Academic literature on the topic 'Electric utilities - Data processing'

Electric power quality is a critical issue for electric utilities and their customers and identification of the power quality disturbances is an important task in power system monitoring and protection. Offline processing of power quality disturbances provides an economic alternative for electric distribution companies, not capable of buying enough number of power quality analyzers for monitoring the disturbances online. Due to the wide frequency range of the disturbances which may happen in a power system, a high sampling rate is necessary for digital processing of the disturbances. Therefore, a large volume of data must be processed for this purpose for each node of an electric distribution network and such a processing has not yet been practical. However, thanks to the rapid developments of digital processors and computer networks, processing big databases is not so hard today. Apache Hadoop is an open-source software framework that allows for the distributed processing of large datasets using simple programming models. In this paper, application of Hadoop distributed computing software for offline processing of power quality disturbances is proposed and it is shown that this application makes such a processing possible and leads to a very cheaper system with widespread usage, compared to the power quality analyzers.

This paper describes Electric Power Research Institute (EPRI) sponsored case studies of two nuclear power plants that automated their maintenance management system in an effort to improve maintenance processing. These case studies evaluated the impact of an automated maintenance management system (AMMS) on the organizational interfaces and information requirements of a variety of system users. The goal of the project was to provide guidance to the electric power industry in maintenance management system design. A product of the investigation was a set of guidelines for use by utilities in conducting a front-end functional requirements analysis to help define major information requirements and organizational and data file interfaces.

In recent years, the problem of electrical load forecasting gained attention due to the arrival of new measurement technologies that produce electrical energy consumption data at very short intervals of time. Such short term measurements become voluminous in very short time. The availability of big electrical consumption data allows machine learning techniques to be employed to analyze consumption behavior of every consumer on a greater detail. Predicting the consumption of a residential customer is crucial at this point of time because tailor-made consumer-specific tariffs will play a vital role in load balancing process of Utilities. This paper analyzes the electrical consumption of a single residential customer measured using a smart meter that is capable of measuring electrical consumption at circuit level. The issues and challenges in collecting the data and pre-processing required for making them suitable for data analytics are discussed in detail. A comparison of the performance of different machine learning algorithms implemented using Python’s Scikit-learn module gives an insight on the consumption pattern.

Wireless sensor networks have been extensively deployed in the electric power systems for sensing, transmission and control, which provide more opportunities for wireless low power radios to operate. As the next generation electricity system, the smart grid should possess the capability to transmit reliable and real-time information to the control centers of the utilities. In order to solve the issues such as heterogeneous coexistence, spectrum scarcity, tremendous data processing and Security guarantees, revolutionary communication architecture is urgently demanded. In this paper, after analyzing the hierarchical structure of smart grid and illustrating the principle of WCSN in smart grids, we propose the security architecture of wireless sensor networks based on cognitive radio for smart grids, which can be used as a reference to design and develop the Wireless Cognitive Sensor Network (WCSN) security schemes in the electric power systems.

This study, a follow-up of one published in 1979, reports the results of a questionnaire concerning the twelve-hour shift that was sent to human resource management executives at 23 chemical, petroleum, pharmaceutical, and cosmetic companies in 1987. Respondents from all 11 chemical companies and 4 petroleum companies that returned the form indicated they were using the shift. Most of them reported that the shift was popular with employees, largely because of the longer periods of time off and greater freedom on weekends and evenings it provides. The twelve-hour shift is also widely used in the mini-steel and offshore oil drilling industries, and it is used to a limited extent in paper manufacturing, data processing, metal can manufacturing, and electric utilities.

Public facilities are part of residential area that is provided by developer for the public interest. The public facilities available at Jeulingke Residence such as road, sanitation, drainage, clean water, and electric network. Based on the Republic of Indonesia Law Number 1 of 2011, and Minister of Public Housing Regulation Number 22 / PERMEN / M / 2008, Jeulingke Residence housing still has inadequate public facilities such as worship place, green area, and waste. The purpose this research to identify indicators of public facilities that provide satisfaction for residents of Jeulingke Residence, and identify dominant factors of public facilities that can provide satisfaction for residents of Jeulingke Residence. Respondents in this study were owners at Jeulingke Residence. The sample in this study was 150 people. The sampling technique used was proportionate stratified random sampling. The factors evaluated were infrastructure, facilities, and public utilities. Data processing used validity test, and reliability test, while data analysis used descriptive analysis and factor analysis of Principle Component Analysis (PCA). The results showed that the factors of public facilities that could provide satisfaction for residents at Jeulingke Residence were infrastructure and facilities. The dominant factor of public facilities that gives satisfaction to residents at Jeulingke Residence is infrastructure with a variance of 68.942%. Indicators of infrastructure are road condition, drainage condition, sanitation condition, clean water condition, and electric network condition.

Recent advances in nanoscale resistive memory devices offer promising opportunities for in-memory computing with their capability of simultaneous information storage and processing. The relationship between current and memory conductance can be utilized to perform matrix-vector multiplication for data-intensive tasks, such as training and inference in machine learning and analysis of continuous data stream. This work implements a mapping algorithm of memory conductance for matrix-vector multiplication using a realistic crossbar model with finite cell-to-cell resistance. An iterative simulation calculates the matrix-specific local junction voltages at each crosspoint, and systematically compensates the voltage drop by multiplying the memory conductance with the ratio between the applied and real junction potential. The calibration factors depend both on the location of the crosspoints and the matrix structure. This modification enabled the compression of Electrocardiographic signals, which was not possible with uncalibrated conductance. The results suggest potential utilities of the calibration scheme in the processing of data generated from mobile sensing or communication devices that requires energy/areal efficiencies.

The article deals with the problem of unbalance of currents and voltages of communal utilities and the degree of correspondence of existing solutions to the level of informatization. The classification and structure of measures to reduce asymmetry, existing means and devices for balancing are considered. Particular attention is paid to the switching method of asymmetry’s correction. The advantages of this method in comparison with the others are indicated in the article. It is established that at present the realization of this method is associated with considerable labor costs for personnel with minimal automation of the process. A comparative analysis of devices based on the switching method of balancing with other devices is performed. Several examples of devices are given. It was found out that devices, the principle of operation of which is based on the switching method, require significantly less investment than other devices. The analysis of the correspondence between the level of automation of the balancing process and the capabilities of automated systems for data collection and processing is carried out. Several devices of automated systems for monitoring and accounting of electric power and automated devices for monitoring the quality of electricity were considered. It was found out that automated systems for monitoring and accounting of electric power, in spite of lower accuracy of measurements, have an advantage over automated systems for monitoring the quality of electric power in their greater prevalence. It is concluded that with the existing level of equipping networks with such systems, information on asymmetry can be obtained with the necessary accuracy and without additional capital investments. The conclusion is made that the problem is topical and because of the analysis of existing methods for reducing asymmetry, the task is formulated of developing new methods, the realization of which is possible with the help of an automated advisory system.

The electric power systems together with the entire energy sector are rapidly evolving towards a low-carbon, secure, and competitive economy facing revolutionary transformations from technical structure to economic value chain. Pathways to achieve sustainability led to the development of new technologies, accommodation of larger shares of unpredictable and stochastic electricity transfer from sources to end-users without loss of reliability, new business models and services, data management, and so on. The new technologies and incentives for local energy communities along with large development of microgrids are main forces driving the evolution of the low voltage energy sector changing the context and paradigm of rigid contractual binding between utilities and end-user customers (now progressing to flexible prosumers with generation and storage capabilities). The flexibility and operation of a prosumer can be enhanced by a non-intrusive time-frequency analysis of distorted power quality waveforms for both generation and demand at the point of common connection. Therefore, it becomes of importance to discriminate among successive quasi-steady-state operation of a given local system using only the aggregated waveforms information available in the PCC. This paper focuses on the Hilbert–Huang method with modifications such as empirical mode decomposition improved with masking signals based on the Fast Fourier Transform, Hilbert spectral analysis, and a post-processing method for separating components and their amplitudes and frequencies within distorted power signals for a low-voltage prosumer operation. The method is used for a time-frequency-magnitude representation with promising localization capabilities enabling efficient operation for prosumers.

The aim of this article is to present the influence of detector selection for the image-based Terrestrial Laser Scanning (TLS) registration method. The presented results are the extended continuation of investigations presented in the article, ‘The Influence of the Cartographic Transformation of TLS Data on the Quality of the Automatic Registration’. In order to obtain the correct results of the TLS registration process, it is necessary to detect and match the correct tie points, which are evenly distributed across the entire area. Commonly, for TLS data registration manually or semi-manually corresponding points are detected. However, when large, complicated cultural heritage objects are investigated, it is sometimes impossible to place marked control points. The only possibility of resolving this problem is the use of image-based TLS data registration. One of the most important factors that influences the quality and ability to use it correctly, is accurate selection. For this purpose, the authors decided to test three blob detectors ASIFT, SURF, CenSurE, and two point detectors FAST and BRISK. The results indicated that selection depends on two factors: if the time required for data processing is not important, the ASIFT algorithm should be used, which allows for full registration, but if not, a combination of other algorithms with results supervision should be considered.

Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Electrical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology 2014
The electric power utilities play a vital role in the generation, transmission and distribution of the electrical power to the end users. The power utilities face two major issues, i.e. i) power grids are expected to operate close to the maximum capacity, and ii) there is a need for accurate and better monitoring and control of the power system network using the modern technology and the available tools. These two issues are interconnected as better monitoring allows for better control of the power system. Development of the new standard-based power system technologies contributed to raising the ideas for building of a Smart grid. The challenges are that this process requires development of new control and operation architectures and methods for data acquisition, data transfer, and control computation. These methods require data for the full dynamic state of the power system in real-time, which leads to the introduction of the synchrophasor-based monitoring and control of the power system. The thesis describes the research work and investigations for integration of the existing new power system technologies to build fully automated systems for real-time solution of power system energy management problems, incorporating data measurement and acquisition, data transfer and distribution through a communication network, and data storage and retrieval in one whole system.

Many electric utilities have been tapping such energy sources as wind energy or conservation for years. However, the literature shows few attempts to incorporate such non-dispatchable energy sources as decision variables into the long-range planning methodology. In this dissertation, efficient algorithms for electric utility capacity expansion planning with renewable energy are developed. The algorithms include a deterministic phase which quickly finds a near-optimal expansion plan using derating and a linearized approximation to the time-dependent availability of non-dispatchable energy sources. A probabilistic second phase needs comparatively few computer-time consuming probabilistic simulation iterations to modify this solution towards the optimal expansion plan. For the deterministic first phase, two algorithms, based on a Lagrangian Dual decomposition and a Generalized Benders Decomposition, are developed. The Lagrangian Dual formulation results in a subproblem which can be separated into single-year plantmix problems that are easily solved using a breakeven analysis. The probabilistic second phase uses a Generalized Benders Decomposition approach. A depth-first Branch and Bound algorithm is superimposed on the two-phase algorithm if conventional equipment types are only available in discrete sizes. In this context, computer time savings accrued through the application of the two-phase method are crucial. Extensive computational tests of the algorithms are reported. Among the deterministic algorithms, the one based on Lagrangian Duality proves fastest. The two-phase approach is shown to save up to 80 percent in computing time as compared to a purely probabilistic algorithm. The algorithms are applied to determine the optimal expansion plan for the Tijuana-Mexicali subsystem of the Mexican electric utility system. A strong recommendation to push conservation programs in the desert city of Mexicali I results from this implementation.
Ph. D.

Computer professionals have been agents of change in many organizations. In some cases the role inadvertently became theirs as they were the ones at the vanguard of implementing the new information processing technology in organizations. While in other cases they were the catalysts for change, to force new methods/procedures onto lethargic organizations. While introducing change on others in the organization and adapting to new technological changes themselves, the computer professionals have not really had to face a significant change in their status, power, or importance to the organization. The introduction of the personal computer has brought about significant change in the way the job of the computer professional is perceived by many in the business world. While this change is personally affecting the way they do their job, there has not been a noticeable attempt by those managing computer professionals to deal with the human emotions engendered by such a change. Part of the reason for this lack of attention may be due to the lack of a model as to how computer professionals react to change. Such a model would provide a system whereby it would be possible to recognize where efforts could be made to measure, predict, and modify situations so that a smooth transition can be made to the change. Toward this end a model was developed which presents a system as to how computer professionals react to change. This dissertation presents the model, surveys a population of computer professionals, and analyzes the model using data gathered from the population. The data was gathered in the form of a self administered survey which was given to computer professionals working for six investor owned electric and gas utilities in the Northwestern United states. They answered questions on a scale of from one to five as to their emotions and perceptions about the introduction of personal computers into their organizations. These questions spanned the timeframe as the organizations migrated from the early beginnings of personal computer introduction, to a situation where the use of personal computers was widespread in the company. In the case of three of the companies the personal computer had not yet achieved widespread use at the time of the survey. The data gathered from the computer professionals was statistically analyzed to see if relationships exist between the model and the data. Additionally, interesting demographic data was analyzed to see if certain other factors affected the computer professional's perception as to the impact of the personal computer on their quality of worklife.

Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009
The purpose of this project is to develop methods for distribution network power quality' variations monitoring. Power quality (PO) has become a significant issue for both power suppliers and customers. There have been important changes in power system regarding to power quality requirements. "Power quality" is the combination at voltage quality and current quality. The main research problem of the project is to investigate the power quality of a distribution network by selection of proper measurement, applying and developing the existing classic and modern signal conditioning methods for power disturbance's parameters extracting and monitoring. The research objectives are: To study the standard lEC 61000-4-30 requirements. to investigate the common couplings in the distribution network. To identity the points for measurement, to develop MySQL database for the data from the measurement and to develop MATLAB software tor simulation of the network To develop methods based on Fourier transforms for estimation of the parameters of the disturbances. To develop software for the methods implementation, The influence of different loads on power quality disturbances are considered in the distribution network. Points on the network and meters according to the lEC power quality standards are investigated and applied for the CPUT Bellville campus distribution network. The implementation of the power quality monitoring for the CPUT Bellville campus helps the quality of power supply to be improved and the used power to be reduced. MATLAB programs to communicate with the database and calculate the disturbances and power quality parameters are developed.

The purpose of the thesis was to propose one set of solutions to some of the challenges that are delaying the adoption of utility computing on a wider scale. These components enable effective deployment of utility computing, efficient look-up, and comparison of service offerings of different utility computing resource centers connected to the utility computing network.

Individual systems or groups of systems related to the safety and operational I&C, and Electrical Systems (ES) are gradually replaced in existing Nuclear Power Plants (NPPs) as part of modernization projects. Modernizations are usually scheduled over multiple years. Different automation platform generations and safety-related product families are deployed to progressively replace legacy systems. Typically, each of the new I&C platforms and products have their own set of engineering tools. One challenge for the modernization of installed systems is the safety and security approval of these heterogeneous systems by regulatory bodies. A NPP consists of systems manufactured by different vendors which target different application domains, like Category A according to IEC 61226 for a Reactor Protection System, Category C for some Control Room Data Processing Systems or non-classified for auxiliary systems. Thus, replacing a legacy system by introducing a new one might bring in unknown risks, especially when the new system has more complex interfaces, e.g. when replacing an analog system by a digital system. Moreover, considering the time and budget limitations, commercial-off-the-shelf (COTS) hardware and software are also involved in modernization projects. In contrast to specialized equipment, vulnerabilities for COTS are widespread. On the other hand, existing security measures/mitigations are also required to reflect the system’s changes, e.g. mitigations for known vulnerabilities of COTS systems. In order to make an overall and integrated safety analysis after a system change in the frame of a modernization project, it is necessary to jointly consider these I&C systems targeting different application domains, in addition to the physical aggregates, like sensors, pumps and valves that interact with the physical processes. The restrictive deployment of wireless technologies may also be modeled and analyzed. While wireless is not deployed by legacy systems, it is being covered by new nuclear IEC standards, as some utilities intend to simplify selected I&C maintenance procedures that involve temporary data collection. The key modeling concepts consider new developments in the critical infrastructure and industrial automation domain. With the integrated modeling approach, different disciplines can be addressed, like probabilistic and deterministic safety analyses, security assessments, need for testing and specialized trainings.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.