A Reserve-Based Method for Mitigating the Impact of Renewable Energy

The fundamental operating paradigm of today\u27s power systems is undergoing a significant shift. This is partially motivated by the increased desire for incorporating variable renewable energy resources into generation portfolios. While these generating technologies offer clean energy at zero marginal cost, i.e. no fuel costs, they also offer unique operating challenges for system operators. Perhaps the biggest operating challenge these resources introduce is accommodating their intermittent fuel source availability. For this reason, these generators increase the system-wide variability and uncertainty. As a result, system operators are revisiting traditional operating strategies to more efficiently incorporate these generation resources to maximize the benefit they provide while minimizing the challenges they introduce. One way system operators have accounted for system variability and uncertainty is through the use of operating reserves. Operating reserves can be simplified as excess capacity kept online during real time operations to help accommodate unforeseen fluctuations in demand. With new generation resources, a new class of operating reserves has emerged that is generally known as flexibility, or ramping, reserves. This new reserve class is meant to better position systems to mitigate severe ramping in the net load profile. The best way to define this new requirement is still under investigation. Typical requirement definitions focus on the additional uncertainty introduced by variable generation and there is room for improvement regarding explicit consideration for the variability they introduce. An exogenous reserve modification method is introduced in this report that can improve system reliability with minimal impacts on total system wide production costs. Another potential solution to this problem is to formulate the problem as a stochastic programming problem. The unit commitment and economic dispatch problems are typically formulated as deterministic problems due to fast solution times and the solutions being sufficient for operations. Improvements in technical computing hardware have reignited interest in stochastic modeling. The variability of wind and solar naturally lends itself to stochastic modeling. The use of explicit reserve requirements in stochastic models is an area of interest for power system researchers. This report introduces a new reserve modification implementation based on previous results to be used in a stochastic modeling framework. With technological improvements in distributed generation technologies, microgrids are currently being researched and implemented. Microgrids are small power systems that have the ability to serve their demand with their own generation resources and may have a connection to a larger power system. As battery technologies improve, they are becoming a more viable option in these distributed power systems and research is necessary to determine the most efficient way to utilize them. This report will investigate several unique operating strategies for batteries in small power systems and analyze their benefits. These new operating strategies will help reduce operating costs and improve system reliability

The political economy of decarbonisation: exploring the dynamics of South Africa’s electricity sector

South Africa’s coal-dominated electricity sector, a key feature of the country’s minerals-energy complex, is in crisis and subject to change. This offers potential opportunities for decarbonisation. Despite positive examples of decarbonisation in South Africa’s electricity sector, such as a procurement programme for renewable energy, there are structural path dependencies linked to coal-fired generation and security of supply. Decarbonisation goes far beyond what is technologically or even economically feasible, to encompass a complexity of political, social and economic factors. Meanwhile, decision-making in electricity is highly politicised and lack of transparency and power struggles in the policy sphere pose key challenges. Such power struggles are reflected in national debates over which technologies should be prioritised and the institutional arrangements that should facilitate them

The Value of Grid-Scale Variable Renewable Energy Generation in Sub-Saharan Africa

This report was produced for the Green Growth Diagnostics for Africa project, funded by the Engineering and Physical Sciences Research Council.Securing a sufficient supply of reliable and affordable electricity is a huge challenge for countries in sub-Saharan Africa. Many countries in the region are experiencing rapid increases in the size of their populations, and even more rapid growth in their economies. As a result, the region experienced a 45 per cent increase in annual energy consumption between the years 2000-2014, with the growth in some countries much higher. This article surveys the most relevant research, policies and sources of data relevant to generation adequacy assessment in two example SSA countries: Kenya and Ghana. It also includes an exploratory analysis of the temporal relationships between the hydro resource, wind resource and power demand in Kenya, with an emphasis on assessing the impact of limited data availability

Understanding the Impact of Large-Scale Power Grid Architectures on Performance

Grid balancing is a critical system requirement for the power grid in matching the supply to the demand. This balancing has historically been achieved by conventional power generators. However, the increasing level of renewable penetration has brought more variability and uncertainty to the grid (Ela, Diakov et al. 2013, Bessa, Moreira et al. 2014), which has considerable impacts and implications on power system reliability and efficiency, as well as costs. Energy planners have the task of designing infrastructure power systems to provide electricity to the population, wherever and whenever needed. Deciding of the right grid architecture is no easy task, considering consumers’ economic, environmental, and security priorities, while making efficient use of existing resources. In this research, as one contribution, we explore associations between grid architectures and their performance, that is, their ability to meet consumers’ concerns. To do this, we first conduct a correlation analysis study. We propose a generative method that captures path dependency by iteratively creating grids, structurally different. The method would generate alternative grid architectures by subjecting an initial grid to a heuristic choice method for decision making over a fixed time horizon. Second, we also conduct a comparative study to evaluate differences in grid performances. We consider two balancing area operation types, presenting different structures and coordination mechanisms. Both studies are performed with the use of a grid simulation model, Spark! The aim of this model is to offer a meso-scale solution that enables the study of very large power systems over long-time horizons, with a sufficient level of fidelity to perform day-to-day grid activities and support architectural questions about the grids of the future. More importantly, the model reconciles long-term planning with short-term grid operations, enabling long-term projections validation via grid operations and response on a daily basis. This is our second contribution

Sustainable generation mix as a reference in effective design of electricity market structures and rules

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Operating risk analysis of wind integrated generation systems

Wind power installations are growing rapidly throughout the world due to environmental concerns associated with electric power generation from conventional generating units. Wind power is highly variable and its uncertainty creates considerable difficulties in system operation. Reliable operation of an electric power system with significant wind power requires quantifying the uncertainty associated with wind power and assessing the capacity value of wind power that will be available in the operating lead time. This thesis presents probabilistic techniques that utilize time series models and a conditional probability approach to quantify the uncertainty associated with wind power in a short future time, such as one or two hours. The presented models are applied to evaluate the risk of committing electric power from a wind farm to a power system. The impacts of initial wind conditions, rising and falling wind trends, and different operating lead times are also assessed using the developed methods. An appropriate model for day-ahead wind power commitment is also presented. Wind power commitment for the short future time is commonly made equal to, or a certain percentage, of the wind power available at the present time. The risk in meeting the commitment made in this way is different at various operating conditions, and unknown to the operator. A simplified risk based method has been developed in this thesis to assist the operator in making wind power commitments at a consistent level of risk that is acceptable to the system. This thesis presents a methodology to integrate the developed short-term wind models with the conventional power generation models to evaluate the overall operational reliability of a wind integrated power system. The area risk concept has been extended to incorporate wind power, evaluate the unit commitment risk and the well- being indices of a power system for a specified operating lead time. The method presented in this thesis will assist the operator to determine the generator units and the operating reserve required to integrate wind power and meet the forecast load for a short future time while maintaining an acceptable reliability criterion. System operators also face challenges in load dispatch while integrating wind power since it cannot be dispatched in a conventional sense, and is accepted as and when present in current operational practices. The thesis presents a method to evaluate the response risk and determine the unit schedule while satisfying a specified response risk criterion incorporating wind power. Energy storage is regarded as an effective resource for mitigating the uncertainty of wind power. New methods to incorporate energy storage with wind models, and with wind-integrated power system models to evaluate the wind power commitment risk and unit commitment risk are presented in this thesis. The developed methods and the research findings should prove useful in evaluating the operating risks to wind farm operators and system operators in wind integrated power systems

Nuclear Power Plants

This book will shed light on some hot topics related to nuclear power plants starting from uranium ore processing to fabrication through enrichment and finally to nuclear fuel at nuclear reactors. This book will hopefully encourage researchers and scientists to look further into the advantages of nuclear power plants in the production of cheap electricity with low fuel cost

Decision aiding in off-grid electrification projects: the role of uncertainty acknowledgement and objectives alignment

Most completed South African off-grid electrification projects have failed to contribute significantly to the sustainable development of the communities they supply. The hypothesis of this research is that the root causes of these failures can often be found in the pre-implementation decision making (planning) processes, specifically in three areas: 1. Decision aiding approaches and tools, aimed at supporting the decision making process, are either not used or do not support high quality decisions. 2. Uncertainties that can impact the project negatively are often not acknowledged (identified) initially, and can therefore not be addressed proactively. 3. The primary project objectives often do not align with sustainable development objectives, which mean that even if all the project objectives are achieved (i.e. a successful project) the project still does not contribute to sustainable development. The process of validating this hypothesis results in several outputs aimed at improving the contribution of future off-grid electrification projects to sustainable development: A framework of primary energisation objectives for sustainable development is developed, which defines what the outcomes of a successful off-grid electrification project should be. High quality decision making is defined, and a framework of decision aiding characteristics that support high quality decision making is developed against which decision aiding approaches and tools can be evaluated. The concept of soft and hard uncertainties is introduced, and it is shown that most of the social and institutional unacknowledged uncertainties in South African off-grid projects are hard. Hard uncertainties are impossible to represent probabilistically, and are difficult to include in traditional single-dimensional (mostly cost-based) decision aiding approaches and tools. A degree of surprise tool, based on Shackle's measure of a decision maker's degree of surprise at a future outcome becoming reality, is developed to act as an example of how hard uncertainty can be acknowledged in the decision making process. p14 - Abstract Soft uncertainty in the decision process is quantified for two examples: renewable energy system sizing, where an adequacy confidence index is proposed, and renewable energy resource estimation, where the accuracy and applicability of RETScreen and Homer within a South African climatic context are analysed. Finally, the above outputs are integrated into an existing decision aiding process and applied in order to demonstrate the value of decision aiding which includes uncertainty acknowledgement and objectives alignment. The applicability of the results of this research is not limited to off-grid electrification, and can be of value within any developmental project aligned with sustainable development, especially where social and institutional uncertainties are prevalent