Reliability analysis of distribution systems with photovoltaic generation using a power flow simulator and a parallel Monte Carlo approach

This paper presents a Monte Carlo approach for reliability assessment of distribution systems with distributed generation using parallel computing. The calculations are carried out with a royalty-free power flow simulator, OpenDSS (Open Distribution System Simulator). The procedure has been implemented in an environment in which OpenDSS is driven from MATLAB. The test system is an overhead distribution system represented by means of a three-phase model that includes protective devices. The paper details the implemented procedure, which can be applied to systems with or without distributed generation, includes an illustrative case study and summarizes the results derived from the analysis of the test system during one year. The goal is to evaluate the test system performance considering different scenarios with different level of system automation and reconfiguration, and assess the impact that distributed photovoltaic generation can have on that performance. Several reliability indices, including those related to the impact of distributed generation, are obtained for every scenario.Postprint (published version

Adequacy Evaluation of an Islanded Microgrid

The reliability of power converters has been extensively examined in terms of component- and converter level. However, in case of multiple generation units, the evaluation of the performance of power systems requires system-level modeling. This paper aims to merge the prior art of reliability modeling of power converters with the adequacy evaluation of power systems through an extensive design and evaluation analysis of a microgrid based case study. The methodology proposed in the paper integrates the device-level analysis into the domain of the conventional power system reliability analysis while outlining the steps needed to deal with non-exponential distributed failures of power electronic-based generation units. A replacement policy of the power electronic-based units is adopted by means of evaluating the system risk of not supplying system loads, and, finally, an approach on how to ensure a desired replacement frequency is outlined

RELIABILITY AND RESILIENCE EVALUATION OF A STAND-ALONE MOBILE MICROGRID-ANALYSIS AND EXPERIMENTAL MEASUREMENTS

As the Department of Defense (DOD) deploys renewable distributed energy resources (DERs) to reduce fossil fuel consumption, microgrids are being evaluated as one way to generate and deliver reliable electric power to stationary and mobile military units. Commercial off the Shelf (COTS) microgrid components are a viable cost-effective option to setup stand-alone microgrid systems to support mobile military units and help drive the transition to a more sustainable yet energy-resilient military. Reliability and resilience are key parameters in determining the effectiveness of microgrids in supporting military missions. Although in the past few years many researchers have presented reliability and resilience models of various complexity, experimental measurements and model validation are not available in the literature for mobile COTS microgrids. The goal of this thesis research is to experimentally assess the reliability and resilience of stand-alone, mobile microgrids that can be carried by one or two individuals and can be easily assembled in the field in support of operations in locations where utility power is not available. Utilizing COTS DERs including batteries, PV arrays and power converters, three different standalone microgrid architectures were designed, analyzed, and tested in the laboratory. Reliability block diagrams, and system fault trees were created per MIL-HDBK-338B, to compare the reliability of the three microgrid configurations.Major, United States Marine CorpsApproved for public release. Distribution is unlimited

OPERATIONAL RELIABILITY AND RISK EVALUATION FRAMEWORKS FOR SUSTAINABLE ELECTRIC POWER SYSTEMS

Driven by a confluence of multiple environmental, social, technical, and economic factors, traditional electric power systems are undergoing a momentous transition toward sustainable electric power systems. One of the important facets of this transformation is the inclusion of high penetration of variable renewable energy sources, the chief among them being wind power. The new source of uncertainty that stems from imperfect wind power forecasts, coupled with the traditional uncertainties in electric power systems, such as unplanned component outages, introduces new challenges for power system operators. In particular, the short-term or operational reliability of sustainable electric power systems could be at increased risk as limited remedial resources are available to the operators to handle uncertainties and outages during system operation. Furthermore, as sustainable electric power systems and natural gas networks become increasingly coupled, the impacts of outages in one network can quickly propagate into the other, thereby reducing the operational reliability of integrated electric power-gas networks (IEPGNs). In light of the above discussion, a successful transition to sustainable electric power systems necessitates a new set of tools to assist the power system operators to make risk-informed decisions amid multiple sources of uncertainties. Such tools should be able to realistically evaluate the hour- and day-ahead operational reliability and risk indices of sustainable electric power systems in a computationally efficient manner while giving full attention to the uncertainties of wind power and IEGPNs. To this end, the research is conducted on five related topics. First, a simulation-based framework is proposed to evaluate the operational reliability indices of generating systems using the fixed-effort generalized splitting approach. Simulations show improvement in computational performance when compared to the traditional Monte-Carlo simulation (MCS). Second, a hybrid analytical-simulation framework is proposed for the short-term risk assessment of wind-integrated power systems. The area risk method – an analytical technique, is combined with the importance sampling (IS)-based MCS to integrate the proposed reliability models of wind speed and calculate the risk indices with a low computational burden. Case studies validate the efficacy of the proposed framework. Third, the importance sampling-based MCS framework is extended to include the proposed data-driven probabilistic models of wind power to avoid the drawbacks of wind speed models. Fourth, a comprehensive framework for the operational reliability evaluation of IEPGNs is developed. This framework includes new reliability models for natural gas pipelines and natural gas-fired generators with dual fuel capabilities. Simulations show the importance of considering the coupling between the two networks while evaluating operational reliability indices. Finally, a new chance-constrained optimization model to consider the operational reliability constraints while determining the optimal operational schedule for microgrids is proposed. Case studies show the tradeoff between the reliability and the operating costs when scheduling the microgrids

Reliability assessment for electrical power generation system based on advanced Markov process combined with blocks diagram

This paper presents the power generation system reliability assessment using an advanced Markov process combined with blocks diagram technique. The effectiveness of the suggested methodology is based on HL-I of IEEE_EPS_24_bus. The proposed method achieved the generation reliability and availability of an electrical power system using the Markov chain which based on the operational transition from state to state which represented in matrix. The proposed methodology has been presented for reliability performance evaluation of IEEE_EPS_24_bus. MATLAB code is developed using Markov chain construction. The transition between probability states is represented using changing the failure and repair rates. The reduced number of generation system are used with Markov process to assess the availability, unavailability, and reliability for the generation system. Additionally, the proposed technique calculates the frequency, time duration of states, the probability of generation capacity state which get out of service or remained in service for each state of failure, and reliability indices. A considerable improvement in reliability indices is found with using blocks diagram technique which is used to reduce the infinity number of transition states and assess the system reliability. The proposed technique succeeded at achieving accurate and faster reliability for the power system

Microgrid availability during natural disasters

textA common issue with the power grid during natural disasters is low availability. Many critical applications that are required during and after natural disasters, for rescue and logistical operations require highly available power supplies. Microgrids with distributed generation resources along with the grid provide promising solutions in order to improve the availability of power supply during natural disasters. However, distributed generators (DGs) such as diesel gensets depend on lifelines such as transportation networks whose behavior during disasters affects the genset fuel delivery systems and as a result affect the availability. Renewable sources depend on natural phenomena that have both deterministic as well as stochastic aspects to their behavior, which usually results in high variability in the output. Therefore DGs require energy storage in order to make them dispatchable sources. The microgrids availability depends on the availability characteristics of its distributed generators and energy storage and their dependent infrastructure, the distribution architecture and the power electronic interfaces. This dissertation presents models to evaluate the availability of power supply from the various distributed energy resources of a microgrid during natural disasters. The stochastic behavior of the distributed generators, storage and interfaces are modeled using Markov processes and the effect of the distribution network on availability is also considered. The presented models supported by empirical data can be hence used for microgrid planning.Electrical and Computer Engineerin