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Technological development has not only helped in effective integration of renewable sources but also made it possible for consumers to participate in system operation. Different market players are coming up in the electricity market, microgrid being one of them. Thus, this paper aims to investigate consumers’ role in the dispatch of a microgrid system that has a hybrid market structure under varied system conditions.

The mathematical model developed has been solved by the CONOPT solver in the GAMS optimization tool. GAMS-MATLAB interfacing is done to obtain solutions.

The problem formulated shows the effect of consumers in dispatch and overall operational cost. Consumers’ participation has been proposed through a quadratic cost function. The system operation under pool and bilateral contracts has been investigated. It shows that proper incentives to the consumers can help in reduction and effective management of the demand, carbon emission and overall system operational cost.

This paper considers the hybrid market structure to find the load dispatch in a microgrid system. The participation of consumers in the microgrid system has been implemented considering variations in wind power, solar power and load. The power exchange between the grid and microgrid system has been modeled showing the contribution of the consumers in system operation.

The purpose of studying the low voltage direct current (DC) microgrid, which uses computerised control system techniques, an orderly coordination control stratagem considering optimisation of a hybrid energy storage system (HESS) was projected in this paper.

The projected control stratagem was divided into three levels: topmost power dispatch level, transitional bus voltage regulation level and bottommost converter control level.

At the topmost power dispatch level, the cost of system stability was introduced, which is related with state of charge and discharging power of HESS.

Furthermore, the cost of system stability and HESS depreciation was compared with commercial price, and HESS switches its operating mode to discharge more at higher price or charge more at lower price to ensure the DC microgrid in economic operation. At the transitional bus voltage regulation level, DC bus gesturing is used as a control signal to achieve an autonomous decentralised operation of DC microgrid. The Matlab/Simulink simulation inveterate that the economical and autonomous decentralised operation can be achieved through the control stratagem.

The purpose of this paper is to propose an optimal energy management (OEM) method using intelligent optimization techniques applied to implement an optimally hybrid heat and power isolated microgrid. The microgrid investigated combines renewable and conventional power generation.

Five bio-inspired optimization methods include an advanced proposed multi-objective particle swarm optimization (MOPSO) approach which is comparatively applied for OEM of the implemented microgrid with other bio-inspired optimization approaches via their comparative simulation results.

Optimal multi-objective solutions through Pareto front demonstrate that the advanced proposed MOPSO method performs quite better in comparison with other meta-heuristic optimization methods. Moreover, the proposed MOPSO is successfully applied to perform 24-h OEM microgrid. The simulation results also display the merits of the real time optimization along with the arbitrary of users’ selection as to satisfy their power requirement.

This paper focuses on the OEM of a designed microgrid using a newly proposed modified MOPSO algorithm. Optimal multi-objective solutions through Pareto front demonstrate that the advanced proposed MOPSO method performs quite better in comparison with other meta-heuristic optimization approaches.

Storage systems are deemed to be unable to provide revenue commensurate with the resources invested in them, thus discouraging their incorporation within power networks. In prosumer microgrids, storage systems can provide revenue from reduced grid consumption, energy arbitraging or when serving as back-up power. This study aims to examine stacking these revenue streams with the aim of making storage systems financially viable for inclusion in prosumer microgrids.

With the aim of reducing self-consumption and maximising revenue, the prosumer microgrid incorporating hybrid energy storage systems (HESS) and solar PV power is solved using the CPLEX solver of the Advanced Interactive Multidimensional Modeling Software (AIMMS). The financial analysis of the results is carried out to provide the payback periods of different system configurations of the prosumer microgrid.

The findings reveal that the payback period of the three HESS when minimising grid expenses during self-consumption alone and when compared with stacked revenue streams shows an improvement from 4.8–11.2 years to 2.4–6.6 years. With stacked HESS revenues, the supercapacitor-lithium ion battery HESS gave the shortest payback period of 2.31 years when solar PV power is at 75% penetration level.

Existing literature has considered revenue streams of storage systems at the electrical power transmission and distribution levels, but not for prosumer microgrids in particular. This study has captured these benefits and verified the profitability of stacking revenue from HESS to prosumer microgrids, using a case study.

The study aims to accomplish the short-term load forecasting for microgrids. Short-term load forecasting is a vital component of economic dispatch in microgrids, and the forecasting error directly affects the economic efficiency of operation. To some extent, short-term load forecasting is more difficult in microgrids than in macrogrids.

This paper presents the method of Dragonfly Algorithm-based support vector machine (DA-SVM) to forecast the short-term load in microgrids. This method adopts the combination of penalty factor C and kernel parameters of SVM which needs to be optimized as the position of dragonfly to find the solution. It takes the forecast accuracy calculated by SVM as the current fitness value of dragonfly and the optimal position of dragonfly obtained through iteration is considered as the optimal combination of parameters C and s of SVM.

DA-SVM algorithm was used to do short-term load forecast in the microgrid of an offshore oilfield group in the Bohai Sea, China and the forecasting results were compared with those of PSO-SVM, GA-SVM and BP neural network models. The experimental results indicate that the DA-SVM algorithm has better global searching ability. In the case of study, the root mean square errors of DA-SVA are about 1.5 per cent and its computation time is saved about 50 per cent.

The DA-SVM model presented in this paper provides an efficient and effective method of short-term load forecasting for a microgrid electric power system.

This paper aims to introduce a new fault protection scheme for microgrid DC networks with ring buses.

It is well recognized that the protection scheme in a DC ring bus microgrid becomes very complicated due to the bidirectional power flow. To provide reliable protection, the differential current signal is decomposed into several basic modes using adaptive variational mode decomposition (VMD). In this method, the mode number and the penalty factor are chosen optimally by using arithmetic optimization algorithm, yielding satisfactory decomposition results than the conventional VMD. Weighted Kurtosis index is used as the measurement index to select the sensitive mode, which is used to evaluate the discrete Teager energy (DTE) that indicates the occurrence of DC faults. For localizing cable faults, the current signals from the two ends are used on a sample-to-sample basis to formulate the state space matrix, which is solved by using generalized least squares approach. The proposed protection method is validated in MATLAB/SIMULINK by considering various test cases.

DTE is used to detect pole-pole and pole-ground fault and other disturbances such as high-impedance faults and series arc faults with a reduced detection time (10 ms) compared to some existing techniques.

Verification of this method is performed considering various test cases in MATLAB/SIMULINK platform yielding fast detection timings and accurate fault location.

The purpose of this paper is to optimally operate a Smart Microgrid which is interconnected to the main grid so as to minimize expenditures associated with CO₂ emissions. Microgrids could come into play to aid the network through CO₂ emission reduction while increasing their efficiency through local generation. For this purpose, a Smart Microgrid incorporating Distributed Energy Resources (DER), especially Renewable Energy Sources (RES), is operated optimally while keeping the CO₂ emissions in check in order to minimize the financial burden from emissions stemming from the carbon tax. Since the network is assumed to be interconnected with the main grid, there is a consideration of the expected emissions associated with the imported energy.

An economic/environmental dispatch problem is mathematically formulated using an objective function and the constraints that it is subject to. The methodology is applied on a typical 17-bus test distribution network, representing a Hellenic LV network. Various carbon tax rates and their impact on the system marginal price are examined, in terms of their effect on distributed generation (DG) and as a second step, the effect of imposing lower carbon tax rates for micro-sources with the goal of benefitting from their more eco-friendly generation capabilities. In order to assess that benefit, hourly grid emissions coefficients are derived based on actual grid data.

The CO₂ tax refund policy towards the DG owners can lead to optimal coverage of consumers, optimal financial result both for the DG owners and the operator and greater DG integration within the smart grid.

Greater DG integration within the smart grid by using a CO₂ tax refund policy.

The purpose of this paper is to present the simulation method of power plants and storage system capacity design.

Owing to solar irradiation, wind speed and water flow are highly and randomly changeable, time variation of the signals needs to be taken into consideration as well as some features of the power plants and storage system. A Matlab/Simulink model of the given system – DC microgrid has been developed. The model allows simulation of a few years static simulations of the power balance. Hence, it can be used to size the plants.

An effective method of the power system design has been developed. It allows sizing the plants taking into consideration resources and load profiles, year changes in profiles and future development of the system. The storage system can be optimized to avoid high power unbalance and power cost increasing.

The model describes only static power behaviour of the modelled power system. It does not allow simulating local voltage changes and dynamic properties of the plants and storage.

This technique helps to size the plants and, first of all, storage system taking into consideration several technical and economical issues.

The method gives opportunity to design a storage system's capacity and power and optimize them. The authors have not found similar methods in the literature.

Applicable to both undergraduate and graduate courses in managing technology or sustainability.

Technology strategy.

Business Model evaluation.

Sustainable technologies.

In this case study, gas and electric utility holding company Southern Company has embarked on an ambitious experiment to learn more about energy usage at a household level, as well as community scale microgrids. Every minute, 62 homes in Reynolds Landing upload appliance and electrical outlet level data to Southern Company. How can Southern Company use this vast amount of data to promote energy efficiency? Are microgrids a key to creating a more sustainable and resilient energy future? At a higher level, how can microgrids impact or change traditional power generation business models like those used by Southern Company?

1. To explore why companies develop technologies that are counter to current business models.

2. To understand how new technology can lead to new business models for existing businesses.

3. To understand the drivers of company led R&D.

4. To discuss “technology push” applications. Where technology is developed and then a market or markets are sought.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

Two parts here. The first is looking at sustainable energy solutions such as solar farms and micro-grids. The second is this case challenges students to ask how this research helps the 45% of consumers making less than $40,000/yr.

CSS 11: Strategy.

This paper aims to present a new fault detection and classification scheme of both DC faults and AC faults on a DC microgrid network.

To achieve reliable protection, the derivative of DC current signal is decomposed into several intrinsic modes using variational mode decomposition (VMD), which are then used as inputs to the Hilbert–Haung transform technique to obtain the instantaneous amplitude and frequency of the decomposed modes of the signal. A weighted Kurtosis index is used to obtain the most sensitive mode, which is used to compute sudden change in discrete Teager energy (DTE), indicating the occurrence of the fault. A stacked autoencoder-based neural network is applied for classifying the pole to ground (PG), pole to pole (PP), line to ground (LG), line to line (LL) and three-phase line to ground (LLLG) faults. The effectiveness of the proposed protection technique is validated in MATLAB/SIMULINK by considering different test cases.

As the maximum fault detection time is only 5 ms, the proposed detection technique is very fast. A stacked autoencoder-based neural network is applied for classifying the PG, PP, LG, LL and LLLG faults with classification accuracy of 99.1%.

The proposed technique provides a very fast, reliable and accurate protection scheme for DC microgrid system.