Mokhtar Bozorg

The mining industry is among the most energy-intensive sectors and remains highly dependent on fossil fuels, particularly in remote, cold-climate regions where access to centralized electricity grids is limited. This dependence poses significant challenges in terms of operating costs, energy security, and greenhouse gas (GHG) emissions. This review provides a system-level analysis of energy consumption patterns, decarbonization pathways, and renewable energy integration strategies in the mining sector. The paper first examines the structure and drivers of energy demand in open-pit and underground mines, identifying transport systems, material handling, ventilation, and comminution processes as major energy consumers. It then analyzes technological and operational decarbonization strategies, including electrification, hybrid energy systems, renewable generation, and energy storage solutions. Particular attention is given to the technical constraints associated with site isolation, extreme climatic conditions, intermittency of renewable energy sources, and mine-life considerations. Case studies from the Canadian mining industry illustrate practical implementation challenges and achievable performance improvements. The analysis shows that while renewable energy technologies and storage systems are increasingly cost-competitive, deep decarbonization of mining operations requires integrated energy management, long-duration storage solutions, and site-specific hybrid system design. The review highlights engineering and strategic pathways that can progressively reduce fossil fuel dependence and support the transition toward low-carbon mining energy systems.

This paper proposes a novel approach for optimal energy and reserve scheduling of wind farms by explicitly modelling wake interactions to enhance market participation and operational efficiency. Conventional methods often neglect wake effects, relying on power curve estimations that represent an upper limit and reduce market performance. To address this, a two-stage stochastic programming framework is developed, integrating a wake-aware power estimation model within the FLORIS simulation software. Wind and reserve uncertainties are addressed through scenario generation and reduction, enabling wind power producers to optimise participation in day-ahead energy and ancillary services markets, with particular focus on the Frequency Restoration Reserve (FRR). The wake-aware model provides more realistic power output predictions based on site-specific wind and atmospheric conditions, improving scheduling accuracy and reducing imbalance penalties. Wake steering is further employed to mitigate wake-induced losses and increase income through participation in ancillary services. The proposed approach is evaluated through a case study of the London Array offshore wind farm participating in the Great Britain (GB) electricity markets. Results show that conventional methods estimate production 12-13% higher, leading to imbalance penalties and 3% lower revenue compared with the wake-aware approach accounting for wake interactions. Moreover, the steering-enhanced approach yields an additional 1-2% increase in income relative to the wake-aware baseline. These findings underscore the value of accounting for wake interactions in wind farm scheduling and demonstrate the economic and operational benefits of active wake management, offering insights for improving grid stability and profitability as wind penetration continues to rise.

Importance of aggregating distributed energy resources (DERs) capacity to procure high-performance frequency regulation services ensuring adequate flexibility for renewable-rich power systems is increasing. Meanwhile, disregarding response performance variety arising from different technical characteristics and inherent uncertainties of DERs managed by an aggregator adversely impacts aggregated response (AR) from three viewpoints: technical feasibility of AR delivery, economic profit-making and fairness of capacity allocation. To tackle these challenges, this paper introduces a new probabilistic flexibility response index (FRI) to integrally evaluate DERs’ performance considering four factors: structure, control, communication, aggregation and uncertainties and interactions of these factors. Also, a multi-objective stochastic bidding strategy framework in the day-ahead energy and regulation markets is developed, in which the DERs capacity allocation is devised using the evaluation of their FRIs as the second objective. This framework lies within a mixed-integer linear programming model, considering uncertainties of resources, communication systems, AR, and market prices. The multi-objective structure of problem is handled through augmented ε -constraint and Fuzzy decision-making approaches. To validate the efficiency, scalability, and generality of the developed framework, it is implemented on three aggregators of different numbers and types of DERs participating in the ERCOT market context. The results show fundamental improvements regarding three viewpoints.

Fast charging stations (FCSs) for electric vehicles are associated with large power demands, often coinciding with peak power demands from other consumers. This places significant strain on distribution networks (DNs). To address this issue, this paper proposes a promising method that harnesses the untapped potential of railway systems and wasted regenerative braking energy (RBE) of trains in combination with a battery energy storage system (BESS) to supply EV charging station and participate in the FCS energy supply chain (FCS-ESCH). The proposed integrated approach, as the intermodal sustainable electric transportation system (SETS), aims to reduce the peak power demand of FCSs especially at strategic locations, such as parking areas close to electric railway stations (ERSs) and park and ride areas. To achieve this goal, an operation-aware optimization model is developed that determines the optimal sizes of the interfacing converter and the BESS, while also facilitating optimal energy exchange planning. A generic model for trains’ RBE production is proposed and adapted to the operation-aware optimization model to verify the effectiveness of the proposed approach by conducting simulations of a real case study that accurately replicates system behavior with the desired level of precision. Furthermore, sensitivity analyses are performed to explore the impact of varying the power rating of the converters responsible for transmitting RBE to the FCS-ESCH, as well as the per-unit price of BESS energy capacity. The results showcase the potential of employing SETS as an efficient means to mitigate the challenges associated with FCSs, especially peak shaving and cost reductions, paving the way for a more sustainable electric transportation system.

Electrification of final use sectors such as heating and mobility is often proposed as an effective pathway towards decarbonization of urban areas. In this context, power-driven heat pumps (HP) are usually strongly fostered as alternatives to fossil-burning boilers in municipal planning processes. In continental climates, this leads to substantially increased electricity demand in winter months that, in turn may lead to stress situations on local power distribution grids. Hence, in parallel to the massive implementation of electric HP, strategies must be put in place to ensure the grid stability and operational security, notably in terms of voltage levels, as well as transformer and line’s capacity limits. In this paper, three such strategies are highlighted within the specific situation of a mid-sized Swiss city, potentially representative of many continental, central Europe urban zones as a test-case. The hourly-based power flow simulations of the medium- and low-voltage distribution grids show the impact of various future scenarios, inspired from typical territorial energy planning processes, implying various degrees of heat pumps penetration. The first strategy relies on the implementation of decentralized combined heat and power (CHP) units, fed by the existing natural gas network and is shown to provide an effective pathway to accommodate heat pump electricity demand on urban power distribution grids. Two alternative solutions based on grid reinforcements and controlled usage of reactive power from photovoltaic (PV) inverters are additionally considered to ensure security constraints of grid operation and compared with the scenario relying on CHP deployment.