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© 2016 Elsevier Ltd Power balance is one of the key requirements for reliable power system operation. However, factors, such as net load variability and forecast errors, impose practical limitations on matching the scheduled generation and the real-time demand. Normally, potential power imbalances are mitigated by scheduling additional generation capacity called operating reserves. However, reserves are a costly commodity and their requirements should be accurately assessed to avoid unnecessary expense. Currently, the reserve requirements are determined using a posteriori methods based upon operator's experience and established assumptions. While these assumptions are made out of a level of engineering practicality, they may not be formally true given the numerical evidence. This paper presents a formal mathematical framework for the a priori determination of three types of operating reserve requirements, namely load following, ramping and regulation. Validation of the methodology is performed by a set of extensive simulations that model the power system operations for different scenarios. This methodology is used to study the sensitivity of each type of reserve requirement to the net load and power system parameters.

© 2016 Elsevier Ltd Power balance is one of the key requirements for reliable power system operation. However, factors, such as net load variability and forecast errors, impose practical limitations on matching the scheduled generation and the real-time demand. Normally, potential power imbalances are mitigated by scheduling additional generation capacity called operating reserves. However, reserves are a costly commodity and their requirements should be accurately assessed to avoid unnecessary expense. Currently, the reserve requirements are determined using a posteriori methods based upon operator's experience and established assumptions. While these assumptions are made out of a level of engineering practicality, they may not be formally true given the numerical evidence. This paper presents a formal mathematical framework for the a priori determination of three types of operating reserve requirements, namely load following, ramping and regulation. Validation of the methodology is performed by a set of extensive simulations that model the power system operations for different scenarios. This methodology is used to study the sensitivity of each type of reserve requirement to the net load and power system parameters.

Power generation reserves play a central role for maintaining the balance of generation and consumption. Reserves, scheduled in advance, compensate for forecast error, variability and transmission losses. However, as reserves are a costly commodity, their amount should be carefully assessed to prevent unnecessary expense. Currently, the quantity of required reserves are determined based upon a posteriori methods that use operator's experience and established assumptions. While these assumptions have been made out of a level of engineering practicality, they may not be formally true given the numerical evidence. The earlier 'sister' paper to this work presented a method to determine the quantity of load following reserves a priori. This paper now uses a similar methodology to determine the quantity of ramping reserves. ©2015

Power generation reserves play a central role for maintaining the balance of generation and consumption. Reserves, scheduled in advance, compensate for forecast error, variability and transmission losses. However, as reserves are a costly commodity, their amount should be carefully assessed to prevent unnecessary expense. Currently, the quantity of required reserves are determined based upon a posteriori methods that use operator's experience and established assumptions. While these assumptions have been made out of a level of engineering practicality, they may not be formally true given the numerical evidence. The earlier “sister” paper to this work presented a method to determine the quantity of load following reserves a priori. This paper now uses a similar methodology to determine the quantity of ramping reserves.

In recent years, an extensive academic and industrial literature has been developed to determine how much such variable energy resources (VERs) may be integrated and how to best mitigate their impacts. While certainly insightful within the context of their application, many integration studies have methodological limitations in that they are case specific, address a single control function of power grid balancing operations, and are often not validated by simulation. This paper presents a holistic method for the assessment of power grid imbalances induced by VERs based upon the concept of enterprise control. It consists within a single package a three-layer enterprise control simulator which includes most of the balancing operation functionality found in traditional power systems. The control layers include a resource scheduling layer composed of a security-constrained unit commitment, a balancing layer composed of a security-constrained economic dispatch, and a regulation layer. The proposed method is validated by a set of numerical simulations. The sequel to this paper submitted to the same issue provides a set of extensive results that demonstrate how power grid balancing operations systematically address VER integration.

In recent years, renewable energy has developed to address energy security and climate change drivers. However, as energy resources, they possess a variable and uncertain nature that significantly complicates grid balancing operations. As a result, an extensive academic and industrial literature has developed to determine how much such variable energy resources (VERs) may be integrated and how to best mitigate their impacts. While certainly insightful with the context of their application, many integration studies have methodological limitations because they are case specific, address a single control function of the power grid balancing operations, and are often not validated by simulation. The prequel to this paper presented a holistic method for the assessment of power grid imbalances induced by VERs based upon the concept of enterprise control. This paper now systematically studies these power grid imbalances in terms of five independent variables: 1) day-ahead market time step; 2) real-time market time step; 3) VER normalized variability; 4) normalized day-ahead VER forecast error; and 5) normalized short-term VER forecast error. The systematic study elucidates the impacts of these variables and provides significant insights as to how planners should address these independent variables in the future.