M.A. Baherifard; R. Kazemzadeh; A.S. Yazdankhah; M. Marzband
Abstract
With the development of electrical network infrastructure and the emergence of concepts such as demand response and using electric vehicles for purposes other than transportation, knowing the behavioral patterns of network technical specifications to manage electrical systems has become very important ...
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With the development of electrical network infrastructure and the emergence of concepts such as demand response and using electric vehicles for purposes other than transportation, knowing the behavioral patterns of network technical specifications to manage electrical systems has become very important optimally. One of the critical parameters in the electrical system management is the distribution network imbalance. There are several ways to improve and control network imbalances. One of these ways is to detect the behavior of bus imbalance profiles in the network using data analysis. In the past, data analysis was performed for large environments such as states and countries. However, after the emergence of smart grids, behavioral study and recognition of these patterns in small-scale environments has found a fundamental and essential role in the deep management of these networks. One of the appropriate methods in identifying behavioral patterns is data mining. This paper uses the concepts of hierarchical and k-means clustering methods to identify the behavioral pattern of the imbalance index in an unbalanced distribution network. For this purpose, first, in an unbalanced network without the electric vehicle parking, the imbalance profile for all busses is estimated. Then, by applying the penetration coefficient of 25% and 75% for electric vehicles in the network, charging\discharging effects on the imbalance profile is determined. Then, by determining the target cluster and using demand response, the imbalance index is improved. This method reduces the number of busses competing in demand response programs. Next, using the concept of classification, a decision tree is constructed to minimize metering time.
Power System Operation
A. Niromandfam; A. Sadeghi Yazdankhah; R. Kazemzadeh
Abstract
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 ...
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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.
Energy Management
A. Hatefi einaddin; A. Sadeghi Yazdankhah; R. Kazemzadeh
Abstract
As an efficient alternative to fossil fuels, renewable energy sources have attained great attention due to their sustainable, cost-effective, and environmentally friendly characteristic. However, as a deficiency, renewable energy sources have low reliability because of their non-deterministic and stochastic ...
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As an efficient alternative to fossil fuels, renewable energy sources have attained great attention due to their sustainable, cost-effective, and environmentally friendly characteristic. However, as a deficiency, renewable energy sources have low reliability because of their non-deterministic and stochastic generation pattern. The use of hybrid renewable generation systems along with the storage units can mitigate the reliability problem. Hence, in this paper, a grid connected hybrid micro-grid is presented, which includes wind and photovoltaic resources as the primary power sources and a hydrogen storage system (including fuel cell and electrolyzer) as a backup. A new power management strategy is proposed to perform a proper load sharing among the micro-grid units. Hybrid (distributed/central) control method is applied for the realization of the control objectives such as DC bus voltage regulation, power factor control, synchronous grid connection, and power fluctuation suppression. Distributed controllers have the task of fulfilling local control objectives such as MPPT implementation and storage unit control. On the other hand, the central control unit is mainly responsible for power management in the micro-grid. Performance and effectiveness of the proposed power management strategy for the presented micro-grid are verified using a simulation study.
