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Generation expansion planning consists of finding the optimal long-term plan for the construction of new generation capacity subject to various economic and technical constraints. It usually involves solving a large-scale, non-linear discrete and dynamic optimisation problem in a highly constrained and uncertain environment. Traditional approaches to capacity planning have focused on achieving a least-cost plan. During the last two decades however, new paradigms for expansion planning have emerged that are driven by environmental and political factors. This has resulted in the formulation of multi-criteria approaches that enable power system planners to simultaneously consider multiple and conflicting objectives in the decision-making process. More recently, the increasing integration of intermittent renewable energy sources in the grid to sustain power system decarbonisation and energy security has introduced new challenges. Such a transition spawns new dynamics pertaining to the variability and uncertainty of these generation resources in determining the best mix. In addition to ensuring adequacy of generation capacity, it is essential to consider the operational characteristics of the generation sources in the planning process. In this paper, we first review the evolution of generation expansion planning techniques in the face of more stringent environmental policies and growing uncertainty. More importantly, we highlight the emerging challenges presented by the intermittent nature of some renewable energy sources. In particular, we discuss the power supply adequacy and operational flexibility issues introduced by variable renewable sources as well as the attempts made to address them. Finally, we identify important future research directions. [ABSTRACT FROM AUTHOR]

With increasing levels of integration of intermittent renewable energy in the power grid, it has become essential for power system planners to quantify future requirements of power systems in terms of flexibility . It is also equally important to evaluate whether the flexibility available in a given power system is adequate to meet more frequent and larger variations in the net load. In this paper, we present a novel framework to develop a composite metric that provides an accurate assessment of flexibility within conventional generators of a power system. This assessment is performed using eight technical characteristics of generating units as indicators. An Analytic Hierarchy Process is applied to assign weights to these indicators in order to reflect their relative importance in the supply of flexibility. Following normalization with min–max method, the indicators are linearly aggregated to give the composite flexibility index for each generator. The proposed methodology is tested on an adapted IEEE RTS-96 system. Our results demonstrate the consistency of the composite flexibility metric. It is further observed that the proposed metric is adaptive since it automatically adjusts to the addition and/or removal of generating units. To evaluate the robustness of the proposed framework, we also performed sensitivity and uncertainty analysis in the presence of alternative methodological choices in the composite metric construction process. [ABSTRACT FROM AUTHOR]

• Framework considers flexibility, cost and CO 2 emissions as separate objectives. • Overlooking flexibility in generation planning gives rise to infeasible portfolios. • Analysis of Pareto-optimal solutions reveals potential correlations among objectives. • Unit commitment validates evaluation of flexibility in generation plans by model. • Parallel coordinates plots help in the selection of preferred investment plan. The growing importance of operational flexibility in generation expansion planning with increased integration of variable renewables has been regularly highlighted in recent research. Yet, operational flexibility has been largely overlooked in order to reduce the prohibitive problem size that results when operational details at small timescales are included in this long-term exercise. In this work, we present a multi-objective optimization framework that effectively and tractably incorporates flexibility screening of candidate generation portfolios in long-term generation expansion planning. Operational flexibility is considered as a separate objective along with the traditional economic and environmental objectives. The ability of the proposed methodology to provide valuable insights into the correlations between flexibility, total costs and carbon emissions is demonstrated using a case study. The results clearly reveal that omission of flexibility from the framework gives rise to deficient generation mixes that are unable to match the more frequent and steeper variations in net load. A high-level evaluation of the flexibility needed in generation portfolios to balance net loads with different degrees of variability is also provided. Finally, a procedure is proposed to support the decision-making process for selecting the most appropriate investment plan among the many solution options provided by the multi-objective optimization framework. [ABSTRACT FROM AUTHOR]