Microgrids are now emerging from lab benches and pilot demonstration sites into commercial markets, driven by technological improvements, falling costs, a proven track record, and growing recognition of their benefits. They are being used to improve reliability and resilience of electrical grids, to manage the addition of distributed clean energy resources like wind and solar photovoltaic (PV) generation to reduce fossil fuel emissions, and to provide electricity in areas not served by centralized electrical infrastructure. This review article (1) explains what a microgrid is, and (2) provides a multi-disciplinary portrait of today's microgrid drivers, real-world applications, challenges, and future prospects.

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Microgrids: A review of technologies, key drivers, and outstanding issues

This paper presents an energy management system (EMS) for a stand-alone droop-controlled microgrid, which adjusts generators output power to minimize fuel consumption and also ensures stable operation. It has previously been shown that frequency-droop gains have a significant effect on stability in such microgrids. Relationship between these parameters and stability margins are therefore identified, using qualitative analysis and small-signal techniques. This allows them to be selected to ensure stability. Optimized generator outputs are then implemented in real-time by the EMS, through adjustments to droop characteristics within this constraint. Experimental results from a laboratory-sized microgrid confirm the EMS function.

https://spiral.imperial.ac.uk:8443/bitstream/10044/1/15430/2/IEEE%20Transactions%20on%20Power%20Electronics_23_5_2008.pdf

Energy Management in Autonomous Microgrid Using Stability-Constrained Droop Control of Inverters

The recent development of efficient thermal prime movers for distributed generation is changing the focus of the production of electricity from large centralized power plants to local generation units scattered over the territory. The scientific community is addressing the analysis and planning of distributed energy resources with widespread approaches, taking into account technical, environmental, economic and social issues. The coupling of cogeneration systems to absorption/electric chillers or heat pumps, as well as the interactions with renewable sources, allow for setting up multi-generation systems for combined local production of different energy vectors such as electricity, heat (at different enthalpy levels), cooling power, hydrogen, various chemical substances, and so forth. Adoption of composite multi-generation systems may lead to significant benefits in terms of higher energy efficiency, reduced CO2 emissions, and enhanced economy. In this light, a key direction for improving the characteristics of the local energy production concerns the integration of the concepts of distributed energy resources and combined production of different energy vectors into a comprehensive distributed multi-generation (DMG) framework that entails various approaches to energy planning currently available in the literature. This paper outlines the main aspects of the DMG framework, illustrating its characteristics and summarizing the relevant DMG structures. The presentation is backed by an extended review of the most recent journal publications and reports.

Distributed multi-generation: A comprehensive view

Emerging new technologies like distributed generation, distributed storage, and demand-side load management will change the way we consume and produce energy. These techniques enable the possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams. By smartly applying future energy production, consumption, and storage techniques, a more energy-efficient electricity supply chain can be achieved. In this paper a three-step control methodology is proposed to manage the cooperation between these technologies, focused on domestic energy streams. In this approach, (global) objectives like peak shaving or forming a virtual power plant can be achieved without harming the comfort of residents. As shown in this work, using good predictions, in advance planning and real-time control of domestic appliances, a better matching of demand and supply can be achieved.

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Management and Control of Domestic Smart Grid Technology

The rapid developing literature on ‘smart grids’ suggests that these will facilitate ‘distributed generation’ (DG) preferably from renewable sources. However, the current development of smart (micro)grids with substantial amount of DG (“DisGenMiGrids”) suffers from a focus on mere ‘technology’. Ongoing problems with deployment of renewable energy have shown that implementation is largely determined by broad social acceptance issues. This smart grid development is very important for further renewables deployment, but again there is a tendency to continue the neglect of social determinants. Most technical studies apply implicit and largely unfounded assumptions about the participation in and contribution of actors to DisGenMiGrid systems. This lack of understanding will have severe consequences: smart grids will not further renewables deployment when there are hardly actors that are willing to become part of them. This review is a first attempt to address the social construction of smart electricity grids. As institutional factors have proved to be the main determinants of acceptance, these will also be crucial for further renewables deployment in micro-grid communities. Elaboration of the institutional character of social acceptance and renewables’ innovation calls for an institutional theory approach involving Common Pool Resources management, because these socio-technical systems aim to optimise the exploitation of natural resources. Citizens/consumers and other end-users increasingly have the option to become more self-sufficient by becoming co-producers of electricity. They may optimise the contribution of DG when they cooperate and insert their renewable energy in a cooperative microgrid with mutual delivery. Moreover, the option to include ‘distributed storage’ capacity (electric vehicles) in these microgrids, enables an increasing share of renewables deployment. However, all these options should be institutionally opened. This requires much self-governance and flexible overall regulation that allows microgrids. The research agenda should focus on how such new systems become institutionally embedded, and how they are socially constructed.

The research agenda on social acceptance of distributed generation in smart grids: Renewable as common pool resources

Almost all the electricity is generated in the UK as part of a centralised power system designed around large fossil fuel or nuclear power stations. This power system is robust and reliable but the efficiency of power generation is low, resulting in large quantities of waste heat. The principal aim of this paper is to investigate an alternative concept: the energy production by small scale generators in close proximity to the energy users, integrated into microgrids. Microgrids - de-centralised electricity generation combined with on-site production of heat - bear the promise of substantial environmental benefits , brought about by a higher efficiency and by facilitating the integration of renewable energy sources such as photovoltaic arrays or wind turbines. By virtue of good match between generation and load, microgrids have a low impact on the electricity network, despite a potentially significant level of generationby interemittent energy sources. The paper discusses the technical and economic issues associated with this novel concept, giving an overview of the generator technologies, the current regulatory framework in the UK, and the barriers that have to be overcome if microgrids are to make a major contribution to the UK energy supply. The focus of this study is a microgrid of domestic users powered by small Combined Heat and Power generators and photovoltaics. Focusing on the energy balance between the generation and load, it is found that the optimum combination of the generators in the microgrid - consisting of around 1.4 kWp PV array per household and 45% household ownership of micro-CHP generators - will maintain energy balance on a yearly basis if suplemented by energy storage of 2.7 kWh per household. We find that there is no fundamental technological reason why microgrids cannot contribute an appreciable part of UK energy demand. Indeed, an estimate of cost indicates that the microgrids considered in this study would supply electricity at a cost comparable with the present electricity supply if the current support mechanisms for photovoltaics were maintained. Combining photovoltaics and micro-CHP and a smallbattery requirement gives a microgrid that is independent of the national electricity network. In the short term, this has particular benefits for remote communities but more wide-ranging possibilities open up in the medium to long term. Microgrids could meet the need to replace current generation nuclear and coal fired power stations, greatly reducing the demand on the transmission and distribution network.

Can microgrids make a major contribution to UK energy supply

Modeling magnetic components for simulation in electric circuits requires an accurate model of the hysteresis loop of the core material used It is important that the parameters extracted for the hysteresis model be optimized across the range of operating conditions that may occur in circuit simulation This paper shows how to extract optimal parameters for the Jiles-Atherton model of hysteresis by the genetic algorithm approach It compares performance with the well-known simulated annealing method and demonstrates that improved results may be obtained with the genetic algorithm It also shows that a combination of the genetic algorithm and the simulated annealing method can provide an even more accurate solution than either method on its own A statistical analysis shows that the optimization obtained by the genetic algorithm is better on average, not just on a one-off test basis The paper introduces and applies the concept of simultaneous optimization for major and minor hysteresis loops to ensure accurate model optimization over a wide variety of operating conditions It proposes a modification to the Jiles-Atherton model to allow improved accuracy in the modeling of the major loop

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Optimizing the Jiles-Atherton model of hysteresis by a genetic algorithm

It is essential in the simulation of power electronics applications to model magnetic components accurately. In addition to modeling the nonlinear hysteresis behavior, eddy currents and winding losses must be included to provide a realistic model. In practice the losses in magnetic components give rise to significant temperature increases which can lead to major changes in the component behavior. In this paper a model of magnetic components is presented which integrates a nonlinear model of hysteresis, electro-magnetic windings and thermal behavior in a single model for use in circuit simulation of power electronics systems. Measurements and simulations are presented which demonstrate the accuracy of the approach for the electrical, magnetic and thermal domains across a variety of operating conditions, including static thermal conditions and dynamic self heating.

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Simulation of magnetic component models in electric circuits including dynamic thermal effects

We suggest a practical approach for modeling frequency-dependent losses in ferrite cores for circuit simulation. Previous work has concentrated on the effect of eddy-current losses on the shape of the B--H loop, but in this paper we look at the problem from the perspective of energy loss and propose a different network for accurately modeling power loss in ferrite cores. In power applications, the energy loss across the frequency range can have a profound effect on the efficiency of the system, and a simple ladder network in the magnetic domain is not always adequate for this task. Simulations and measurements demonstrate the difference in this approach from the RL ladder network models both in the small-signal and large-signal contexts.

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Modeling frequency-dependent losses in ferrite cores

The modeling of magnetic components for use in electrical circuit simulation requires that the core material be accurately characterized. This paper investigates a method of extracting parameters to model the hysteresis behavior of magnetic core materials and optimizing them to achieve accurate results during circuit simulation. Metrics are defined to measure specific features of the behavior of both the core magnetic material and the magnetic component, such as a transformer. This paper presents a method of applying these metrics for the purposes of comparison and optimization and demonstrates the method using measured results and corresponding simulations. It compares the effectiveness of a weighted metrics function with that of a least squares goal function for the purpose of optimization. This paper suggests modifications to the original Jiles-Atherton model to improve the ability of the model to more accurately represent the behavior of magnetic materials during saturation.

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J.N. Ross

Papers

Can microgrids make a major contribution to UK energy supply

Optimizing the Jiles-Atherton model of hysteresis by a genetic algorithm

Simulation of magnetic component models in electric circuits including dynamic thermal effects

Modeling frequency-dependent losses in ferrite cores

Definition and application of magnetic material metrics in modeling and optimization