Power sharing and control strategy for provisionally coupled microgrid clusters through an isolated power exchange network

The two common mechanisms of load-shedding and renewable curtailment can prevent provisional overloading and excessive generation and the subsequent unacceptable voltage and frequency deviation in standalone microgrids (MGs), which makes MGs less resilient and reliable. However, instead of enabling load-shedding or renewable curtailment, such overloading or over-generation problems can be alleviated more efficiently and cost-effectively by provisionally interconnecting the neighboring MGs to exchange power amongst themselves. In such a scheme, the interconnected MGs can supply their local demand, as well as a portion of the demand of the adjacent MGs. In order to implement this strategy, a three-phase ac link can be used as the power exchange network, while each MG is coupled to the link through a back-to-back power electronics converter, in order to maintain the autonomy of each MG if they are eachoperated under different standards. This paper proposes a suitable decentralized power management strategy without a communication link between the MGs to achieve power-sharing amongst them and alleviate unacceptable voltage and frequency deviation along with the required control technique for the power electronic converters, which can be implemented at the primary level based on the measurement of the local parameters only. To this end, one of the converters should always regulate the dc link voltage while the other converter should operate in droop control mode when the MG is healthy and in constant PQ mode when overloaded or over-generating. Suitable status detection and mode transition algorithms and controllers were also developed and are proposed in this paper. The performance of the proposed power exchange and control mechanisms were evaluated and verified via PSIM®-based numerical simulation studies. The stability and sensitivity of the proposed power exchange topology are also analyzed against several critical design and operational parameters

Additional controls to enhance the active power management within islanded microgrids

Balancing the generated and consumed power in a microgrid is highly affected by the varying output power of the intermittent, renewable energy-based, distributed energy resources. This paper focuses on coordinating the output power among the energy resources within a microgrid while managing the consumed power at the demand side. The considered microgrid in this study consists of a battery system, which is the primary unit for grid-forming, as well as a photovoltaic system as the grid-following unit. A soft starting ramp function and an active power reduction function are implemented within the photovoltaic inverter respectively for the periods after the isolation of the microgrid from the grid and the over-frequency observation. Meanwhile, a demand-side management is developed based on the level of the battery’s state of charge, to facilitate the microgrid with a longer time in supplying its critical loads

Prediction of indoor temperature in an institutional building

The importance of predicting building indoor temperature is inevitable to execute an effective energy management strategy in an institutional building. An accurate prediction of building indoor temperature not only contributes to improved thermal comfort conditions but also has a role in building heating and cooling energy conservation. To predict the indoor temperature accurately, Artificial Neural Network (ANN) has been used in this study because of its performance superiority to deal with the time-series data as cited in past studies. Network architecture is the most important part of ANN for predicting accurately without overfitting the data. In this study, as a part of determining the optimal network architecture, important input parameters related to the output has been sorted out first. Next, prediction models have been developed for building indoor temperature using real data. Initially, spring season of Australia was selected for data collection. During model development three different training algorithms have been used and the performance of these training algorithms has been evaluated in this study based on prediction accuracy, generalization capability and iteration time to train the algorithm. From results Lovenberg-Marquardt has been found the best-suited training algorithm for short-term prediction of indoor space temperature. Afterwards, residual analysis has been used as a technique to verify the validation result. Finally, the result has been justified by applying a similar approach to another building case and using two different weather data-sets of two different seasons: summer and winter of Australia

Techno-economic evaluation of utilizing a small-scale microgrid

Microgrid deployment has offered technical and economical benefits such as improving grid reliability, maximizing penetration of intermittent renewable energy sources, reducing the cost of energy production, etc. However, to realize those advantages, the costs of microgrid implementation may be bloated as microgrid need additional investment for the enabling technologies. Therefore, an appropriate approach to determine the economic viability of microgrid to quantify the values of microgrid benefits is needed. This study performs a techno-economic analysis of a small-scale grid-connected microgrid deployment which consists of photovoltaic (PV) and energy storage system. The analysis is done by considering the possible bussines models available in Indonesia where the microgrid test case is located, i.e, net metering for electricity bill, feed-in tariff for utilizing renewable energy, demand response (DR) implementation by exploiting battery roles in response of price variation during peak and off-peak period and assuming compensation is given every time microgrid is in islanded mode due to fault event occur in the main grid. The feasibility of each model is indicated by the microgrid’s net present value (NPV) and internal rate of return (IRR). The results show that further incentives from the utility or Government is required to make the small-scale microgrid deployment economically sustainable

A framework-based wind forecasting to assess wind potential with improved grey wolf optimization and support vector regression

Wind energy is one of the most promising alternates of fossil fuels because of its abundant availability, low cost, and pollution-free attributes. Wind potential estimation, wind forecasting, and effective wind-energy management are the critical factors in planning and managing wind farms connected to wind-pooling substations. Hence, this study proposes a hybrid framework-based approach for wind-resource estimation and forecasting, namely IGWO-SVR (improved grey wolf optimization method (IGWO)-support vector regression (SVR)) for a real-time power pooling substation. The wind resource assessment and behavioral wind analysis has been carried out with the proposed IGWO-SVR optimization method for hourly, daily, monthly, and annual cases using 40 years of ERA (European Center for Medium-Range Weather Forecast reanalysis) data along with the impact of the El Niño effect. First, wind reassessment is carried out considering the impact of El Niño, wind speed, power, pressure, and temperature of the selected site Radhapuram substation in Tamilnadu, India and reported extensively. In addition, statistical analysis and wind distribution fitting are performed to demonstrate the seasonal effect. Then the proposed model is adopted for wind speed forecasting based on the dataset. From the results, the proposed model offered the best assessment report and predicted the wind behavior with greater accuracy using evaluation metrics, namely root mean square error (RMSE), mean absolute error (MAE), and mean squared error (MSE). For short-term wind speed, power, and El Niño forecasting, IGWO-SVR optimization effectively outperforms other existing models. This method can be adapted effectively in any potential locations for wind resource assessment and forecasting needs for better renewable energy management by power utilities

Prospects of renewable energy in semi-arid region

Continuous usage of fossil fuels and other conventional resources to meet the growing demand has resulted in increased energy crisis and greenhouse gas emissions. Hence, it is essential to use renewable energy sources for more reliable, effective, sustainable and pollution free transmission and distribution networks. Therefore, to facilitate large-scale integration of renewable energy in particular wind and solar photovoltaic (PV) energy, this paper presents the feasibility analysis for semi-arid climate and finds the most suitable places in North East region of Victoria for renewable energy generation. For economic and environmental analysis, Hybrid Optimization Model for Electric Renewables (HOMER) has used to investigate the prospects of wind and solar energy considering the Net Present Cost (NPC), Cost of Energy (COE) and Renewable fraction (RF). Six locations are selected from North East region of Victoria and simulations are performed. From the feasibility analysis, it can be concluded that Mount Hotham is one of the most suitable locations for wind energy generation while Wangaratta is the most suitable location for solar energy generation. Mount Hotham is also the best suitable locations in North East region for hybrid power systems i.e., combination of both wind and solar energy generation

Homogenising the design criteria of a community battery energy storage for better grid integration

Historically, minimum system demand has usually occurred overnight. However, in recent years, the increased penetration of rooftop photovoltaic systems (RPVs) has caused an even lower demand at midday, forcing some of the conventional generators to shut down only hours before the evening peak demand period. This further complicates the job of power system operators, who need to run the conventional generator at the minimum stable level at the midday low-demand period so that they can reliably supply power during the peak periods. Employing a community battery storage system can alleviate some of the technical issues caused by the high penetration of RPVs. This paper proposed a design criterion for community battery energy storage systems and employed the battery for the improvement of the duck curve profile and providing the desired level of peak-shaving. Furthermore, remote communities with high penetration of RPVs with a community battery energy storage can achieve the desired level of self-sufficiency. To this end, this study recommends and confirms an applicable design criterion for community battery energy storage. The study shows that the suitable size of community battery storage should be based on the community’s daily excess generation and consumption requirements. The results of various scenarios performed on the proposed design criterion show the extent to which the desired objectives of peak-shaving, duck curve mitigation, and self-sufficiency can be achieved

A State-of-the-Art review on the drive of renewables in Gujarat, State of India: Present situation, barriers and future initiatives

Given the recent increasing public focus on climate change issues, the share of electricity generation by renewable energy resources is increasing day by day. Increased renewables share will give us robust, sustainable, and climate-friendly energy systems for the future. Renewable energy penetration with the current power systems needs substantial research, planning and development which are now the primary focus throughout the world. In this study, a global renewable energy scenario is explained in detail in contrast with India, considering a case study elucidating the comprehensive review of the Gujarat state in India. The primary focus is on Gujarat state’s actions plans to pertain to harvest renewable energy and maximizing its share in the energy mix. This study examines the actions and the policies adopted by the Gujarat government to overcome the potential barriers in order to support non-conventional as well as renewable energy development. It also investigates the numerous techno-economic and social constraints with possible solutions in promoting the deployment of upcoming renewable energy resources across Gujarat. This study can be used as a guideline for the government, policymakers, utilities, stakeholders and researchers to promote an increased renewable energy share in Gujarat as well as at other places around the globe

Dynamic frequency and overload management in autonomous coupled microgrids for self-healing and resiliency improvement

Autonomous microgrids (MGs) are being installed in large remote areas to supply power where access to the utility grid is unavailable or infeasible. The power generation of such standalone MGs is largely dominated by renewable based energy sources where overloading or power deficiencies can be common due to the high intermittency and uncertainty in both load and power generation. Load-shedding is the most common mechanism to alleviate these problems to prevent system instability. To minimize load-shedding, most MGs are equipped with local battery energy storage (BES) systems to provide additional support. Furthermore, in the event of severe overloading or when BES capacity is insufficient to alleviate the overload, neighboring MGs can be provisionally coupled to provide mutual support to each other which is a more effective, economic and reliable approach. Such a coupling is preferred to be via power electronic converters to enhance the autonomy of the MGs. This paper proposes a two-stage, coordinated power sharing strategy among BESs and coupled MGs for overload management in autonomous MGs, through dynamic frequency control. Both local BES and the neighboring MGs can work in conjunction or individually to supply the required overload power demand. For this, BES’ state of charge should be above a minimum level and extra power generation capacity needs to be available in the neighboring MGs. A predefined framework with appropriate constraints and conditions, under which the power exchange will take place, are defined and formulated. The proposed mechanism is a decentralized approach, operating based on local frequency and state of charge measurements, and without any data communication amongst the MGs. The dynamic performance of such a network, is evaluated through extensive simulation studies in PSIM Ⓡ and verifies that the proposed strategy can successfully alleviate the overloading situation in the MGs through proper frequency regulation

A practical biogas based energy neutral home system for rural communities of Bangladesh

Growing demand of energy consumption, subsequent increase in energy generation costs, and increased greenhouse gas(GHG) emissions, as well as global warming from the conventional energy sources, encourages interest worldwide to bring a higher percentage of renewable energy sources such as biogas into the energy mix to build a climate friendly environment for the future. Moreover, due to high investment and maintenance costs, governments are not providing enough support for grid extension and delivering electricity to remote locations or rural areas, in particular, in under-developing countries like Bangladesh. Therefore, this paper presents an Energy Neutral Home System (ENHS) that can meet all its energy requirements from low-cost, locally available, nonpolluting biogas generated from animal waste, in particular, chicken and cow manure. The proposed ENHS has been developed for rural community, typically an area of 200 families, and will not only provide cooking gas and sustainable and affordable power supply to the community with low emissions, but will also facilitate high quality fertilizer for agricultural purposes. In-depth analysis clearly demonstrates that the proposed ENHS not only offers electricity and cooking gas to the community with the lowest costs, but also reduces the energy crisis and GHG emissions and can play an active role in developing socio-economic infrastructure of rural communities in Bangladesh in many ways