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This paper evaluates the feasibility of using wind power for power supply to coastal communities isolated from the main supply grid. The case study is Stewart Island, where the cost of electricity provided by a central diesel power station is higher than the grid network in New Zealand. The Princeton Ocean Model (POM) conducted by MetOcean Solutions Limited (MSL) is used to find Foveaux as an optimized site for generating wind power. Global Wind Atlas is used to plot the wind rose of current wind patterns in New Zealand. In the next step, wind speed data from each site are imported from the NASA database to WRPLOT view software and Homer Pro to find wind frequency distribution and output power in the area. The maximum annual power can be seen in WSW (32,299 kW hours/year), SW (20,111 kW hours/year) and W (15,622 kW hour/year) directions, respectively. [ABSTRACT FROM AUTHOR]

This paper is one of the limited studies to investigate rebound effects in sectoral electricity consumption and the specific case of New Zealand. New Zealand, like other OECD economies, has aimed for energy efficiency improvements and reduced electricity consumption from 9.2 MWh per capita in 2010 to 8.6 MWh per capita in 2015. However, following a significant decline since 2010, electricity consumption in the main New Zealand sectors is increasing. Energy conservation could play an important role in meeting the growing demand for electricity but rebound effects can affect the effectiveness of conservation policies. We decompose the sectoral electricity prices to capture the asymmetric demand response to electricity price changes and estimate electricity demand elasticity during 1980 and 2015 to estimate the sectoral rebound effects. We find partial rebound effects of 54% and 23% in the industrial and commercial sectors respectively while we find no rebound effect at the aggregate level. The rebound effect is insignificant in the residential sector. These findings lead to policy recommendations for sector specific energy conservation measures and policies. [ABSTRACT FROM AUTHOR]

In recent years, there has been considerable interest in the development of zero-emissions, sustainable energy systems utilising the potential of hydrogen energy technologies. However, the improper long-term economic assessment of costs and consequences of such hydrogen-based renewable energy systems has hindered the transition to the so-called hydrogen economy in many cases. One of the main reasons for this is the inefficiency of the optimization techniques employed to estimate the whole-life costs of such systems. Owing to the highly nonlinear and non-convex nature of the life-cycle cost optimization problems of sustainable energy systems using hydrogen as an energy carrier, meta-heuristic optimization techniques must be utilised to solve them. To this end, using a specifically developed artificial intelligence-based micro-grid capacity planning method, this paper examines the performances of twenty meta-heuristics in solving the optimal design problems of three conceptualised hydrogen-based micro-grids, as test-case systems. Accordingly, the obtained numeric simulation results using MATLAB indicate that some of the newly introduced meta-heuristics can play a key role in facilitating the successful, cost-effective development and implementation of hydrogen supply chain models. Notably, the moth-flame optimization algorithm is found capable of reducing the life-cycle costs of micro-grids by up to 6.5% as compared to the dragonfly algorithm. Image 1 • A metaheuristic-driven model is proposed to optimally design H 2 -based microgrids. • An energy management strategy is used to facilitate the uptake of fuel cell vehicles. • The performances of twenty metaheuristics are studied in terms of solution quality. • The moth-flame optimizer outperforms the well-respected algorithms in this area. • Levelized costs of electricity and H 2 are found to be well below the present rates. [ABSTRACT FROM AUTHOR]

One of the key challenges to greater renewable electricity supplies is the temporal mismatch between non-dispatchable renewable sources and peaks in electricity demand. In addition, increased electrification coupled with the de-carbonisation of electricity generation is likely to increase the scale of demand peaks. This could force investment in carbon-intensive peaker generation or capital intensive storage capacity as well as additional transmission and distribution network capacity which may then be substantially underutilised. Whilst considerable effort has been devoted to testing a range of demand response interventions to reduce or shift consumption, less attention has been given to the ability of certain appliances to permanently reduce demand at peak through energy efficiency. In this paper, we use a published model of future energy-efficient lighting uptake together with multi-year measured lighting demand data from a sample of residential households to model the potential power (MW) and energy (MWh) reductions of a 'business as usual' rate of efficient lighting adoption. Our estimates suggest that whilst lighting comprises ~ 4% of overall New Zealand annual electricity consumption, it comprises up to 12% of evening peak electricity consumption in winter. As a result, we estimate that by 2029, more efficient residential lighting could reduce New Zealand's total annual demand by 1 TWh and reduce the highest winter evening peaks (at 17:00) by at least 500 MW (9%). The winter evening demand reduction would be roughly equivalent to avoiding the need for additional generation capacity of the scale of New Zealand's Huntly Power Stations 1–4 (coal/gas) plus the Stratford peaker plant (gas open-cycle) and has clear implications for any electricity system that is intending to transition towards ~ 100% renewable generation at least cost. [ABSTRACT FROM AUTHOR]

A large part of the current New Zealand housing stock was built prior to the 1978 policy of mandatory insulation. Its average low energy efficiency has significantly contributed to the recent growth of health inequality, fuel poverty and building decay. Considering that these old houses will be a significant portion of the future stock, their retrofit is decisive to meet environmental imperatives and to tackle urgent health issues. The mid-century state housing, in particular, is a repository of ‘authenticity’ that needs to be respected, studied, protected and revitalised. It proves to be suitable for effective energy upgrade interventions, setting a new performance benchmark for New Zealand retrofitting practice. This paper presents problems, opportunities, strategies and predictable effects of retrofitting interventions on 1940–1960s state houses, discussing results of empirical research on a representative sample located in Auckland. Different retrofit packages, up to the Passive House standard, were identified for implementation in a pilot project. Indoor and outdoor environmental parameters of the selected house and two control houses were monitored over a one year period and used to define the ‘base case’ for thermal simulation. Several upgrade packages were then modelled to assess their impact on the house's thermal performance, comparing annual heating requirements of various insulation and ventilation options. [ABSTRACT FROM AUTHOR]

• Granular data-driven bottom-up modelling is a path to customer-centric energy utilities. • Real-world insights from New Zealand's largest gas and electricity distributor are shown. • The insights benefit from temporal and spatial analysis and data science techniques. • This approach is the platform for new applications such as scenario planning. In the current dynamic environment of rapid technology and behaviour change, customer centricity is essential to gain granular understanding of an increasingly diverse customer base. This paper presents how New Zealand's largest electricity and gas distribution operator is embracing this new ethos by developing a bottom-up data-driven model to understand customer energy use. The paper presents some key insights gained from this granular model to demonstrate the importance of customer- centricity for utility planning and management. [ABSTRACT FROM AUTHOR]

Many New Zealand residential homes suffer from poor indoor air quality (IAQ). Cold, damp and mould-ridden homes can cause severe respiratory health problems. Poor IAQ can arise due to inadequate insulation and ventilation and is compounded when dwellers cannot afford to heat their homes during colder months. Grandfathering of standards means many New Zealand houses have single glazed windows and insufficient or no wall insulation. These have become mandatory for newly built houses since 2016 under the New Zealand Standard NZS4246:2016 Energy Efficiency. This paper aims to present the results of modified ultraviolet germicidal irradiation (UVGI) lights-dehumidifier coupled with two different types of filters (carbon-fibre or polyester). The modified devices were designed to improve ambient air temperature by removing moisture, particulate matter and reducing mould and bacteria growth in a room. Seven different scenarios were investigated, which include combinations of UV light and filtration. The results showed that the UVGI was superior to filtration only; however, the polyester filter with UV lights (PFUV) was the most effective configuration. The PFUV effectively impeded the mould growth, with a 13.3% reduction in relative humidity and a 4.1 °C increase in the room temperature in the absence of a heating source. The results showed good potential for improving the IAQ of buildings. [ABSTRACT FROM AUTHOR]

Buildings contribute to greenhouse gas emissions that cause environmental impacts on climate change. Net Zero Energy (NZ) buildings would reduce greenhouse gases. The current definition of NZ lacks consensus and has created uncertainties, which cause delays in the adoption of NZ. This paper proposes a Process for Clarification to Accelerate the Net Zero (PC-A-NZ) through three integrated steps: variations, strategies, and requirements. We expand on the results in published NZ literature to clarify the differences in definition and strategy. The objective of this review is to (1) distinguish current variable parameters that are slowing the acceptance of NZ, and (2) focus the discussion internationally on moving faster toward applying NZ to a larger common agreement. The publications of global NZ target assessment and energy efficient strategies will be reviewed to address the main requirements in expediting NZ's successful progress. Our NZ review analysis highlights (1) how the existing NZ definitions and criteria differ, (2) how calculation strategies vary, and (3) how standards and requirements are often localized. The proposed PC-A-NZ will help policymakers and stakeholders to re-evaluate the existing definitions, standards, and requirements to optimize the use of renewable technologies, improved energy efficiency and electrification to speed up achieving the NZ targets. Definition: There are multiple NZ definitions that vary in source and supply requirement, timescale, emission source, and grid connection. [ABSTRACT FROM AUTHOR]

Over the last two decades, the residential building sector has been one of the largest energy consumption sectors in New Zealand. The relationship between that sector and household energy consumption should be carefully studied in order to optimize the energy consumption structure and satisfy energy demands. Researchers have made efforts in this field; however, few have concentrated on the association between household energy use and the cost of residential buildings. This study examined the correlation between household energy use and residential building cost. Analysis of the data indicates that they are significantly correlated. Hence, this study proposes time series methods, including the exponential smoothing method and the autoregressive integrated moving average (ARIMA) model for forecasting residential building costs of five categories of residential buildings (one-storey house, two-storey house, townhouse, residential apartment and retirement village building) in New Zealand. Moreover, the artificial neutral networks (ANNs) model was used to forecast the future usage of three types of household energy (electricity, gas and petrol) using the residential building costs. The t-test was used to validate the effectiveness of the obtained ANN models. The results indicate that the ANN models can generate acceptable forecasts. The primary contributions of this paper are twofold: (1) Identify the close correlation between household energy use and residential building costs; (2) provide a new clue for optimizing energy management. [ABSTRACT FROM AUTHOR]