Power System Stability
F. Babaei; A. Safari; J. Salehi; H. Shayeghi
Abstract
Although the presence of clean energy resources in power systems is required to reduce greenhouse gas emissions, system security faces severe challenges due to its increased intelligence and expansion, as well as the high penetration of renewable energy resources. According to new operating policies, ...
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Although the presence of clean energy resources in power systems is required to reduce greenhouse gas emissions, system security faces severe challenges due to its increased intelligence and expansion, as well as the high penetration of renewable energy resources. According to new operating policies, power systems should withstand subsequent single contingencies. Also, the effect of electrical and structural characteristics must be considered in power system security assessment. Thus, this paper introduces a comprehensive risk-based approach that quantifies the impact of contingency-induced variation in topology by using complex network theory metrics. Then, it identifies elements that surpass security limitations and eliminates them to execute cascading outage analysis via AC power flow. Lastly, wind power uncertainty and contingency probability are multiplied by the linear combination of electrical and structural consequences, and security status is assigned to each contingency based on its risk value. Additionally, simulations are carried out on modified 118 and 300 bus IEEE systems, and the extensive results are utilized to demonstrate the effectiveness of the proposed methodology.
M. Khadem Maaref; J. Salehi
Abstract
Microgrids are known as the main components of energy networks because they can accommodate a large share of renewable energy sources. Peer-to-peer energy trading is one of the most effective ways to implement decentralized patterns in the electricity market. In peer-to-peer trades, each actor negotiates ...
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Microgrids are known as the main components of energy networks because they can accommodate a large share of renewable energy sources. Peer-to-peer energy trading is one of the most effective ways to implement decentralized patterns in the electricity market. In peer-to-peer trades, each actor negotiates directly with a set of partners without any intermediaries. Peer-to-peer energy exchange methods allow direct energy exchange between producers and consumers. This study tested the peer-to-peer trading method on networks consisting of 4 microgrids. Existing microgrids have different generating sources, such as solar energy, wind turbines, and microturbines, each of which is modeled separately. Moreover, in order to reduce the uncertainty in the production of renewable sources, a battery storage system has been used in this network. Also, to encourage microgrids to use renewable resources, cut-off costs have been considered by these resources. This research uses the constrained optimization method and GAMS software with a Baron solver to optimize the problem. In the end, the uncertainty of producing renewable resources for different modes is examined using the information gap decision theory method. The available results show the power distribution between microgrids and other network components based on the objective function and existing constraints.
A. Namvar; J. Salehi
Abstract
One of the crucial challenges within the optimal operation of smart cities is coordinated management of multiple energy carriers in the residential buildings owing to disparate and often conflicting objectives. In response to this challenge, this paper proposes a novel conceptual cost-emission-based ...
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One of the crucial challenges within the optimal operation of smart cities is coordinated management of multiple energy carriers in the residential buildings owing to disparate and often conflicting objectives. In response to this challenge, this paper proposes a novel conceptual cost-emission-based scheme for optimal energy-gas use in a smart home in the context of residential energy hubs considering a meaningful trade-off between cost saving and environmental protection. Various energy conversion resources containing energy and heat storage systems, rooftop photovoltaic modules, and also combined heat and power units along with responsible electrical and thermal loads are taken into account in the proposed model. Furthermore, an efficient stochastic scenario-based method is executed to tackle the intense uncertainty associated with photovoltaic production. The proposed model reduces domestic energy consumption and utility costs by incorporating a weighted summation mixed objective function under various system constraints and user preferences, while at t the same time optimal task scheduling and comfort for the resident that it can guarantee a good lifestyle. The presented scheme is carried out on a realistic case study equipped with energy hubs and as expected, introduces its applicability and effectiveness in the optimal energy management of the proposed residential energy hub problem. The simulation results confirm that energy procurement costs can be saved by up to 46.16% and emission costs by 34.07% while maintaining the desired level of comfort for the head of the household.
