• Energy Research

Rare and extreme climate events may result in wide power outages or blackouts. The concept of power system resilience has been introduced for focusing on high-impact and low-probability (HILP) events such as a hurricane, heavy snow, and floods. Power system resilience is the ability of a system to reduce the likelihood of blackout or wide power outages due to HILP events. Indeed, in a resilient power system, as the severity of HILP events increases, the rate (but not the amount) of unserved loads diminishes. Suitable measures for managing power system resilience can be classified into three categories in terms of time, known as “resilience-based planning,” “resilience-based response,” and “resilience-based restoration.” The most widely used approaches, methods, and techniques in each of these categories, as well as the future trends for improving the power system resilience are reviewed in this article. The challenges of resilience in power systems with high penetration of renewable energy sources are also discussed in each of these categories.

Rare and extreme climate events may result in wide power outages or blackouts. The concept of power system resilience has been introduced for focusing on high-impact and low-probability (HILP) events such as a hurricane, heavy snow, and floods. Power system resilience is the ability of a system to reduce the likelihood of blackout or wide power outages due to HILP events. Indeed, in a resilient power system, as the severity of HILP events increases, the rate (but not the amount) of unserved loads diminishes. Suitable measures for managing power system resilience can be classified into three categories in terms of time, known as “resilience-based planning,” “resilience-based response,” and “resilience-based restoration.” The most widely used approaches, methods, and techniques in each of these categories, as well as the future trends for improving the power system resilience are reviewed in this article. The challenges of resilience in power systems with high penetration of renewable energy sources are also discussed in each of these categories.

AbstractThe rapid development of different energy production and conversion technologies at the distribution system (DS) level facilitates the integration of electrical, heating, and cooling DSs. The planning and operation of integrated DSs will affect the asset management of the transmission system (TS), which in turn will change the electrical energy prices and investment decisions at the DS level. This paper addresses a tri‐level multi‐stage approach for coordinated expansion planning of TS and integrated electrical, heating and cooling DSs. The photo voltaic panels (PVs), wind turbines (WTs), combined heat and power generation (CHP) units, boilers, and electrical and absorption chillers are considered investment candidates for coupling the DSs. Moreover, the expansion planning of TS lines, electrical feeders,and heating and cooling pipelines are integrated into the proposed model. The discussed model is tested on the modified 6‐bus, 30‐bus, and 118 bus IEEE TS comprising electrical, heating, and cooling DSs. The numerical study proves that the distribution system operators (DSOs), connected to different nodes of the TS, reduce their operation and emissioncosts by investing in the energy resources. Moreover, the proposed scheme successfully reduces the total expected cost of the transmission system operator (TSO) and successfully postpones the expansion of the TS.

AbstractThe rapid development of different energy production and conversion technologies at the distribution system (DS) level facilitates the integration of electrical, heating, and cooling DSs. The planning and operation of integrated DSs will affect the asset management of the transmission system (TS), which in turn will change the electrical energy prices and investment decisions at the DS level. This paper addresses a tri‐level multi‐stage approach for coordinated expansion planning of TS and integrated electrical, heating and cooling DSs. The photo voltaic panels (PVs), wind turbines (WTs), combined heat and power generation (CHP) units, boilers, and electrical and absorption chillers are considered investment candidates for coupling the DSs. Moreover, the expansion planning of TS lines, electrical feeders,and heating and cooling pipelines are integrated into the proposed model. The discussed model is tested on the modified 6‐bus, 30‐bus, and 118 bus IEEE TS comprising electrical, heating, and cooling DSs. The numerical study proves that the distribution system operators (DSOs), connected to different nodes of the TS, reduce their operation and emissioncosts by investing in the energy resources. Moreover, the proposed scheme successfully reduces the total expected cost of the transmission system operator (TSO) and successfully postpones the expansion of the TS.

This paper investigates the impacts of integrating nondeterministic flexible ramp reserves in a multistage multiresolution day-ahead robust unit commitment to cope with variability of renewable energy sources. While the common literature considers deterministic forms of flexible ramp reserves, the proposed affinely adjustable robust UC model considers explicit endogenous up and down subhourly ramp reserve deployment to effectively allocate flexible ramp capacities. In addition, unlike the conventional noncausal two-stage robust unit commitment models that immunize solutions against worst economic scenario with the dependency of decisions on the future information of uncertainty, the current nonconservative multistage model optimizes hourly commitment and dispatch scheduling for the base-case scenario, while ensuring that the specified subhourly causal ramp reserves can be adaptively adjusted. Moreover, dimensionality limitations of the conventional duality-based affinely adjustable robust optimizations are resolved. The effectiveness of the proposed model compared with conventional robust unit commitment frameworks is extensively illustrated on the IEEE 24-bus reliability test system and the IEEE 118-bus test system.

This paper investigates the impacts of integrating nondeterministic flexible ramp reserves in a multistage multiresolution day-ahead robust unit commitment to cope with variability of renewable energy sources. While the common literature considers deterministic forms of flexible ramp reserves, the proposed affinely adjustable robust UC model considers explicit endogenous up and down subhourly ramp reserve deployment to effectively allocate flexible ramp capacities. In addition, unlike the conventional noncausal two-stage robust unit commitment models that immunize solutions against worst economic scenario with the dependency of decisions on the future information of uncertainty, the current nonconservative multistage model optimizes hourly commitment and dispatch scheduling for the base-case scenario, while ensuring that the specified subhourly causal ramp reserves can be adaptively adjusted. Moreover, dimensionality limitations of the conventional duality-based affinely adjustable robust optimizations are resolved. The effectiveness of the proposed model compared with conventional robust unit commitment frameworks is extensively illustrated on the IEEE 24-bus reliability test system and the IEEE 118-bus test system.

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