7,327 research outputs found

    Reliability and cost evaluation of small isolated power systems containing photovoltaic and wind energy

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    Renewable energy application in electric power systems is growing rapidly worldwide due to enhanced public concerns for adverse environmental impacts and escalation in energy costs associated with the use of conventional energy sources. Photovoltaics and wind energy sources are being increasingly recognized as cost effective generation sources. A comprehensive evaluation of reliability and cost is required to analyze the actual benefits of utilizing these energy sources. The reliability aspects of utilizing renewable energy sources have largely been ignored in the past due the relatively insignificant contribution of these sources in major power systems, and consequently due to the lack of appropriate techniques. Renewable energy sources have the potential to play a significant role in the electrical energy requirements of small isolated power systems which are primarily supplied by costly diesel fuel. A relatively high renewable energy penetration can significantly reduce the system fuel costs but can alsohave considerable impact on the system reliability. Small isolated systems routinely plan their generating facilities using deterministic adequacy methods that cannot incorporate the highly erratic behavior of renewable energy sources. The utilization of a single probabilistic risk index has not been generally accepted in small isolated system evaluation despite its utilization in most large power utilities. Deterministic and probabilistic techniques are combined in this thesis using a system well-being approach to provide useful adequacy indices for small isolated systems that include renewable energy. This thesis presents an evaluation model for small isolated systems containing renewable energy sources by integrating simulation models that generate appropriate atmospheric data, evaluate chronological renewable power outputs and combine total available energy and load to provide useful system indices. A software tool SIPSREL+ has been developed which generates risk, well-being and energy based indices to provide realistic cost/reliability measures of utilizing renewable energy. The concepts presented and the examples illustrated in this thesis will help system planners to decide on appropriate installation sites, the types and mix of different energy generating sources, the optimum operating policies, and the optimum generation expansion plans required to meet increasing load demands in small isolated power systems containing photovoltaic and wind energy sources

    Integration of renewable energy sources: reliability-constrained power system planning and operations using computational intelligence

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    Renewable sources of energy such as wind turbine generators and solar panels have attracted much attention because they are environmentally friendly, do not consume fossil fuels, and can enhance a nation’s energy security. As a result, recently more significant amounts of renewable energy are being integrated into conventional power grids. The research reported in this dissertation primarily investigates the reliability-constrained planning and operations of electric power systems including renewable sources of energy by accounting for uncertainty. The major sources of uncertainty in these systems include equipment failures and stochastic variations in time-dependent power sources. Different energy sources have different characteristics in terms of cost, power dispatchability, and environmental impact. For instance, the intermittency of some renewable energy sources may compromise the system reliability when they are integrated into the traditional power grids. Thus, multiple issues should be considered in grid interconnection, including system cost, reliability, and pollutant emissions. Furthermore, due to the high complexity and high nonlinearity of such non-traditional power systems with multiple energy sources, computational intelligence based optimization methods are used to resolve several important and challenging problems in their operations and planning. Meanwhile, probabilistic methods are used for reliability evaluation in these reliability-constrained planning and design. The major problems studied in the dissertation include reliability evaluation of power systems with time-dependent energy sources, multi-objective design of hybrid generation systems, risk and cost tradeoff in economic dispatch with wind power penetration, optimal placement of distributed generators and protective devices in power distribution systems, and reliability-based estimation of wind power capacity credit. These case studies have demonstrated the viability and effectiveness of computational intelligence based methods in dealing with a set of important problems in this research arena

    Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System

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    Due to the inherent aleatory uncertainties in renewable generators, the reliability/adequacy assessments of distributed generation (DG) systems have been particularly focused on the probabilistic modeling of random behaviors, given sufficient informative data. However, another type of uncertainty (epistemic uncertainty) must be accounted for in the modeling, due to incomplete knowledge of the phenomena and imprecise evaluation of the related characteristic parameters. In circumstances of few informative data, this type of uncertainty calls for alternative methods of representation, propagation, analysis and interpretation. In this study, we make a first attempt to identify, model, and jointly propagate aleatory and epistemic uncertainties in the context of DG systems modeling for adequacy assessment. Probability and possibility distributions are used to model the aleatory and epistemic uncertainties, respectively. Evidence theory is used to incorporate the two uncertainties under a single framework. Based on the plausibility and belief functions of evidence theory, the hybrid propagation approach is introduced. A demonstration is given on a DG system adapted from the IEEE 34 nodes distribution test feeder. Compared to the pure probabilistic approach, it is shown that the hybrid propagation is capable of explicitly expressing the imprecision in the knowledge on the DG parameters into the final adequacy values assessed. It also effectively captures the growth of uncertainties with higher DG penetration levels

    Reducing Voltage Volatility with Step Voltage Regulators: A Life-Cycle Cost Analysis of Korean Solar Photovoltaic Distributed Generation

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    To meet the United Nation’s sustainable development energy goal, the Korean Ministry of Commerce announced they would increase renewable energy generation to 5.3% by 2029. These energy sources are often produced in small-scale power plants located close to the end users, known as distributed generation (DG). The use of DG is an excellent way to reduce greenhouse gases but has also been found to reduce power quality and safety reliability through an increase in voltage volatility. This paper performs a life-cycle cost analysis on the use of step voltage regulators (SVR) to reduce said volatility, simulating the impact they have on existing Korean solar photovoltaic (PV) DG. From the data collected on a Korean Electrical Power Corporation 30 km/8.2 megawatts (MW) feeder system, SVRs were found to increase earnings by one million USD. SVR volatile voltage mitigation increased expected earnings by increasing the estimated allowable PV power generation by 2.7 MW. While this study is based on Korean PV power generation, its findings are applicable to any DG sources worldwide.11Nsciescopu

    A critical evaluation of deterministic methods in size optimisation of reliable and cost effective standalone Hybrid renewable energy systems

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    Reliability of a hybrid renewable energy system (HRES) strongly depends on various uncertainties affecting the amount of power produced by the system. In the design of systems subject to uncertainties, both deterministic and nondeterministic design approaches can be adopted. In a deterministic design approach, the designer considers the presence of uncertainties and incorporates them indirectly into the design by applying safety factors. It is assumed that, by employing suitable safety factors and considering worst-case-scenarios, reliable systems can be designed. In fact, the multi-objective optimisation problem with two objectives of reliability and cost is reduced to a single-objective optimisation problem with the objective of cost only. In this paper the competence of deterministic design methods in size optimisation of reliable standalone wind-PV-battery, wind-PV-diesel and wind-PV-battery-diesel configurations is examined. For each configuration, first, using different values of safety factors, the optimal size of the system components which minimises the system cost is found deterministically. Then, for each case, using a Monte Carlo simulation, the effect of safety factors on the reliability and the cost are investigated. In performing reliability analysis, several reliability measures, namely, unmet load, blackout durations (total, maximum and average) and mean time between failures are considered. It is shown that the traditional methods of considering the effect of uncertainties in deterministic designs such as design for an autonomy period and employing safety factors have either little or unpredictable impact on the actual reliability of the designed wind-PV-battery configuration. In the case of wind-PV-diesel and wind-PV-battery-diesel configurations it is shown that, while using a high-enough margin of safety in sizing diesel generator leads to reliable systems, the optimum value for this margin of safety leading to a cost-effective system cannot be quantified without employing probabilistic methods of analysis. It is also shown that deterministic cost analysis yields inaccurate results for all of the investigated configurations

    Energy Production Analysis and Optimization of Mini-Grid in Remote Areas: The Case Study of Habaswein, Kenya

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    Rural electrification in remote areas of developing countries has several challenges which hinder energy access to the population. For instance, the extension of the national grid to provide electricity in these areas is largely not viable. The Kenyan Government has put a target to achieve universal energy access by the year 2020. To realize this objective, the focus of the program is being shifted to establishing off-grid power stations in rural areas. Among rural areas to be electrified is Habaswein, which is a settlement in Kenya’s northeastern region without connection to the national power grid, and where Kenya Power installed a stand-alone hybrid mini-grid. Based on field observations, power generation data analysis, evaluation of the potential energy resources and simulations, this research intends to evaluate the performance of the Habaswein mini-grid and optimize the existing hybrid generation system to enhance its reliability and reduce the operation costs. The result will be a suggestion of how Kenyan rural areas could be sustainably electrified by using renewable energy based off-grid power stations. It will contribute to bridge the current research gap in this area, and it will be a vital tool to researchers, implementers and the policy makers in energy sector
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