Journal of Operation and Automation in Power Engineering
Volume:8 Issue: 3, Autumn 2020

The operation planning problem encounters several uncertainties in terms of the power system’s parameters such as load, operating reserve and wind power generation. The modeling of those uncertainties is an important issue in power system operation. The system operators can implement different approaches to manage these uncertainties such as stochastic and fuzzy methods. In this paper, new fuzzy based modeling approach is implemented to develop the new formulation of power system problems under an uncertain environment with energy storage systems. Interval type-2 fuzzy membership function (MF) is implemented to model the uncertainty of available wind power generation and the type-1 fuzzy MF is used to model the other parameters in weekly unit commitment (UC) problem. The proposed approach is applied to two different test systems which have conventional generating units, wind farms and pumped storage plants to consider differences between the type-1 and type-2 fuzzy approaches for uncertainty modeling. The results show that the total profit of UC problem using type-2 fuzzy MF is better than type-1 fuzzy MF.

This study addresses a stochastic structure for generation companies (GenCoʼs) that participate in hydro-thermal self-scheduling with a wind power plant on short-term scheduling for simultaneous reserve energy and energy market. In stochastic scheduling of HTSS with a wind power plant, in addition to various types of uncertainties such as energy price, spinning /non-spinning reserve prices, uncertainties of RESs, such as output power of the wind power plant are also taken into account. In the proposed framework, mixed-integer non-linear  programming of the HTSS problem is converted into a MIP. Since the objective of the study is to show how GenCosʼ aim to achieve maximum profit, mixed-integer programming is used here. Therefore, to formulate the MIP for the problem of HTSS with a wind power plant in the real-time modeling, some parameters like the impact of valve loading cost (VLC) that are accompanied by linear modeling, are considered. Furthermore, in thermal units, parameters such as prohibited operating zones (POZs) and different  uncertainties  like the energy  price and wind power are included  to formulate the problem more suitably. The point that is worth noting is the use of dynamic ramp rate (DRR). Also, the application of multi-functional curves (L) of hydro plants is considered  when studying  inter-unit scheduling. Finally, the required tests are conducted  on  a modified  IEEE 118-bus system to verify the accuracy and methodology of the proposed method.

Voltage stability is one of the most important factors in maintaining reliable operation of power systems. When a disturbance occurs in the power system, it usually causes instabilities and sometimes leads to voltage collapse (VC). To avoid such problems, a novel approach called Vector Analysis (VA) is proposed that exploits a new instability detection index to provide wide area voltage stability for the power systems. The presented index is calculated based on measuring the active and reactive powers that flow through the bus which is connected to the generator bus. Moreover, when the proposed VA approach predicts VC, through disconnecting weak lines and based on network graph, zoning is carried out in the power system. After zoning, damaged and undamaged zones will be differentiated and damaged zones requires load shedding (LS) which is accomplished using ANFIS-TSK (AN-T) intelligent method. The presented approach is applied to the IEEE-39 bus test system. The obtained simulation results demonstrate acceptable performance of the presented approach compared with other suggested methods in terms of speed and accuracy.

In this paper, a novel method for loss reduction and efficiency optimization of the high frequency flyback transformers is proposed based on rearrangement of the windings. According to detailed analysis of the high frequency flyback transformer using FEM technique, a novel and simple approach for its design improvement and loss reduction is introduced. It is shown that leakage flux scattering in core air-gap is one of the main reasons for hot-spot point generation in the windings. So, this problem and its possible solutions are analyzed in more detail. Moreover, FEM analysis is used for investigation of the developed method and rearrangement of the winding structure. In fact, some winding structures for efficiency improvement of the flyback transformer is presented and analyzed. Finally, in order to verify accuracy and effectiveness of the developed approach, simulation and experimental results are presented. Experimental results show 3.3% improvement in total efficiency of the converter and 41.78% loss reduction in the flyback transformer.

Mitigating switching overvoltages (SOVs) and conducting well-suited insulation coordination for handling stresses are very important in UHV transmission Lines. The best strategy in the absence of arresters is controlled switching (CS). Although elaborate works on electromagnetic transients are considered in the process of designing transmission systems, such works are not prevalent in day-to-day operations. The power utility and/or operator have to carefully monitor the peak values of SOVs so this values not to exceed the safe limits. In this paper, we present a novel CS approach in dealing with EMTP/ATP environment, where trapped charge (TC) is intended to train a radial basis function network (RBFN) meta-model that is implemented to calculate SOVs. A new weighted maximum overvoltage factor proposed to find locations of critical failure risk due to SOVs occurred along transmission lines. Power utilities or design engineers can benefit from the presented meta-model in designing a well-suited insulation level without spending time for taking into account the feasible risk value. Besides, the operators can energize the lines sequentially upon their choice; i.e., a safe and proper energization.

This paper presents a model-based approach for the global maximum power point (GMPP) tracking of solar strings under partial shading conditions. In the proposed method, the GMPP voltage is estimated without any need to solve numerically the implicit and nonlinear equations of the photovoltaic (PV) string model. In contrast to the existing methods in which first the locations of all the local peaks on the P-V curve are estimated and next the place of the GMPP is selected among them, the suggested method estimates directly the GMPP without any need for the evaluation of the other local peaks. The obtained GMPP voltage is then given as a reference value to the input voltage controller of a DC-DC boost converter to regulate the output voltage of the solar string at the GMPP voltage in various irradiation conditions. Furthermore, the values of the temperature and irradiation level of each PV module within the PV string are estimated, and therefore, the proposed method does not need to thermometers and pyranometers. This makes it as a reliable and low-cost GMPP tracking method. The theoretical aspects on which the proposed GMPP algorithm is established are also discussed. The comparison of the numerical results of the suggested GMPP tracking scheme with the existing methods at different environmental conditions shows the satisfactory operation of the proposed technique from the speed and accuracy point of views.

The regulatory schemes currently used for reliability improvement have weaknesses in the provision of quality services based on the customers’ perspective. These schemes consider the average of the service as a criterion to incentivize or penalize the distribution system operators (DSOs). On the other hand, most DSOs do not differentiate electricity services at the customer level, due to the status of the electricity grid and lack of adequate information about customers’ preferences. This paper proposes a novel reliability insurance scheme (RIS), which enables the electricity consumers to determine their desired reliability levels according to their preferences and pay corresponding premiums to the DSO. The DSO can use the premiums to improve reliability or reimburse consumers. To design efficient insurance contracts, this paper uses utility function to estimate customers’ viewpoints of electricity energy consumption. This function measures the customers’ satisfaction of electricity energy consumption. The proposed utility based reliability insurance scheme (URIS) may create a free-riding opportunity for the DSO, in which low quality service is provided and the collected premiums are used to pay the reimbursements. To prevent free-riding opportunity, this paper incorporates the proposed URIS and reward/penalty schemes (RPSs). The results show that the success of the proposed reliability scheme increases as the grid flexibility increases.

A stand-alone microgrid usually contains a set of distributed generation resources, energy storage system and loads that can be used to supply electricity of remote areas. These areas are small in terms of population and industry. Connection of these areas to the national distribution network due to the high costs of constructing transmission lines is not economical. Optimal utilization and economic management of production units and storage devices are important issues in isolated microgrids. During optimum utilization, of renewable energy harvesting is maximized and fuel cost of diesel units reduces as much as possible. In this paper, the optimization problem is designed and solved as Linear Programming (LP). The cost of diesel generator unit depends on its production. Also, the fact is considered that the efficiency of diesel generator units is not constant for all amount of production. As a solution for this challenge demand side management plans have been proposed. On the other hand, load uncertainty is considered in this paper. Several scenarios are simulated by GAMS software for different conditions of a typical microgrid. The simulation results show the success of the proposed method in reducing costs and fossil fuel consumption and increasing the consumption of renewable energy.