Tanvir Ahmad

More than 940 million people (13% of the world population) do not have any access to electricity. Most of these people live in rural and remote areas, where the lack of electricity access is significantly damaging the quality of life, economic development and the environment. Distributed energy systems (DESs) (based on clean energy technologies) for energy access offer a potentially important strategy for pursuing environment-friendly sustainable development and poverty alleviation; especially in rural and remote communities. DESs are also helpful in reducing deforestation and greenhouse gas (GHG) emissions as the fossil fuel-based energy production is among the largest contributors to GHG emissions. This paper presents the importance of energy access through DESs for resilient and sustainable development using two projects case studies from Pakistan. The first project case study is based on the Afghan refugee villages, where, currently, there is no electricity access. A baseline survey was conducted to assess the socio-economic conditions and energy demand of the refugees. This assessment is then used to devise clean energy solutions as per the local context. This project aims to improve the quality of life of the refugees by providing energy access. In the second case study, electricity access was provided to the local communities a few years ago. Analyses of primary data collected in this case study show that DES integrated with socio-economic and cultural systems can bring a significantly positive impact on the local communities, advancing all the sustainability development goals. This work concludes that DES can be significantly generative, if effectively integrated into socio-economic processes. This article is part of the theme issue ‘Developing resilient energy systems’.

The achievement of sustainable energy goals warrants keen interest in promoting efficient buildings and renewable energy resources. Prominent among the energy-efficient building technologies is geothermal energy, which has a significant margin for improving energy utilization related to Heat, Ventilation, and Air Conditioning (HVAC). However, the efficient extraction of geothermal energy for HVAC applications requires stringent control of geometric parameters, boundary conditions, and environmental conditions. In this study a new approach has been devised to optimize the open loop Earth to Air Heat Exchanger (EAHE) system using a statistical optimization technique i.e., Response Surface Method (RSM). The study was conducted in the soil and weather conditions of Peshawar city in Pakistan. Parametric analysis was conducted for the three influencing variables, i.e., the pipe length, diameter, and air velocity using the EAHE model. The soil model predicts temperature in the range 20–26 °C for Peshawar at a depth above 3 m. Response Surface method was used to optimize the pipe length, diameter, and air velocity of the EAHE system. Analysis of Variance (ANOVA) indicates that all the three factors are significant. The EAHE system can effectively reduce the temperature by 15–18 °C and compensate the cooling load of single room for the parameters in the ranges of 50–70 m for the length, 0.18–0.25 m for the diameter, and 5–7 ms⁻¹ for the air velocity. A regression equation is developed to predict the cooling load for any input values of the three influencing variables according to the weather and soil conditions.

Increasing large-scale integration of renewables in conventional power system has led to an increase in reserve power requirement owing to the forecasting error. Innovative operating strategies are required for maintaining balance between load and generation in real time, while keeping the reserve power requirement at its minimum. This research work proposes a control strategy for active power balance control without compromising power system security, emphasizing the integration of wind power and flexible load in automatic generation control. Simulations were performed in DIgSILENT for forecasting the modern Danish power system with bulk wind power integration. A high wind day of year 2020 was selected for analysis when wind power plants were contributing 76.7% of the total electricity production. Conventional power plants and power exchange with interconnected power systems utilize an hour-ahead power regulation schedule, while real-time series are used for wind power plants and load demand. Analysis showed that flexible load units along with wind power plants can actively help in reducing real-time power imbalances introduced due to large-scale integration of wind power, thus increasing power system reliability without enhancing the reserve power requirement from conventional power plants.

Short moving primary and rigid low‐cost secondary are important requirements of linear machines designed for long stroke applications. In the race, linear permanent magnet flux switching machine (LPMFSM) is a competitive candidate by confining excitation sources to short mover, thus making stator robust and low cost (made of only iron). However, single‐sided LPMFSM exhibit a demerit of high normal (attraction) force due to its topology. In order to rectify the problem and enhance thrust force profile, two novel double‐sided LPMFSMs are proposed with dual stator and dual mover topologies. After stator pole study, both topologies with same design dimensions are analysed and compared by 2‐D finite element method here. Detailed analysis revealed that 12/14 DMLPMFSM exhibit low numerical values of thrust force ripples and detent force while maintaining average thrust force value. Hence, 12/14 DMLPMFSM is selected and optimised by structure‐based deterministic optimisation (SBDO) approach to further enhance thrust force profile. Finally, comparison of initial and optimised design of 12/14 DMLPMFSM is presented to validate optimisation procedure.

Cereal-legumes intercropping is among the most economical and effective agronomic strategies to boost forage biomass production, nutritional quality and monetary returns. This review synthesizes the research findings on how intercropping affects productivity, quality, competitiveness and economic viability of sorghum-legumes mixed, row and strip intercropping systems under varied pedo-climatic conditions. Though component crops show yield reductions in row (additive and row-replacement series), mixed (seed blended crops) and strip intercropping systems, in general overall productivity per unit land area increases to a great extent. The significantly higher resource capturing with better utilization efficacy by intercrops in temporal and spatial dimensions helps explain their greater productivity. In addition, forage intercrops result in improved nutritional quality as legumes contain protein in double quantity than cereals. Cereal-legumes intercropping systems yield higher quantities of lush green forage with improved quality traits, which ultimately increase monetary benefits. Furthermore, legumes inclusion as an intercrop with cereals has the potential to serve as a nitrogen-saving strategy due to the biological nitrogen fixation (BNF) process. Moreover, cereal-legume intercropping systems are effective in reducing weed infestations and soil erosion by providing extended soil cover, as well as in increasing water use efficiency and improving soil fertility. However, despite a significant increase in overall productivity, component crops suffer yield losses in intercropping systems owing to competition for the finite divisible pool of growth resources. Thus, there is a dire need to optimize spatial and temporal arrangements in sorghum-legumes intercropping systems to achieve maximum productivity and economic returns.

This paper presents the effectiveness of the interior search algorithm in economic power scheduling of a grid-tied DC microgrid with renewable generation (wind and photovoltaic) and battery energy storage. The study presents the modelling and simulation of various DC/DC converters for tracking maximum power from wind and photovoltaic sources and the bidirectional power flow of battery energy storage. The DC microgrid and its controllers were modelled and simulated in MATLAB/Simulink. The generating units were dispatched economically using the interior search algorithm with the objective to minimize the operating cost of the microgrid. The simulated results verify the effectiveness of the interior search algorithm as the daily cost of microgrid operation was reduced by 11.25%.

A practical wind farm controller for production maximisation based on coordinated control is presented. The farm controller emphasises computational efficiency without compromising accuracy. The controller combines Particle Swarm Optimisation (PSO) with a turbulence intensity based Jensen wake model (TI-JM) for exploiting the benefits of either curtailing upstream turbines using coefficient of power ($C_P$) or deflecting wakes by applying yaw-offsets for maximising net farm production. First, TI-JM is evaluated using convention control benchmarking WindPRO and real time SCADA data from three operating wind farms. Then the optimized strategies are evaluated using simulations based on TI-JM and PSO. The innovative control strategies can optimise a medium size wind farm, Lillgrund consisting of 48 wind turbines, requiring less than 50 seconds for a single simulation, increasing farm efficiency up to a maximum of 6% in full wake conditions.