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Renewable energy-based generation facilities emerging in microgrids are modifying many traditional principles of economic dispatch because of the variability and uncertainty of their output characteristics. Since the power generation from renewable resources is difficult to anticipate, a real-time adjustment of generation schedules is necessary after more forecast information becomes available. Intra-hour, or ultra-short-term dispatch, allows microgrid operators to frequently update generators’ outputs for providing power supplies efficiently in an uncertain operating condition. However, several technical challenges such as information availability, control architecture, and computational burden make it difficult to find an optimal generation schedule at runtime. This work addresses the intra-hour economic dispatch problem by designing a closed-loop distributed model predictive control (DMPC) that reduces potential variations in the determined generation schedules. At first, optimization problems regarding the behaviors of several participants in a microgrid are formulated. Then, the procedures for achieving the real-time power balance under ramp-rate constraints are detailed. Simulation results present the efficiency of the proposed DMPC for the optimal intra-hour economic dispatch when multiple types of generation resources are considered in a microgrid.

Distributed generation entities such as renewable energy sources have posed great challenges on power system economic dispatch because of their output variability and stochasticity. Accordingly, operators need to lessen unpredictable changes in scheduled generation settings by fully utilizing available forecast information in the decision-making process. This paper proposes a closed-loop algorithm for solving economic dispatch at runtime while reducing potential deviations of generation schedules. At first, a traditional centralized approach that addresses the economic dispatch problem is presented with discussions on potential enhancement enabled by model predictive control (MPC) techniques. The MPC application makes it possible for operators to address the concern of variability and stochasticity. This paper develops a dual decomposition-based distributed model predictive control (DDMPC) strategy that is compatible with consensus techniques. Different advantages of the proposed DDMPC are highlighted throughout the paper and are analyzed through simulations. The simulation results validate the advantages of the proposed DDMPC approach by comparing it with traditional techniques for economic dispatch and by another distributed method based on MPC.

The Republic of Colombia is a country situated in the northwest of South America, with territories in Central America. In 2005, the interconnected electricity system served 87% of the population, a percentage that is below the 95% average for Latin America and the Caribbean. The Colombian government is making massive efforts to increase the electrification, especially at very remote and rural places. However, there are still several rural communities isolated from the main grid in Colombia. Also, although some communities have already been connected to the distribution system, the security and reliability are still an issue. One key element in the effort of electrification is the use of very small microgrids projects called “nanogrids.” A nanogrid is a small power system that uses a combination of renewable and conventional energy sources to supply power to small local loads. The total load in a nanogrid is typically less than 20 kW, as an industrial site, small rural village. or a household. The generators are primarily based on clean energy such as solar arrays, wind turbines, and fuel cells. In Colombia, the Caribbean coastline, Andes Mountains, and strong agriculture provide the country with abundant distributed renewable energy resources that might largely surpass the fast-growing electricity demand. In this framework, the nanogrids emerge as a solution to supply energy for some communities, located far away from the network, improving the inhabitant’s quality of life. Moreover, the nanogrids might improve the security and reliability levels of the distribution system. This chapter discusses good practices and proposed some solutions to overcome challenges detected in nanogrid projects developed in Colombia. In essence, this chapter is a case study of nanogrid systems; it focuses on a full detailed explanation of 23 nanogrid projects developed in Colombia considering location, installed power, purpose, etc. Then the nanogrid projects are evaluated, and it gives the opportunity to identify some characteristics that hinder or benefit the operation of these systems. Some of them are the growth of the demand, the appropriate and inadequate use of energy and drinking water, the changes of habits in the users in the presence of energy or the increase in the reliability of the energy supply and how it affects the maintenance or lack this, the operation of the systems.

A hierarchical approach for the energy management of geographically close microgrids connected through a dedicated AC power network is proposed in this paper. The proposed approach consists of a two-layer energy management system (EMS) for networked microgrids. In the lower layer, each microgrid solves its own economic dispatch problem through a distributed model predictive control approach that respects capacity limits and ramp-rate constraints of distributed generation. In the upper layer, the energy trading in the network of microgrids decides how to optimally trade the energy based on the marginal cost information from the lower layer in order to improve global optimization objectives, e.g., social welfare. In order to solve the trading problem, a consensus-based algorithm and a replicator dynamics algorithm are proposed assuming that the marginal cost function of the microgrid is known and linear. It is shown that both algorithms converge to the same solution, which is equivalent to the minimization of operation costs. The consensus-based algorithm is extended in order to tackle more general marginal cost functions and trading network constraints. Moreover, the effect of ramp constraints and network limits is studied. Simulations show the effectiveness of the proposed algorithms for three interconnected microgrids with different characteristics.

Power system operation has been a very complex and interesting problem, and currently has gathered more attention because of new elements in the network. New elements such as renewable sources, demand response, electric vehicles, and energy storage systems, are crucial because of their stochastic behavior. Stochastic variables present new challenges for the system operator, who must prevent future changes in the network status by taking efficient decisions with available information and guarantee the system security. In this document we show that Model Predictive Control (MPC) might be appropriate to solve the economic dispatch problem when feasible future events are considered. A case study is solved from different perspectives of the system operator, which is able to consider or neglect future events. Results show that MPC efficiently solves the economic dispatch problem when considering future events and ramp rate constraints.

Achieving the Paris Agreement’s near-term goals (nationally determined contributions, or NDCs) and long-term temperature targets could result in pre-mature retirement, or stranding, of carbon-intensive assets before the end of their useful lifetime. We use an integrated assessment model to quantify the implications of the Paris Agreement for stranded assets in Latin America and the Caribbean (LAC), a developing region with the least carbon-intensive power sector in the world. We find that meeting the Paris goals results in stranding of $37–90 billion and investment of $1.9–2.6 trillion worth of power sector capital (2021–2050) across a range of future scenarios. Strengthening the NDCs could reduce stranding costs by 27%–40%. Additionally, while politically shielding power plants from pre-mature retirement or increasing the role of other sectors (e.g. land-use) could also reduce power sector stranding, such actions could make mitigation more expensive and negatively impact society. For example, we find that avoiding stranded assets in the power sector increases food prices 13%, suggesting implications for food security in LAC. Our analysis demonstrates that climate goals are relevant for investment decisions even in developing countries with low emissions.

Power systems operation has been traditionally addressed by deterministic and centralized approaches because of their low-variation behavior. However, current tendencies have introduced variability and stochasticity as a result of including renewable energy sources, active demand participation, and short-term market clearing. Thereby, operators are looking for utilizing available forecast information to enhance the system operation response to unpredictable changes from the uncertainty sources. This paper considers two distributed techniques that solve the economic dispatch problem in an hourly basis and for the ultra-short term, and a data-driven scenario generation method that reduces uncertainty impacts on operation costs. At first, the hourly and ultra-short term dispatches are presented as stochastic programming problems by relying on model predictive control (MPC), which also address the concern of variability and uncertainty. Second, since ultra-short term dispatch does not optimize the social benefit, we provide a hierarchical configuration that allows operators to efficiently coordinate it with the hourly approach to obtain enhanced operation costs. The simulation results validate the advantages of using stochastic programming instead of deterministic approaches under smart grids framework and show how a hierarchical coordination of both methods provides enhanced results. Additionally, computational time has been tested and it has been successfully shown that the proposed methods maintain a reasonable computational burden even for high complexity cases.

Planning of protection systems plays a significant role to achieve an efficient behavior (or performance) of distribution systems. Feeders that offer high robustness and reliability are essential to ensure continuous energy delivering to all customer loads. Since distributed generation (DG) has increased its penetration in distribution systems, it has become necessary to place protective devices (such as reclosers) in order to allow DG islanded operation, which decreases the energy not supplied. This paper addresses efficient placement of protective switches, which mainly comprises circuit breakers and reclosers. Two optimization approaches are proposed to enhance reliability indices. First, a single objective optimization problem is defined to maximize the profit of the distribution system operator. Such problem is solved through implementing the differential evolution algorithm (DE). Second, a multi-objective optimization problem is defined to reduce the system average interruption duration index (SAIDI), the system average interruption frequency index (SAIFI), and system costs. This approach yields optimal planning of switches by applying the non-dominated sorting differential evolution algorithm (NSDE). The heuristic algorithms are implemented in Matlab, while the power system is modeled in DIgSILENT in order to use a co-simulation environment between these two tools. Simulations are developed on a real test feeder for two cases: (i) without DG; and (ii) with 6 MW penetration of distributed sources. Results show the importance of both DG and protective devices to enhance reliability, and the effect of enabling intentional islanded operation.

This paper presents an economic model that aims to evaluate -from the regulatory perspective- the behavior of an aggregator capable of exploiting business opportunities of electric vehicles (EV) in the context of a wholesale electricity market. As a key contribution, we investigate the market equilibrium point when only one firm acts as an EV aggregator taking advantage of the management of the storage assets. To do so, a Stackelberg game is stated as a bi-level optimization problem where the maximization of the EV aggregator profit is regarded as the leader’s optimization problem, and the set of hourly economic dispatches and the corresponding locational marginal prices (LMPs) are determined by a benevolent system operator (the follower’s optimization problem). The model was applied in the IEEE RTS test system and the Colombian electricity market. The best solution for the EV aggregator does not require a significant share of the existing storage capacity. However, despite the loss of efficiency observed in the short-term energy market, the oligopolistic solution leads to flattening load curves and, therefore, a better use of the transmission and distribution infrastructure in the long term.

Hydro-dominated systems are characterized by uncertainty on the inflows to the reservoirs. Driven by both technological advances and environmental awareness, the share of renewables in the energy production mix has been increasing over the past decades. However, due to their intermittent nature, the integration of renewables entails additional uncertainty, which may negatively impact the operation of the system if the overall risk is not properly appraised. This work analyzes the impact of short-term wind variability on the long-term operation of a hydro-dominated power system based upon two risk measure approaches, namely (i) chance constrained programming, and (ii) conditional value-at-risk. Both approaches are formulated under the framework of stochastic dual dynamic programming. The proposals are tested on a portion of the Colombian power system, in the presence of wind energy and storage units.

Operation planning models for hydro-dominated power systems usually use low temporal resolutions due to the excessive computational burden, thus ignoring short-term characteristics of such systems. As a result, in systems coupled with wind energy, such models may fail to accurately capture wind variability, and may not appropriately take into account potential consequences of uncertainty on the system operation. This paper addresses this drawback by (i) “controlling” the cost associated with the operation of a hydro-dominated power system equipped with wind power and batteries via a risk-measure and (ii) formulating the short-term load balance as probabilistic constraints in order to hedge against potential extreme wind power scenarios. The risk-averse scheme is embedded in the stochastic dual dynamic programming framework. Simulation results for a case study on a real industrial setting show that hedging the system against the short-term volatility of wind power contributes to mitigating the risk of excessive operations costs or load curtailments, and that the consideration of the decision maker risk profile contributes to decreasing the variability of the solutions. In addition, the results of the application also illustrate the potential of the scheme to assess the energy situation of a country or a region under the penetration of wind energy and batteries deployment. © 2019 Elsevier Ltd

The efficient planning of radial distribution feeders is important to ensure energy supply to load demands as suitable quality of the service is provided. This planning is usually separated into two decision-making stages, i.e., design of topology infrastructure and protection system shaping. Moreover, these stages are performed pursuing the achievement of multiple objectives such as costs minimization and reliability maximization. In consequence, a multi-stage and multi-objective optimization problem arises. In this paper, an efficient Pareto-based approach is proposed to solve the aforementioned kind of optimization. Infrastructure preparation considers possible interconnections between loads and installation of Distributed Generation (DG). Furthermore, the shaping of protection system considers the amount of devices as their efficient placement in the feeder. DG have been largely considered as an alternative to increase the operation performance of distribution systems (DSs), besides its merely function to provide energy. On the other hand, Non-Dominated Sorting Genetic Algorithm (NSGA-II) is implemented to solve each stage of the planning. Finally, simulations are applied on a 33-nodes test feeder with available sources to install DG

En este artículo se presentan los pronósticos de incorporación de reservas y de producción de hidrocarburos para el periodo 2013-2035, realizados por la Unidad de Planeación Minero Energética (UPME), a partir de un estudio adelantado por la firma Arthur D´Little. Para este trabajo se empleó la técnica de escenarios tomando en consideración el comportamiento de diversas variables internas y externas, así como su nivel de incertidumbre e impacto. Para los escenarios construidos se cuantifican las inversiones necesarias para su materialización. Los resultados del análisis muestran que el país tiene potencial para incorporar más de nueve mil millones de barriles de crudo y seis TPC de gas natural en los próximos años. Lo anterior dependerá del comportamiento de la inversión en exploración que a su vez estará en función del comportamiento de los precios del crudo a nivel internacional y de los avances en la gestión ambiental y social.

In light of the ongoing international discussions about the Nationally Appropriate Mitigation Action concept, this study takes instead a more ‘bottom-up’ approach through a comparative analysis of five studies of mitigation actions (MAs) in Brazil, Colombia, Chile, Peru and South Africa. The analysis shows that MAs are driven by both developmental and climate objectives. The character, scope, policy horizon and potential success of an action are closely linked to the developmental path of countries such that MAs that directly address poverty and development seem to have a better chance of being implemented since they address issues higher on the policy agenda of developing countries. Where international support is sought, all five countries have some existing measurement, reporting and verification (MRV) and technical competence capacity that can be built upon. The choice of MAs is evidently linked to institutional capacity (both for design and implementation of MAs and possible MRV), emissions profile and the relative resource endowments of countries. The policy environments – from highly planned to less coordinated – and time-horizons – from 4-year plans to 40-year scenarios – differ substantially between the countries. Thus, the comparative analysis underscores the diversity of possible MAs and capabilities and the concomitant need for flexibility in definition, design and implementation.

This paper applies the conceptual framework applied in the work of Oum et al. to hedge retailers against price-quantity fluctuations in spot electricity markets, and extends it to power generators, in order to design suitable power options with optimal strike prices from a market maker's perspective. These options are then used to hedge agents against price and quantity fluctuations by maximizing a static expected utility problem. An infinite collection of derivatives (“exotic option”) emerges as the solution of both price and quantity hedging. This exotic option is approximated with a portfolio composed by bonds, forward/futures contracts, and a fixed number of put and call options, employing a plausible replicating strategy. The theoretical framework is tested within the context of the Colombian power market, and is applied to month-ahead and quarterly-ahead hedging during on-peak hours. The proposal addresses major problems such as lack of liquidity and anonymity of the current bilateral electricity trading scheme in Colombia.

En este articulo se presenta un resumen del Proyecto DNP- Universidad de los Andes sobre " Clusters " en la industria minero energetica , que la Universidad de los Andes realizo para el Departamento Nacional de Planeacion. Para comenzar, se hace una sintesis de la metodologia empleada, que combino analisis de tipo macro con analisis de detalle. Mas adelante se exponen los hallazgos en cuanto a la caracterizacion y localizacion de las industrias minero energeticas y aquellas relacionadas. Se presentan las cuatro propuestas que se plantearon para aprovechar el crecimiento de esta industria mediante la generacion de valor. La primera propuesta esta relacionada con la estructuracion de la funcion de comercializacion para lograr mejoras en la productividad de la pequena y mediana mineria del carbon, la segunda con la creacion de un programa nacional de desarrollo de proveedores de bienes y servicios para la industria petrolera y de gran mineria. Las dos ultimas propuestas se enfocan en el desarrollo de conglomerados de negocios, la primera de la petroquimica y los plasticos en la region de Bolivar - Atlantico y la otra de los nuevos materiales plasticos en Bogota, con un papel protagonico de la academia. Es importante anotar el analisis y propuestas detalladas pueden encontrarse en los informes del proyecto.

In those countries where the electric production chain has been disintegrated, transportation utilities (transmission as well as distribution) are subject to regulation or are under supervised activity. Regulation of activities considered as natural monopolies in network economies requires knowing or assessing efficient capital and operating expenditures (CAPEX and OPEX) depending on the output levels. The problem of determining the tariffs that transmission utilities can charge is tightly related to efficient OPEX levels. This work discusses the use of Data Envelopment Analysis and Stochastic Frontier Analysis to determine efficient frontiers for the electricity transmission activity. The results include relative efficiency and productivity indexes, as well as benchmarking peers. This information can be useful to the regulator to foster efficient performance of transmission utilities.

En este documento se presentan los principales hallazgos del trabajo adelantado por las Universidades de los Andes y Nacional con el apoyo de Colciencias e ISAGEN, los cuales indican que: i) La penetración de las nuevas fuentes y tecnologías más limpias de producción de energía (no sólo de electricidad) en el país, tendrán como motivadores, en su orden, la diversificación de la canasta energética, la reducción de la dependencia de los combustibles fósiles (como es el caso de los biocombustibles), la minimización de los impactos ambientales y el impulso al desarrollo tecnológico e industrial. ii) La regulación del mercado de energía eléctrica no limita el desarrollo de estas fuentes y tecnologías para la generación eléctrica; sin embargo, la arquitectura del mercado y las reglas fueron definidas pensado en las fuentes y tecnologías convencionales y, en consecuencia, hay algunos ajustes que deben adelantarse para "nivelar el terreno de juego" para las renovables en el país, derivados de la consideración de todos los costos y beneficios externos de su instalación y operación, así como la participación de generación distribuida en las redes. iii) Es indispensable contar con esquemas de financiación adecuados a los más largos periodos de recuperación del capital de estas tecnologías; así mismo, que los inversionistas sean concientes de las complementariedades y beneficios que se pueden lograr en mercados, como los de reducción de emisiones, y que en el país se dé alguna prioridad al desarrollo tecnológico e instalación de algunas de estas fuentes, donde las condiciones sean las más favorables. This paper presents the main findings of the work carried out by Universidad de los Andes and Universidad Nacional de Colombia, with support from Colciencias - the Colombian National Science Development Institution) and ISAGEN, a power generation company. These results are briefed in the following items: i) The main drivers for penetration of new energy sources and cleaner Technologies (not only for electricity) in the country, will be in its order: energy basket diversification, reduction of dependence on fossil fuels (as it is the case of biofuels), minimization of environmental impact, and support to technology and industrial development. ii) Current regulation of the energy market is not explicitly against the development of these power sources and technologies, however the market architecture and rules were made thinking in conventional sources and technologies, then some adjustments should be carried out to "level de playing field" for renewable in the country, this should aim to include all external cost and benefits from its installation and operation, as well as from the participation of distributed generation in grids. iii) It is indispensable to have appropriate financial schemes for longer pay-back periods with these technologies, investors should be aware of the benefits and complementarities that can be achieved in power markets, such as emission reduction. In addition, governments should give some priority to in-country technology development and to the adoption of some of these sources when conditions are the most favourable.

Mediante una metodología basada en un modelo de optimización multiperiodo de mínimo costo y un modelo para la estimación de demandas de movilidad, se evalúan diferentes escenarios de movilidad y políticas regulatorias de carácter energético y ambiental para el transporte urbano del Área Metropolitana del Valle de Aburrá. Se espera que la metodología y herramientas desarrolladas apoyen y orienten el proceso de toma de decisiones sobre el transporte urbano local hacia la disminución de la emisión de contaminantes a la atmósfera. La metodología considera alta desagregación geográfica de la información para apoyar el proceso de planificación del territorio./ Through a methodology based on a minimum cost multi-period optimization model and a previous model for mobility demand estimation, there are assessed different mobility demand scenarios next to energy and environmental regulatory policies for the urban transportation of the Aburrá Valley. It is expected the developed methodology and tools to support and guide decision processes over urban transportation sector at a local scale pointing to diminish pollutant emissions to atmosphere. This methodology considers high geographic dissagregation level of the information to support territorial urban planning.

Uno de los retos más importantes para lograr los objetivos de la política energética es tener estrategias de coordinación efectiva. Los cuatro Planes Energéticos Nacionales propuestos a lo largo de los últimos quince años tienen objetivos sectoriales muy similares con algunas diferencias en su tratamiento transversal o instrumental. Aun cuando los objetivos trazados en estos planes siguen siendo válidos, las metas propuestas no se han alcanzado en su totalidad, lo cual indica que lo que se requiere hoy con mayor urgencia es una actualización de las estrategias. Es válido, entonces, preguntarse si las estrategias actuales han sido las más adecuadas para alcanzar las metas esperadas. En el contexto actual de manejo descentralizado de la economía, una de las tareas esenciales de la función de planeación es lograr la coordinación efectiva entre la multiplicidad de agentes (y principales) y objetivos, además de suministrar información confiable y oportuna para mejorar la toma de decisiones y definir políticas y estrategias para corregir y adaptar las soluciones obtenidas en mercados parciales, cuando sea necesario./ One of the most important challenges in order to achieve the goals of an energy policy is to have effective coordination strategies. Four National Energy Plans have been proposed in the last fifteen years with very similar sector objectives and minor differences in transversal and instrumental treatment. Even though the objectives laid are still valid the proposed goals have not been totally achieved thus indicating that the most urgent task is an strategy update. It is valid then to ask how adequate are the strategies used today. In the context of the economics decentralized management an essential task of the planning function is to achieve effective coordination among multiple agents (and principals) and objectives besides providing reliable and timely information for improved decision making and defining effective correction strategies for partial and incomplete market solutions as necessary.

This article evaluates the active demand-side participation in the Colombian electricity market as a strategy to mitigate the apparently market power. Real energy and price offers from years 2000 to 2014 are used to characterize the supply curves of the model. The model is developed as a potential game where the strategies available are each of the firms (mostly hydro-based) that are supposed to behave strategically. A replicator dynamics approach is used to obtain the Nash equilibrium of the game. The results show that for acceptable levels of demand-side participation the energy price is reduced in approximately 58% when firms have the opportunity to exercise market power. It is borne out the fact that an active demand-side participation helps improving the market efficiency reducing the ability to exercise market power, among others.

Planning of protection systems has been a significant task in order to achieve an efficient behavior of distribution systems. Feeders that offer high robustness and reliability are essential to ensure continuous energy delivering to all customer loads. Since distributed generation (DG) has increased its penetration in distribution systems, it has become necessary to place protective devices (such as reclosers) in order to allow DG islanded operation, which decreases the energy not supplied. This paper addresses efficient placement of normally closed reclosers (NCRs). A multi-objective optimization is defined to reduce SAIDI, SAIFI, and system costs. This approach yields optimal planning of NCRs by applying the non-dominated sorting differential evolution algorithm (NSDE). The NSDE is implemented in Matlab, while the power system is modeled in DigSILENT in order to employ a co-simulation environment. Simulations are developed on a real test feeder for two cases: i) without DG; and ii) with 6 MW penetration of distributed sources.

Planning the expansion of distribution systems (DS) is a nonlinear and combinatorial problem that combines technical and regulatory constraints. Commonly, the planning of DS is intended to achieve a radial topology to reduce its complexity. However, in a smart-grid context, distribution feeders are subject to reconfigurations to transfer load between feeders in failure events, or to compensate for voltage profile and power quality issues caused by distributed generation (DG). In this paper we propose a novel methodology for the planning of primary feeders, which considers the DS performance in both open and closedloop arrangements. To this end we introduce the concept of reach current, which we use to define and solve a minimum power-loss flow problem. We solve this problem for each type of conductor considered to find a set of primary-feeder candidates. Additionally, an efficiency evaluation is performed to select the best among the candidate primary feeders. Simulation results on a test system show how this method is able to capture open and closed-loop operations, explicitly considering DG in the DS expansion planning within a smart-grid scheme.

The evolution of distribution systems (DS) towards the smart-grid concept posses new challenges, triggered by the integration of distributed generation (DG) and the installation of new devices. These challenges raise the need to reconsider the traditional network operation during the planning stage, enabling the DS to be flexible to operate under different network configuration scenarios. In this paper we propose a DS planning methodology for the connection of support feeders in radial networks, explicitly considering reconfiguration options with open-and closed-loop operation. To this end, we propose an efficiency evaluation, based on Data Envelopment Analysis, to assess candidate feeders in terms of expansion costs, energy losses, and lines' chargeability, under a range of demand scenarios that include GD penetration. Additionally, we have developed a method to identify the main feeder in a radial system, obtaining a simplified version of the DS, better suited for analysis. Simulation results on a real urban DS show the effectiveness of the method to identify the best nodes in a main feeder to connect support feeders, further indicating how to divide the network into operation areas for an improved network performance.

This paper presents the approach undertaken, and the four energy scenarios that have been developed, to support long term energy policy in Colombia. The scenarios were constructed with emphasis on maximum interaction between stakeholders in the Colombian energy sector. The process directly involved over 120 people. The scenarios were developed as strategic support tools for the Energy and Mining Planning Unit (UPME), which is the Colombian institution in charge of developing the country's energy strategies and National Energy Policy. The methodology employed is presented, followed by a detailed description of each of the four scenarios.

This paper introduces the Colombian case study developed under the Mitigation Actions Plans and Scenarios Initiative and the Endesa Colombia Electric Vehicles Initiative. It is aimed to consider the use of electricity in the transportation sector, particularly in the city of Bogota, Colombia. A model for assessing the economic and environmental impacts of the introduction of electric vehicules for private, utility and public services is proposed. Diversification of the energy basket by introducing electricity in the transportation sector is a plausible development strategy for the country. Colombian electricity is relatively clean because of the high hydro component in the generation basket; therefore the substitution of fossil fuels for electricity represents net savings in emissions of greenhouse gases as well as a reduction of particulate matter. The increase in electricity demand as a result of this new use is not high enough to stress installed generation capacity or supply security.

Protection systems planning is essential to enhance the reliability of radial distribution feeders. This planning must consider the amount of devices as their efficient placement in the feeder. Moreover, distributed generation (DG) has been largely considered as an alternative to increase the operation performance of distribution systems, besides its merely function to provide energy. Protective devices, such as reclosers, allow DG to operate in island mode decreasing the non-supplied energy (ENS). In this paper, the economic theory of the firm, together with evolutionary algorithms, is used to derive the optimal planning of reclosers. A single objective optimization problem is developed in order to minimize the ENS. Furthermore, genetic algorithm (GA) and differential evolution (DE) are implemented to solve the decision making problem. Finally, Simulations are applied on a real test feeder in two cases: without DG and with 6 MW penetration of distributed sources.

When planning the expansion and operation of distribution systems (DS), utilities face a complex combination of technical and regulatory constraints, which must be considered together with the influence that investment decisions today have on the behavior of the DS along the planning horizon. We present a novel methodology for the multi-stage expansion and operation of a DS, considering a broad set of expansion options, such as the installation or repowering of substations and feeders, variations of the network topology, as well as the installation of distributed generators of various technologies and capacities. The problem is posed as a multi-objective optimization with two objectives: the cost of the energy delivered and the reliability of the network. The problem is solved with an evolutionary algorithm that finds a broad set of non-dominated solutions.

The grid expansion is the most usual alternative to increase the coverage of distribution utility in rural areas. However, this alternative has several constraints related with its costs, the dispersion of costumers, assets configuration (mostly radial), and reliability, among others. This paper summarizes the main issues concerning to supply the energy demand in rural areas. Technical and economic assessment methods are proposed to determine the best alternative that satisfies energy requirements in specific rural areas. Distributed Generation (DG) is suggested as a competitive option in two cases: islanded and interconnected operation. For each scenario, technical requirements are examined to be met. Similarly, an economic evaluation is performed and finally the results are contrasted.

A single-period day-ahead stochastic market-clearing mechanism that schedules large and Distributed Generators (DGs) to reliably supply the system demand is proposed. The mechanism considers the stochasticity of both, the system demand and the generation of variable DGs to satisfy a reliability criterion. The reserves provided by large generators, are endogenously determined by the scheduling mechanism. The mechanism allocates in a cost-reflective manner the additional operational costs introduced by variable DGs in such a way that no entry barriers are imposed to them. Aiming to achieve the effective integration of DG within the proposed mechanism, flexibility rights are defined, and a further classification of DGs according to their generation capacity is proposed.

Technical and economic impacts of Distributed Generation on the Colombian extra-high and high voltage transmission network are analyzed in this paper. The transmission network (extra-high, high and medium voltage) is divided in geographical zones. DG capacity installation is modeled in some of those zones considering two different location criteria: nodal factors and declared investment options. Results show significant benefits of the introduction of DG in transmission power losses and congestion reduction as well as in voltage profile improvement.

Different energy markets in many countries have been put in place different programs to make electricity demand responsive to prices or reliability needs. In this work we evaluate the consequences of directly translating the prices from the wholesale energy market to the retail energy market as a mechanism to promote changes in energy consumption patterns. We use as a case study a non-regulated market in Colombia to measure the benefits of varying the consumption energy from one hour to another (peak and non-peak hour). We also propose some performance metrics that help utilities and system operators recognize the value of implementing demand response programs. Results show benefits of approximately two hundred million of COP annually and peak reductions of 1%, but these benefits depend on the number of clients who participate in these programs and their load curves.

In liberalized hydro-dominated power supply systems, the way managers use the knowledge they have about water levels in order to make production decisions impacts both their market power potential and the market outcomes. Assuming that the corresponding risk can be priced, we develop a dynamic hydro-dominated oligopolistic modeling framework to discuss the strategic cost of hydroelectric resources, in the context of the short-term marginal opportunity cost of storable electricity. As our contribution over previous approaches we construct a criterion embodying in a single number the strategic cost of hydropower production decisions. This criterion is built through the use of an indifference (risk-neutral) argument regarding the expected profits associated to a particular production strategy. Our result enables us to define regulatory policies to mitigate the market power potential of oligopolistic hydro-dominated producers, and to define socially optimum water allocation policies. We use data from the Colombian power market to run an informal check of the plausibility of our findings.

Firm energy market proposal for the Colombian electricity market is analyzed. It is based in a product: firm energy - the ability to provide electricity in a dry period - and it includes a financial call option and the physical capability to supply firm energy. This new market coordinates investment in new resources to assure that sufficient firm energy is available in dry periods. Load will be procured under a descendent clock auction format. Although, auctions has been the most efficient allocation mechanism, questions about the possible outcomes using the allocation format designed, and the incentives that participants have to collude or deviate from the true strategies have not been solved, neither questions about the way participants must behave (supply curve shape). This paper summarizes the research work in order to give solution to these problems under a simple methodological approach simulating agents' behavior in auction simulated exercises.

In this paper we evaluate a heuristic methodology to obtain the optimal placement and size of distributed generation in order to minimize the distribution utilitypsilas cost. Technical aspects like energy losses and voltage levels are considered, as well as economic aspects like price of energy, investment and operating cost of distributed generation and cost of losses. We use the IEEE 13 nodes test feeder.

This study offers insights about the identification of joint implementation (JI) projects to curb carbon dioxide (CO2) emissions in Colombia, which Switzerland could finance to comply with emission reduction commitments. The method uses MARKAL, a bottom-up engineering model of the energy system. Based on the Colombian MARKAL model, this study determines first a baseline CO2 emission path in Colombia. Using a Swiss-Colombian joint MARKAL model, this study then considers a cooperation between Switzerland and Colombia to curb jointly CO2 emissions. The joint model minimises the total energy and emission control cost of the two countries to reach global CO2 emission reduction targets. It enables JI projects in the Colombian energy system to be identified, and illustrates the benefits to be gained through international cooperation to reduce CO2 emissions.