, based on sensitivity analysis, loop-analysis and superimpose theorem, opening a tie switch is equivalent to superimposing an electric current source on the loop. Consequently, the computational effort required in solving such large-scale dynamic optimization problems is decreased greatly by converting the original problems into some simpler static optimization problems with appropriate linearization and stepwise correction idea. For dynamic reconfiguration, in considering the load changes in engineering practice, the mathematic model takes the minimum energy loss as the objective in which the regulating costs of control variables is also converted into the forms of energy loss. Therefore, depondeing on the traditional mathematical programming method combined with the modern intelligent algorithm, time series fusion algorithm can determine the optimal network struction in the each subsection and finally obtain the optimal switches control operation series required for dynamic network reconfiguration plan.Finally, this paper proposes a distribution network comprehensive optimization to solve capacitor switching and network reconfiguration problem at same time based on system process state characterization. In the method, minimum energy loss combined with predefined index for load balance is taken as objective, and an alternating iteration algorithm is proposed in the paper to improve the effect of comprehensive optimization. The experiment has worked out satisfactorily.