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The purpose of this paper is to evaluate the suitability and robustness of sliding mode controller (SMC) for maintaining flat voltage profile at the load bus of two different micro-grid systems using STATCOM.

Two micro-grid systems are dynamically modelled and simulated using MATLAB/Simulink. The first micro-grid has a single diesel engine-driven synchronous generator. The second micro-grid has one diesel engine-driven synchronous generator and a doubly fed induction generator-based wind energy conversion system. The STATCOM is connected to the load bus in both the micro-grids. SMC is used for the control of STATCOM for voltage profile improvement of micro-grid. The performance of SMC-based STATCOM is analysed and compared with the performance of conventional PI controller-based STATCOM.

The SMCs are more suited for STATCOM control as these are more immune to load disturbances even with the presence of wind energy generators. The voltage deviations and the steady state errors in voltage are less with SMC. Although SMC introduces a bit of steady state error in the dc link voltage of the STATCOM, it is much less than the settling limit of 2 per cent, which is quite acceptable. SMC proves to be better than conventional PI controllers in both the proposed models of micro-grid.

Design of a robust first-order SMC for a STATCOM is used for voltage profile improvement in two different micro-grid systems.

This paper aims to demonstrate the efficacy of fuzzy logic controller (FLC) over proportional integral (PI) and sliding mode controller (SMC) for maintaining flat voltage profile at the load bus of a single-generator-based micro-grid system using STATCOM.

A STATCOM is used to improve the voltage profile of the load bus. The performance of the STATCOM is evaluated by using three different controllers: PI controllers, FLCs and SMCs. The performance comparison of the controllers is done with different dc bus voltages, different load bus voltage references, various loads such as R-L loads and dynamic loads.

A comparative analysis is done between the performances of the three different controllers. The comparative study culminates that FLC is found to be superior than the other proposed controllers. SMC is a close competitor of fuzzy controller.

Design of fuzzy logic and SMCs for a STATCOM implemented in a single-generator-based micro-grid system is applied.

Over the past three decades, new off-grid electrification infrastructures – as micro-grids and other solar solutions – have moved from innovative initiatives, conducted by NGOs and private stakeholders, to a credible model promoted by international organizations for electrification of rural areas in developing countries. Multiple conditions support their spread: major technological advances in the field of renewable energies (panels, batteries), intensive Chinese industrial production allowing lower prices, institutional reforms in Africa including these solutions in major national electrification programmes, and, finally, an opening to the private sector as a supposed guarantee of the projects’ viability. However, while the development of this market calls for significant investments, a vast set of calculations and a strong “micro-capitalist” doctrine, all involved in their design, experts admit that a large proportion of projects hardly survive or even fail.

This chapter investigates these failures by exploring the ecology of such infrastructures, designed for “the poor.” It discusses “thinking infrastructures” in terms of longevity by focusing on economic failures risks. The authors argue that the ecology of the infrastructure integrates various economic conversions and exchanges chains expected to participate in the infrastructure’s functioning. By following energy access solutions for rural Africa in sub-regions of Senegal and Madagascar, from their political and technical design to their ordinary life, the authors examine the tensions and contradictions embedded within the scripts of balance supposed to guarantee their success.

The purpose is to open the possibility for a research institute, perhaps in partnership with a local council and a major developer, to bring together skills necessary to prototype the CEV development model.

This paper advances the development of a hypothetical, systems-based approach to the design and development of smart rural villages – a network of circular economy villages (CEVs). The method is to assimilate visionary ideas from 20th century town planning literature related to decentralisation and the development of new towns in rural areas, identifying key design principles. The present trajectory of infrastructure design and emerging development models are then analysed to modernise the design principles for implementation in the 21st century.

The availability of localised, renewable energy micro-grids potentially makes CEVs feasible and affordable. The shift to remote work and movement of people to regional areas suggests that this may be a desirable development form. This can only be confirmed through the development of a pilot project as proof of concept.

The proposed CEV development model applies circular economy strategies to every aspect of the smart rural village development including financing, ownership, spatial planning, design and material selection.

In this paper, a novel Lyapunov–Krasovskii stable fuzzy proportional-integral-derivative (PID) (FPID) controller is introduced for load frequency control of a time-delayed micro-grid (MG) system that benefits from a fuel cell unit, wind turbine generator and plug-in electric vehicles.

Using the Lyapunov–Krasovskii theorem, the adaptation laws for the consequent parameters and output scaling factors of the FPID controller are developed in such a way that an upper limit (the maximum permissible value) for time delay is introduced for the stability of the closed-loop MG system. In this way, there is a stable FPID controller, the adaptive parameters of which are bounded. In the obtained adaptation laws and the way of stability analyses, there is no need to approximate the nonlinear model of the controlled system, which makes the implementation process of the proposed adaptive FPID controller much simpler.

It has been shown that for a different amount of time delay and intermittent resources/loads, the proposed adaptive FPID controller is able to enforce the frequency deviations to zero with better performance and a less amount of energy. In the proposed FPID controller, the increase in the amount of time delay leads to a small increase in the amount of overshoot/undershoot and settling time values, which indicate that the proposed controller is robust to the time delay changes.

Although the designed FPID controllers in the literature are very efficient in being applied to the uncertain and nonlinear systems, they suffer from stability problems. In this paper, the stability of the FPID controller has been examined in applying to the frequency control of a nonlinear input-delayed MG system. Based on the Lyapunov–Krasovskii theorem and using rigorous mathematical analyses, the stability conditions and the adaptation laws for the parameters of the FPID controller have been obtained in the presence of input delay and nonlinearities of the MG system.

Whilst the energy transition from fossil fuels to renewables offers significant environmental benefits, the other transition – from a centralised to a distributed energy system – underpins a disruptive model for planning cities, towns and villages. A local energy micro-grid can power a local water micro-grid, which in turn can irrigate a local food system, offering a community the opportunity to harvest, store and distribute food, water and energy within their immediate catchment. A distributed network of regenerative villages, connected virtually and with shared electric vehicles is offered as an alternative vision for future cities. The paper aims to justify this as a preferred model for human settlements and develop an implementation process.

This paper asks: Is it inevitable that large cities will keep growing, while rural communities will continue to be deprived of resources and opportunities? Is the flow of people into cities inevitable? To answer this question, the adopted methodology is to take a systems approach, observing town planning processes from a range of different disciplines and perspectives.

By contrasting the current centralising city model with a distributed network of villages, this paper offers ten reasons why the distributed network is preferable to centralisation.

It is argued that in this time of dramatic technological upheaval, environmental destruction and social inequality, business-as-usual is unacceptable in any field of human endeavour. This paper presents a sketch outlining a new human settlement theory, a different way of living on the land. It is an invitation to academics and practitioners to participate in a debate.

The information and energy revolutions, both distributed systems, are reshaping cities.

Explains that segregation processes during the solidification of a binary alloy occur at two distinct length scales: on the microscopic length scale of the crystal interface, in the two‐phase mushy zone, segregation is controlled by solid state mass diffusion; and, on the macroscopic scale of the process, segregation is controlled by the convective transport of the molten metal. Concludes that developing models that can capture both these scales is a challenge. Introduces a bi‐level grid, and uses a macro grid on the scale of the process for the solution of equations describing macroscopic heat and mass transport. Details how each node point in the macro grid is associated with a micro grid on which equations describing the microscopic phenomena in the mushy region are solved. In this way, develops a dual‐scale model of segregation during the solidification of a binary alloy. On investigating the unidirectional solidification of a binary alloy, demonstrates that this dual‐scale model is able to capture both the macro and micro‐scales in a single numerical treatment.

This paper aims to implement a maiden methodology for load frequency control of an AC multi micro-grid (MG) by using hybrid fractional order fuzzy PID (FOFPID) controller and linear quadratic Gaussian (LQG).

The multi MG system considered is consisting of photovoltaic, wind turbine and a synchronous generator. Different energy storage devices i.e. battery energy storage system and flywheel energy storage system are also integrated to the system. The renewable energy sources suffer from uncertainty and fluctuation from their nominal values, which results in fluctuation of system frequency. Inspired by this difficulty in MG control, this research paper proposes a hybridized FOFPID and LQG controller under random and stochastic environments. Again to confer viability of proposed controller its performances are compared with PID, fuzzy PID and fuzzy PID-LQG controllers. A comparative study among all implemented techniques i.e. proposed multi-verse optimization (MVO) algorithm, particle swarm optimization and genetic algorithm has been done to justify the supremacy of MVO algorithm. To check the robustness of the controller sensitivity analysis is done.

The merged concept of fractional calculus and state feedback theory is found to be efficient. The designed controller is found to be capable of rejecting the effect of disturbances present in the system.

From the study, the authors observed that the proposed hybrid FOPID and LQG controller is robust hence, there is no need to reset the controller parameters with a large change in network parameters.

The researchers and policy makers worldwide have proposed many ideas for smart cities and homes in urban areas. The extensive work done for urban smart homes neglects the unique constraints of homes at remote mountain tops and deserts and rural village homes. The purpose of this paper is to propose a smart energy management system for a self-sustained home of any type situated in any geographical location with the availability of renewable energy sources like solar, etc. The purpose is mainly to highlight the importance and advantages of direct current (DC) homes with DC loads rather than a conventional alternating current (AC) home with both AC and DC loads. An attempt has been made to evolve a multi-agent coordinated control for the low voltage direct current (LVDC) smart home system.

LVDC supply systems with in situ power generation are providing an efficient solution for the energy needs of a DC smart home. The individual sub-systems of the LVDC system have their unique functions and priorities and hence require both coordinated and independent control. The entire DC smart home system is modeled in the Matlab and codes are implemented for each agent of the home. LVDC grid is operating either in battery connected mode or utility grid-connected mode, and the DC link voltage is held constant in both the cases. Energy imported from the utility grid is minimized by load shedding during the rectifier mode of the bidirectional converter. In addition, load shedding is also done when the battery is discharging to increase the discharge time of the battery. Load shedding is done on the basis of a fixed priority of loads. A 48 s simulation is performed on the Matlab model to bring out the 24-hour operation of the proposed system. Various modes are simulated and the corresponding actions of the agents are tested.

A new control strategy with agents for each sub-system of the LVDC system is presented. Each individual agent works in tandem with other agents and meets its own control imperatives without compromising the requirements of the overall system. Unlike the centralized control system, the proposed control strategy is a distributed control system. The control algorithm for each of the agents is developed, and the pseudo code is presented. The results of the simulation of the proposed scheme are presented to confirm the usefulness of the new control approach.

The multi-agent concept for an energy management system is less addressed and thus its potential for efficient home energy management is presented. The proposed multi-agent strategy for a complete DC smart home with exclusive DC loads is not done earlier and is reported for the first time. The success of this strategy can be extended to other DC micro-grid systems like telecom power systems, ships, aircraft, datacentres, server rooms, residential complexes and commercial malls.

This paper aims to set out a vision of the advent of autonomous electric vehicles (AEV), piloted by artificial intelligence and serviced by other “intelligent” machines, a scenario that poses vast implications for business strategy in many industries.

Given the speed with which business leaders today must assess and react to the business risks and opportunities engendered by breakthrough technological change, their plans to navigate an autonomous electric vehicle-based transportation future can benefit from a scenario map to the roadblocks and the richest prospects.

Self-driving electric cars and trucks, which are expected to transform the transportation landscape over the next decade. A smart charging grid is a critical technology development.

Business opportunities to transform ground transport in areas such as operations and supply chain management are significant as well, particularly with unsupervised AEVs, which could slash labor costs and transport times.

AEVs are expected to free up more than 30 billion hours per year in the U.S. alone currently spent driving, sitting in traffic or searching for a parking space.

Offers a look at the technology evolution needed for the AEV transportation revolution.