Chanan Singh

The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee

This report describes an enhanced test system (RTS-96) for use in bulk power system reliability evaluation studies. The value of the test system is that it will permit comparative and benchmark studies to be performed on new and existing reliability evaluation techniques. The test system was developed by modifying and updating the original IEEE RTS (referred to as RTS-79 hereafter) to reflect changes in evaluation methodologies and to overcome perceived deficiencies.

Assessment of available transfer capability and margins

Available transfer capability (ATC) calculation is a complicated task that involves the determination of total transfer capability (TTC) and two margins: transmission reliability margin (TRM) and capacity benefit margin (CBM). Three currently used methods of TTC determination are presented and compared in this paper. Besides these methods, the transfer-based security constrained OPF (TSCOPF) method is proposed in this paper as a replacement of the conventional SCOPF method for use in the deregulation environment. Both TRM and CBM, which account for reliability of the system, are seldom mentioned in papers associated with ATC. This paper presents a probabilistic method to assess TRM and proposes rules and a procedure to allocate CBM and two methods of incorporating CBM into ATC. A modified IEEE RTS is utilized to demonstrate the proposed methods, and the results show that the values of ATC are quite different when margins are taken into account and the methods of incorporating ATC affect the ATC value significantly.

Reliability Modeling of Generation Systems Including Unconventional Energy Sources

A method for reliability evaluation of electric power systems with unconventional energy sources, such as solar power plants and wind turbine generators, is presented. The fluctuating nature of energy produced by such unconventional units has a different effect on the overall system reliabilitv than conventional units. Methods described in the published literature appear to have several deficiencies. The method presented in this paper combines conventional and unconventional units into separate groups. The analysis proceeds by creating a generation system model for each group. The models of the unconventional groups are modified hourly depending on the limitations of energy. All the models are combined hourly to find the loss of load expectation and the frequency of capacity deficiency for the hour in question. This procedure is accomplished using a discrete state algorithm as well as the method of cumulants. Results obtained in a case study using the proposed method are described.

Reliability-Constrained Optimum Placement of Reclosers and Distributed Generators in Distribution Networks Using an Ant Colony System Algorithm

Optimal placement of protection devices and distributed generators (DGs) in radial feeders is important to ensure power system reliability. Distributed generation is being adopted in distribution networks with one of the objectives being enhancement of system reliability. In this paper, an ant colony system algorithm is used to derive the optimal recloser and DG placement scheme for radial distribution networks. A composite reliability index is used as the objective function in the optimization procedure. Simulations are carried out based on two practical distribution systems to validate the effectiveness of the proposed method. Furthermore, comparative studies in relation to genetic algorithm are also conducted.

Dispersed generation planning using improved Hereford ranch algorithm

This paper presents a new approach to dispersed generation planning based on Hereford ranch algorithm (HRA) in a subtransmission system. Dispersed generations could be photovoltaic cells, wind generation, battery storage, fuel cell, etc. A method to optimally locate such generation in a meshed network for maximizing the potential benefits is outlined using HRA and its improvement in this paper. The benefit expressed as a performance index is minimization of losses. The proposed method was tested for several sample power systems with 6, 14 and 30 bus types. Also, to show its effectiveness, the results of suggested algorithm are compared with those of classical genetic algorithm and conventional second-order method.

An efficient technique for reliability analysis of power systems including time dependent sources

A method of reliability analysis of electric power systems with time-dependent sources, such as photovoltaic and wind generation is introduced. The fluctuating characteristic of unconventional generation units affects the reliability of the generation system in a different manner than the conventional units. The method proposed by the authors groups the units into several subsystems. One subsystem contains the conventional units and the remaining subsystem consist of unconventional units. A generation system model is built for each subsystem. The outputs for the unconventional units and the load are treated as correlated random variables. Using a clustering procedure states are identified wherein for a given value of load there are specific mean values of the outputs of the unconventional units. Reliability analysis is performed by combining the conventional subsystem with the unconventional subsystems in each state. The output from all the states is combined to compute the loss of load expectation and expected unserved energy. >

A practical approach for integrated power system vulnerability analysis with protection failures

Protection system failure is one of the main causes of cascading outages. This paper proposes an integrated scheme to study power system vulnerability considering protection system failures. In this scheme, both adequacy and security based reliability analysis are conducted. A new protection system reliability model including two major failure modes is established to demonstrate their effects on power system reliability. The mechanism and scheme of protection systems have been analyzed for their contribution to cascading outages as well as system stability after a fault occurs. All contingencies and the responses in the power system are depicted in their inherent stochastic manner. The power system vulnerability is assessed by both adequacy indices, such as Bus Isolation Probability (BIP), Loss of Load Probability (LOLP) and Expected Power Loss (EPL), and the security index Probability of Stability (POS). In addition, a new vulnerability index, Integrated System Vulnerability (ISV), is introduced to give a more comprehensive description of the system vulnerability. A nonsequential Monte Carlo simulation approach is used to implement the stochastic properties of contingencies, protective response and protection system failures. The IEEE Reliability Test System is used to illustrate the methodology and present the results.

Composite system reliability evaluation using state space pruning

This paper presents a method of computing the reliability indices of a composite generation-transmission system by performing Monte Carlo simulation selectively on those regions of the state space where loss of load states are more likely to occur. These regions are isolated by performing state space decomposition to remove coherent acceptable subspaces. It is shown that this method results in a significant reduction in the number of sampled states, thereby reducing the computational effort required to compute the system and bus indices. The method assumes a DC flow model, and is tested using the IEEE Reliability Test System. The proposed method is not intended to replace existing variance reduction techniques; in fact, such techniques may be used in conjunction with the proposed method to further improve its efficiency.

Ant Colony Optimization-Based Method for Placement of Sectionalizing Switches in Distribution Networks Using a Fuzzy Multiobjective Approach

This paper proposes a methodology for placement of sectionalizing switches in distribution networks in the presence of distributed generation sources. The multiobjective considerations are handled using a fuzzy approach. The primary objective is reliability improvement with consideration of economic aspects. Thus, the objectives are defined as reliability improvement and minimization of the cost of sectionalizing switches. A fuzzy membership function is defined for each term in the objective function according to relevant conditions. Some considerations incorporated in the proposed model are relocation of existing switches and operating constraints on distribution networks and distributed generation (DG) sources during post-fault service restoration. The ant colony optimization (ACO) algorithm is adopted to solve the fuzzy multiobjective problem efficiently. The performance of the proposed approach is assessed and illustrated by various case studies on a test distribution system and also a real distribution network.

Optimal operating strategy for distributed generation considering hourly reliability worth

This paper presents a method to determine optimal operating strategy for distributed generation (DG) incorporating reliability worth evaluation of a distribution system. The use of DG for peak shaving could reduce the overall system operating cost and its use as standby power could reduce the customer interruption cost. If the DG operating cost is less than the utility power cost at peak time, DG should be employed to reduce the overall system operating cost. However, when customer interruption cost is also an important concern, standby power strategy for DG may be better than peak shaving. The reliability worth and the power cost evaluations are needed to determine whether DG should be operated for peak shaving or as standby power. The hourly reliability worth is incorporated in the strategy proposed in this paper to determine the optimal operating decision for the DG. Using the approach proposed in this paper, the distribution companies could determine the optimal operating strategy for their DG.