Simplified high-level investigation methodology for energy saving initiatives on deep-level mine compressed air systems
Marginal deep-level mines in South Africa are struggling due to current economic conditions. Reducing operating cost on these marginal mines will increase their profitability. Electricity is one of the fastest growing expenditures of which compressed air accounts for approximately 17% of the total electricity cost. Deep-level mine compressed air systems are often mismanaged, which results in energy wastage. Thus, energy service companies (ESCOs) have identified compressed air systems as an area with significant potential for reducing the operating costs of deep-level mines. ESCOs have expertise in different fields to investigate, quantify and realise new energy saving initiatives. Usually, a client approaches an ESCO to examine new possible energy saving initiatives. However, due to current financial constraints, marginal mines cannot afford the service of energy savings experts. Previously, Eskom provided Integrated Demand Management (IDM) funding to motivate both ESCOs and clients to implement energy saving initiatives. However, funding for these initiatives has reduced significantly and only rewards load reduction within the Eskom evening peak period. The problem is that reward is not guaranteed for the investment required from ESCOs during investigation periods. Therefore, ESCOs are required to take risks while investigating new potential energy saving projects. These investigations include benchmarking methods for ranking energy performances and tools for quantifying potential energy saving targets. However, it is not feasible for ESCOs to investigate all potential energy saving projects due to the constraints of existing investigation processes and reduced IDM funding. Available benchmarking methods require multivariable data sets. These data sets are not always readily accessible or feasible to collect during the investigation phase, which could then prolong investigation periods. The first aim of this study is developing a new single-variable benchmarking method that will simplify benchmarking during investigations on deep-level mine compressed air systems. The second aim of this study is simplifying current tools used to quantify potential energy savings. Existing approaches quantify potential energy savings with complex simulation models and detailed audits. The problem is that simulation packages are often time-consuming, and require skilled workers and multivariable data sets as inputs. This complexity adds strain to an ESCO's resources. Therefore, this study focuses on developing a practical tool that only requires power consumption to quantify potential energy savings during investigations. As a whole, research conducted for this study further highlights a need to reduce the risks and investments required from ESCOs during investigations. The new benchmarking method and savings quantification tool were combined into an integrated investigation methodology. This integration provides a simplified high-level investigation methodology that will reduce the time, cost and resources required by ESCOs while investigating new energy saving projects. Consequently, more potential energy saving projects will be feasible for ESCOs to investigate. The new methods and tools developed in this study were verified with available methods and tools from previous studies. These methods and tools were validated by applying them to the compressed air systems of two actual deep-level mines, which are referred to as Case Study 1 and Case Study 2. The novel benchmarking method proved successful for ranking the compressed air systems according to scope for improvement. The new practical tool to quantify potential energy savings during Eskom evening peak period was 98% accurate in Case study 1 and 87% accurate in Case Study 2. The simplified high-level investigation methodology devlivered the required results wihtin 10 minutes with only power consumption as in input. Conventional investigation processes implemented by ESCOs used multivariable data sets, which required a minimum of 4 days in Case study 1 and 12 days in Case study 2. These case study results proved that the new investigation methodology can be used with limited resources and will improve the feasibility for ESCOs to investigate more potential energy saving initiates. The new investigation methodology was further implemented on a holistic application to identify potential missed energy saving opportunities on 25 existing compressed air energy saving projects. As a result, it was determined that an additional saving of 82.7 MW could be realised during Eskom's evening peak period. This equates to an approximate annual cost saving of R60 million. This potential savings could contribute to the sustainability of marginal deep-level mines in South Africa.
- Engineering