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Measuring and understanding the evolution of the electricity generation efficiency sector is a relevant task for policymakers. This study focuses on assessing the determinants of electricity generation efficiency across 24 countries in Latin America and the Caribbean between 2000 and 2020. A hurdle model was employed to account for the censored nature of the dependent variable. The findings show a positive impact of opening up the electricity sector in fully efficient countries. Market liberalization and the involvement of privately owned power plants contribute to efficiency gains in inefficient countries. Additionally, the tariff protectionism level exhibits positive effects for completely efficient and inefficient countries. These results provide valuable insights, as less-efficient countries can glean strategies from their more efficient counterparts to enhance their electricity generation efficiency. [ABSTRACT FROM AUTHOR]

This paper presents a bi-level model for distribution network and renewable energy expansion planning under a demand response (DR) framework. The role of DR has recently attracted an increasing interest in power systems. However, previous models have not been completely adapted in order to treat DR on an equal footing. The target of the distribution network and generation planner, modeled through the upper-level problem, is to minimize generation and network investment cost while meeting the demand. This upper-level problem is constrained by the lower-level problem, stressing the importance of integrating DR to time-varying prices into those investment models. The objective function considered for the lower level is the minimization of overall payment faced by the consumers. Using the Karush-Kuhn-Tucker complementarity constraints, the proposed bi-level model is recast as a mixed-integer linear programming problem, which is solvable using efficient off-the-shelf branch-and-cut solvers. Detailed results from an insular case study (La Graciosa, Canary Islands, Spain) are presented. [ABSTRACT FROM PUBLISHER]

This paper addresses the multistage expansion planning problem of a distribution system where investments in the distribution network and in distributed generation are jointly considered. Network expansion comprises several alternatives for feeders and transformers. Analogously, the installation of distributed generation takes into account several alternatives for conventional and wind generators. Unlike what is customarily done, a set of candidate nodes for generator installation is considered. Thus, the optimal expansion plan identifies the best alternative, location, and installation time for the candidate assets. The model is driven by the minimization of the net present value of the total cost including the costs related to investment, maintenance, production, losses, and unserved energy. The costs of energy losses are modeled by a piecewise linear approximation. As another distinctive feature, radiality conditions are specifically tailored to accommodate the presence of distributed generation in order to avoid the isolation of distributed generators and the issues associated with transfer nodes. The resulting optimization problem is a mixed-integer linear program for which finite convergence to optimality is guaranteed and efficient off-the-shelf software is available. Numerical results illustrate the effective performance of the proposed approach. [ABSTRACT FROM AUTHOR]

Wind energy is present in many countries throughout the world. The main types of wind sales in electricity markets are via regulated tariffs or pool-based markets. Production companies choose cost-effective options for selling wind energy, and some markets, like the Irish electricity market, use regulated tariffs to remunerate wind production. This paper aims to provide some answers to explain what effect wind offers may have in an electricity market if wind power producers participated in the day-ahead market without receiving any premium or aid. A price-maker optimization model is used to detect its effect on prices. The model encompasses energy offers by other technologies using residual demand curves and detailed modeling of wind imbalances. It is observed that wind acting as price-maker reduces electricity prices and the imbalance penalties help the system operator to reduce imbalances. A realistic case study using data from the Irish electricity market illustrates the methodology used comparing the effect of imbalance penalties in the models in terms of profit and total imbalance of the system. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for the joint energy and reserves scheduling and unit commitment with n-K reliability constraints for the day-ahead market. The proposed method includes a novel n-K criterion where demand must be met with a specified probability under any simultaneous loss of K generating units. A chance-constrained method is proposed with an \alpha-quantile measure to determine the confidence level to meet the demand under K simultaneous contingencies. The chance-constrained optimization problem is recast as a mixed integer linear programming optimization problem. Wind and demand uncertainty are included into the model. The methodology proposed is illustrated with several case studies where the effect of increasing wind power penetration is analyzed showing the performance of our model. [ABSTRACT FROM PUBLISHER]

A method is presented that allows finding the market clearance prices within a hydrothermal power exchange market that incorporates network constraints. An analysis is made of the degree of market power exerted by the various agents. The Nash-Cournot equilibrium solution of the market is achieved using the Nikaido-Isoda function, which is derived from the profit maximization functions calculated by the generating companies. Both thermal, hydro generation, and network constraints are considered in the model, with coupling constraints of the hydro units also taken into account. The model is applied to the main Chilean interconnected power system, whose abundant hydro production and existing network bottlenecks make it a valuable suitable case for study. The results for pool-based and bilateral contract markets highlight the strength of the method and show the contribution of the transmission system and hydro constraints. [ABSTRACT FROM AUTHOR]

A mixed integer nonlinear programming (MINLP) model for scheduling of the short-term integrated operation of a series of price-taker hydroelectric plants (H-GENCO) along a cascaded reservoir system in a pool-based electricity market is presented. The objective of the H-GENCO can be either to maximize profit, taking into account technical efficiency, or to maximize technical efficiency, maintaining a profit level. In both cases, the efficiency can be accurately obtained using the “Hill diagram” supplied by turbine manufacturers. A multiple nonlinear regression analysis of the unit's technical efficiency is estimated as a quadratic function of net head and water discharge. Several case studies of realistic dimensions are described, where results indicate that a profit-based MINLP produces better results compared to an MILP model, on the other hand, higher efficiencies and water savings are obtained in the efficiency-based model. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of allocating the cost of the transmission network to generators and demands. A physically-based network usage procedure is proposed. This procedure exhibits desirable apportioning properties and is easy to implement and understand. A case study based on the IEEE 24-bus system is used to illustrate the working of the proposed technique. Some relevant conclusions are finally drawn. [ABSTRACT FROM AUTHOR]

Studying the evolution of the efficiency of the electricity generation sector is a relevant task for policy makers, and requires the undesirable outputs derived from the activity to be considered in the evaluation. In this work, we propose a dynamic slack-based Data Envelopment Analysis (DEA) model that incorporates the assumption of weak disposability between the generation of electricity from fossil sources and the CO2 emissions caused by the sector to measure the technical efficiency of 24 Latin American and Caribbean countries in the period 2000–2016. The results show that, of the total number of countries studied, four are efficient overall, and four groupings of countries in relation to the levels of efficiency achieved are also identified. These results are important given that less-efficient countries can, through learning, increase their efficiency in electricity generation or emulate the future strategies proposed by the most efficient countries. [ABSTRACT FROM AUTHOR]

In deregulated electricity markets, a Generation Company (Genco) has to optimally allocate their energy among different markets including spot, local and bilateral contract markets. Modern portfolio theory (MPT) allows a Genco to achieve their goal by maximizing their profit and decreasing their associated risk. Combining MPT with an adequate tool to forecast energy prices makes it possible for a Genco to vary the optimal allocation of their portfolio even on a daily basis. This paper proposes two MPT models, one applying the Mean Variance Criterion (MVC) and the other one the Conditional Value at Risk (CVaR). The MPT models are combined with a generalized autoregressive conditional heteroskedastic (GARCH) prediction technique for a Genco to optimally diversify their energy portfolio. The two models are applied to a real PJM electricity market showing not only their capabilities but also useful comparisons between them in order to help decision makers to use them as decision-aid tools. [ABSTRACT FROM AUTHOR]

• Proposing and developing a planning tool for MV/LV large-scale distribution systems. • Proposing distribution systems planning via parallel and decomposition techniques. • Proposing RES and ESS allocation in MV/LV large-scale distribution systems planning. The world energy demand is increasing. Currently, most electricity generation sources are fossil fuels. In recent years, the global energy matrix for power generation is changing, in order to meet the demand with minimal environmental impacts. In this context, a new approach to solve the medium- (MV) and low- voltage (LV) planning of large-scale distribution systems via parallel computing and decomposition techniques is proposed. The mathematical formulation considers the allocation of substations, distribution transformers, MV and LV circuits, support structures, poles, renewable energy sources (RES), and energy storage sources (ESS). In addition, variable costs related to the operation of RES and ESS, power losses in cables, distribution transformers and substations, energy purchased from substations, and greenhouse gas emissions are also taken into account. System reliability and maintenance costs of these devices are also considered in the planning. To evaluate the new methodology performance, tests in a large-scale distribution system with 200 nodes in MV and 1672 nodes in LV is considered. Numerical results show the proposed methodology is able to find good solutions that guarantee the minimization of planning costs considering RES and ESS allocation. Furthermore, system reliability is improved by up to 22% and greenhouse gas emissions mitigation by up to 18%. [ABSTRACT FROM AUTHOR]