Volume 10, Issue 5

In an electricity market, suppliers are more concerned with maximizing their profit and minimizing the financial risk, which can be achieved through strategic bidding. In this paper, Equal Incremental Cost Criteria (EICC) has been used for developing the optimal bidding strategy. The rival's bidding behavior has been formulated using a stochastic optimization model. Genetic Algorithm (GA), along with ac sensitivity factors, has been used to decide the optimal bidding strategy including congestion management to maximize the profit of the suppliers, considering single sided as well as double sided bidding. Both pure as well as probabilistic strategies have been simulated. Results with Sequential Quadratic Programming (SQP), a classical optimization method, and dc sensitivity factors have also been obtained to compare and establish the effectiveness of proposed method. Value at Risk (VaR) has been calculated as a measure of financial risk.

This paper presents an approach to model current transformers (CTs) by visual inspection of hysterisis loops. Three parameters on CT hysterisis loops reveal enough information about the core-loss and non-linear magnetizing inductance that power measurements and flux-current data-pairs can be avoided. To validate the proposed model, an experimental CT is saturated with energizations and compared to simulation results. Overlays of the experimental energizations, the proposed modeling approach, and the traditional piecewise-linear approach are compared.

Ever growing demand for the electric power requires timely expansion of generations and networks. It is observed that these expansions may not often be done optimally and the load concentration locations and generation expansion locations may not always match up. To address this problem of meeting the growing loads optimally, a concept of relative electrical distance (RED) is applied to identify the optimum generation reschedule values and also system expansion locations. The approach of RED computes the relative electrical distances between the generation and load buses using the transmission network parameters. Using this approach, the amount of generation increase or evacuation required can be identified. This paper presents the approach using a sample 16-bus system and a practical 72-bus system, an equivalent of Indian southern grid. Studies are carried out considering short term and long term load growths and the results obtained are validated using power flows. The different scenarios studied are assessed based on their minimum voltage, MW loss values, Minimum Singular Value etc. Few aspects like cost estimation for network expansion, loss shared by different generations etc, are also computed, and it is finally concluded that the best tradeoff between the two expansions is to be honored.

This paper discusses the stability of an autonomous microgrid in which, load sharing by a gain scheduled angle droop controller with derivative feedback is proposed. It is assumed that all the DGs are connected through Voltage Source Converter (VSC). The VSCs are controlled by state feedback controller to achieve desired voltage and current outputs that are decided by a droop controller. First a load sharing strategy is derived in terms of droop controller gain and converter output inductance, combining angle droop controller and DC load flow analysis. Then state space models of converters with its associated feedback controller are derived to investigate system stability as a function of the droop controller gain and converter output inductance through eigen value analysis. It is shown that with proposed angle droop controllers, where the droop gains are scheduled based on the output power along with derivative feedback it is possible to achieve a higher stability margin with better load sharing. These observations are then verified through simulation studies using PSCAD/EMTDC. It will be shown that the simulation results closely agree with stability behavior predicted by the eigenvalue analysis.

This paper proposes a method for enhancing stability of an autonomous microgrid with distribution static compensator (DSTATCOM) and power sharing with multiple distributed generators (DG). It is assumed that all the DGs are connected through voltage source converter (VSC) and all connected loads are passive, making the microgrid totally inertia less. The VSCs are controlled by either state feedback or current feedback mode to achieve desired voltage-current or power outputs, respectively. A modified angle droop is used for DG voltage reference generation. Power sharing ratio of the proposed droop control is established through derivation and verified by simulation results. A DSTATCOM is connected in the microgrid to provide ride through capability during power imbalance in the microgrid, thereby enhancing the system stability. This is established through extensive simulation studies using PSCAD.

The purpose of this paper is to present results for power system stabilizers (PSS) coordination in multi-machine applications. Due to their versatility, multiband power system stabilizers (MB_PSS) have been employed to enhance the power oscillations damping. The problem at hand is to minimize an objective function, which is solved by the conventional differential evolution (DE) algorithm. Results for an equivalent of the Mexican power system are exhibited showing the improvement on the electromechanical transient.