Economic Sizing of Distributed Energy Resources for Reliable Community Microgrids

Community microgrids offer many advantages for power distribution systems. When there is an extreme event happening, distribution systems can be seamlessly partitioned into several community microgrids for uninterrupted supply to the end-users. In order to guarantee the system reliability, distributed energy resources (DERs) should be sized for ensuring generation adequacy to cover unexpected events. This paper presents a comprehensive methodology for DERs selection in community microgrids, and an economic approach to meet the system reliability requirements. Algorithms of discrete time Fourier transform (DTFT) and particle swarm optimization (PSO) are employed to find the optimal solution. Uncertainties of load demand and renewable generation are taken into consideration. As part of the case study, a sensitivity analysis is carried out to show the renewable generation impact on DERs' capacity planning.Comment: 5 pages, 6 figures, 1 table, 2017 IEEE Power & Energy Society General Meeting. arXiv admin note: substantial text overlap with arXiv:1708.0102

Optimum Renewable Generation Capacities in a Microgrid Using Generation Adequacy Study

Microgrids, as small power systems, may be comprised of different types of loads and distributed generation. As the integration of renewable power generation increases, the total available generation capacity of the system will be more derated due to the effect of equipment failures and the intermittent nature of these resources. Therefore, it is critical to determine optimum renewable generation capacities and provide enough reserve margin to meet the target reliability of the microgrid. In this paper, we first model a microgrid, including conventional and renewable distributed generation and the loads. Second, we determine the renewable generation capacity required to meet growth in demand at a certain level of grid reliability through a generation adequacy study. Adequacy of the microgrid is evaluated using parameters such as loss of load probability (LOLP) and expected energy not served (EENS). Third, the impact of different conditions, such as wind speed diversity (captured by correlating the wind power output), a combination of wind and solar power, and load diversity, on generation adequacy is studied through sensitivity analyses. Finally, the optimum renewable generation capacities are determined such that the total cost of generation and unserved power is minimized. The optimization process is based on the particle swarm optimization (PSO) method which uses Monte Carlo (MC) simulation for generation adequacy studies in each iteration

Optimum Renewable Generation Capacities in a Microgrid Using Generation Adequacy Study

Microgrids, as small power systems, may be comprised of different types of loads and distributed generation. As the integration of renewable power generation increases, the total available generation capacity of the system will be more derated due to the effect of equipment failures and the intermittent nature of these resources. Therefore, it is critical to determine optimum renewable generation capacities and provide enough reserve margin to meet the target reliability of the microgrid. In this paper, we first model a microgrid, including conventional and renewable distributed generation and the loads. Second, we determine the renewable generation capacity required to meet growth in demand at a certain level of grid reliability through a generation adequacy study. Adequacy of the microgrid is evaluated using parameters such as loss of load probability (LOLP) and expected energy not served (EENS). Third, the impact of different conditions, such as wind speed diversity (captured by correlating the wind power output), a combination of wind and solar power, and load diversity, on generation adequacy is studied through sensitivity analyses. Finally, the optimum renewable generation capacities are determined such that the total cost of generation and unserved power is minimized. The optimization process is based on the particle swarm optimization (PSO) method which uses Monte Carlo (MC) simulation for generation adequacy studies in each iteration

Impact of hybrid renewable energy systems on short circuit levels in distribution networks

The effects of the distributed generation can be classified as environmental, technical and economical effects. It is playing a very vital role for improving the voltage profiles in electrical power systems. However, it could have some negative impacts such as operating conflicts for fault clearing and interference with relaying. Distribution system is the link between the utility system and the consumer. It is divided into three categories radial, Loop, and network. Distribution networks are the most commonly used to cover huge number of loads. The power system reliability mainly depends on the smooth operation and continuity of supply of the distribution network. However, this may not always be guaranteed especially with the introduction of distributed generation to the distribution network. This paper will examine the impact of hybrid renewable energy systems (using photovoltaic and doubly fed induction generators) on short circuit level of IEEE 13-bus distribution test system using ETAP software

Improving Grid Hosting Capacity and Inertia Response with High Penetration of Renewable Generation

To achieve a more sustainable supply of electricity, utilizing renewable energy resources is a promising solution. However, the inclusion of intermittent renewable energy resources in electric power systems, if not appropriately managed and controlled, will raise a new set of technical challenges in both voltage and frequency control and jeopardizes the reliability and stability of the power system, as one of the most critical infrastructures in the today’s world. This dissertation aims to answer how to achieve high penetration of renewable generations in the entire power system without jeopardizing its security and reliability. First, we tackle the data insufficiency in testing new methods and concepts in renewable generation integration and develop a toolkit to generate any number of synthetic power grids feathering the same properties of real power grids. Next, we focus on small-scale PV systems as the most growing renewable generation in distribution networks and develop a detailed impact assessment framework to examine its impacts on the system and provide installation scheme recommendations to improve the hosting capacity of PV systems in the distribution networks. Following, we examine smart homes with rooftop PV systems and propose a new demand side management algorithm to make the best use of distributed renewable energy. Finally, the findings in the aforementioned three parts have been incorporated to solve the challenge of inertia response and hosting capacity of renewables in transmission network

Analysing long-term interactions between demand response and different electricity markets using a stochastic market equilibrium model. ESRI WP585, February 2018

Power systems based on renewable energy sources (RES) are characterised by increasingly distributed, volatile and uncertain supply leading to growing requirements for flexibility. In this paper, we explore the role of demand response (DR) as a source of flexibility that is considered to become increasingly important in future. The majority of research in this context has focussed on the operation of power systems in energy only markets, mostly using deterministic optimisation models. In contrast, we explore the impact of DR on generator investments and profits from different markets, on costs for different consumers from different markets, and on CO2 emissions under consideration of the uncertainties associated with the RES generation. We also analyse the effect of the presence of a feed-in premium (FIP) for RES generation on these impacts. We therefore develop a novel stochastic mixed complementarity model in this paper that considers both operational and investment decisions, that considers interactions between an energy market, a capacity market and a feed-in premium and that takes into account the stochasticity of electricity generation by RES. We use a Benders decomposition algorithm to reduce the computational expenses of the model and apply the model to a case study based on the future Irish power system. We find that DR particularly increases renewable generator profits. While DR may reduce consumer costs from the energy market, these savings may be (over)compensated by increasing costs from the capacity market and the feed-in premium. This result highlights the importance of considering such interactions between different markets

Quantification of efficiency improvements from integration of battery energy storage systems and renewable energy sources into domestic distribution networks

Due to the increasing use of renewable, non-controllable energy generation systems energy storage systems (ESS) are seen as a necessary part of future power delivery systems. ESS have gained research interest and practical implementation over the past decade and this is expected to continue into the future. This is due to the economic and operational benefits for both network operators and customers, battery energy storage system (BESS) is used as the main focus of this research paper. This paper presents an analytical study of the benefits of deploying distributed BESS in an electrical distribution network (DN). The work explores the optimum location of installing BESS and its impact on the DN performance and possible future investment. This study provides a comparison between bulk energy storage installed at three different locations; medium voltage (MV) side and low voltage (LV) side of the distribution transformer (DT) and distributed energy storage at customers’ feeders. The performance of a typical UK DN is examined under different penetration levels of wind energy generation units and BESS. The results show that the minimum storage size is obtained when BESS is installed next to the DT. However, the power loss is reduced to its minimum when BESS and wind energy are both distributed at load busbars. The study demonstrates that BESS installation has improved the loss of life factor of the distribution transformer

Fault Analysis Of An Unbalanced Distribution System With Distributed Generation

In recent years there has been a lot of emphasis on renewable power integration due to environmental issues and to lower the dependence on fossil fuels. The presence of renewable sources in the distribution systems adds complexity to the calculation of the power flows and hence has a direct impact on the short circuit calculations, protection and control. The presence of unbalance in distribution systems worsens the situation since the three phase voltages and currents are no longer equal in magnitude and 120 degrees phase shifted. This thesis involves a fault study in a 14-bus distribution system with integrated wind and solar power generation and shows the impact of unbalance in the system on short circuit calculations. The effect of unbalance on the behavior of traditional synchronous sources is already known and has been shown to cause errors in fault current magnitudes in the system. This thesis aims at observing and comparing the behavior of distributed generators in a balanced and an unbalanced distribution system. Detailed modeling of the DFIG and a grid connected PV array has been carried out in PSCAD. A 14 bus distribution system has been built and the distributed sources have been integrated into it. Unbalance has been introduced into an originally built balanced system by applying unbalanced loads at the buses and using untransposed feeders. Therefore, two systems, balanced and unbalanced, have been simulated and the behavior of the integrated distributed sources during faults has been compared for both the cases

A methodology for optimal placement of distributed generation on meshed networks to reduce power losses for time variant loads.

Master of Science in Power and Energy. University of KwaZulu-Natal, Durban, 2015.In the 21st century, humanity’s thirst for an energy intensive lifestyle has led to the saturated expansion of the modern day power system. As the power system expands, centralised generation philosophies are rapidly being constrained due to increased technical losses. The inability to balance technical, economic and environmental conventional generation needs place further strain on the power system. This constraint has catalysed the emergence of decentralized renewable energy sources. Distributed generation supplements the electrical needs of a rapidly expanding demand for energy and minimises the adverse environmental impact of fossil fuel power stations. Distributed Generation is defined as electric power generation units connected close to load centres. Distributed generation can be classified according to rating, purpose, technology, environmental impact, mode of operation and penetration. Optimally connected distributed generation have many advantages over classically supplied power systems. Such as reduced power losses, improve voltage support and reliability to the system. Deferring network upgrades by relieving congestion and reducing greenhouse gas emission being some of the benefits of integrated distributed generation. This research delivers an optimal placement method of solar photovoltaic distributed generation on a 56 bus utility network to reduce power losses. Critical electrical factors for optimal placement of distributed generation to reduce power losses are defined. A practical loss optimization technique for optimal placement of distributed generation on meshed networks is defined. The technique follows an approach of ranking, profiling, activating, evaluating and finally selecting the optimally placed distributed resources. The importance of reactive power compensation is examined when integrating distributed generation onto meshed networks. Pre and post distributed solar photovoltaic generation placement shows the worsening phase angles leading to poorer power factors. The research demonstrates the impact of penetration and concentration of distributed generation on power system losses. Highly concentrated placement of non-dispatched distributed generation units lead to increase in power losses. Results conclude that the placement of distributed generation for loss reduction on a meshed power system is optimally located to match load-profiled centres. This research is significant as power utility engineers can now benefit from a wider range of skills to assess the impact of DG connections