
Michael D MurphyMunster Technological University | MTU
Michael D Murphy
PhD Engineering
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Publications (99)
Time series aggregation (TSA) is commonly used in energy system optimization to reduce model complexity and computational expenses by selecting periods to represent the entire time series. TSA’s accuracy has traditionally been assessed by comparing the objective values between the original and TSA models (assumed error). However, evaluating TSA fro...
This paper examined the practical impact of price-based demand-side management (DSM) for occupants of an office building connected to a renewable energy microgrid. There has been an absence of studies that have analyzed occupant reactions, in terms of perceived practicality, regarding the implementation of DSM in conjunction with factors including...
This paper addresses the integration of electric vehicle (EV) fleets into industrial smart grids to increase operational flexibility. It focuses on an extended multi-objective optimization problem that minimizes two primary objectives: (i) the electricity expenditure of a company using its employees' EV batteries as temporary distributed energy sto...
Network topology greatly influences both the economic and environmental performance of fifth generation district heating and cooling (5GDHC) systems. In this study the optimal trade-offs between the environmental and economic performance of 5GDHC network topologies for a five-building district with waste heat recovery were explored. A life cycle as...
In pasture-based grazing systems, farm roadways are a pivotal link to connect paddocks on the grazing platform to the milking parlour. However, their effectiveness in the efficient movement of the dairy herd between the grazing paddocks and the milking parlour has yet to be fully quantified. A validation experiment was conducted on a research farm...
The United Nations Sustainable Development Goals aim to double the productivity of small-medium food producers (2015–2030), while food demand is estimated to increase by 60 % by 2050. The objectives of this paper were to identify and quantify the relationship between energy efficiency and milking efficiency, identify the main energy consuming proce...
Digitalization and sector coupling enable companies to turn into flexumers. By using the flexibility of their multi-energy system (MES), they reduce costs and carbon emissions while balancing the electricity grid. However, to identify the necessary investments in energy conversion and storage technologies to leverage demand response (DR) potentials...
The increased average Irish dairy herd size in a post-quota environment has put heightened pressure on grazing infrastructure. In a rotational grazing system, grazing infrastructure consists of the paddock system, which delineates the grazing areas into appropriately sized grazing parcels, and the roadway network, which connects these paddocks to t...
Digitalization and sector coupling enable companies to turn into flexumers. By using the flexibility of their multi-energy system (MES), they reduce costs and carbon emissions while stabilizing the electricity system. However, to identify the necessary investments in energy conversion and storage technologies to leverage demand response (DR) potent...
In this work, a topology optimization framework for district thermal energy systems is presented. The framework seeks to address the questions, for a given district, "What is the best subset of buildings to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?" A particle swarm optim...
A major barrier to investments in clean and future-proof energy technologies of local multi-energy systems (L-MESs) is the lack of knowledge about their impacts on profitability and carbon footprints due to their complex techno-economic interactions. To reduce this problem, decision support tools should integrate various forms of decarbonization me...
With a growing demand for milk and dairy products coupled with concerns regarding greenhouse gas emissions, the sustainable use of on-farm energy resources is essential. Milk production requires electrical energy for powering plant equipment, liquid fuels for powering machinery, indirect energy for fertilizer and feed production, and embodied energ...
Integrating fleets of electric vehicles (EVs) into industrial applications with smart grids is an emerging field of important research. It is necessary to get a comprehensive overview of current approaches and proposed solutions regarding EVs with vehicle-to-grid and smart charging. In this paper, various approaches to battery modeling and demand r...
Currently, there is a strong need to find practical solutions towards meeting the expected efficiency and overcoming recurring sustainability challenges in the global dairy sector [...]
Machine learning applications are becoming more ubiquitous in dairy farming decision support applications in areas such as feeding, animal husbandry, healthcare, animal behavior, milking and resource management. Thus, the objective of this mapping study was to collate and assess studies published in journals and conference proceedings between 1999...
Artificial neural network (ANN) models were developed to predict milk cooling, milk harvesting and water heating electricity consumption using data collected from 56 pasture-based Irish dairy farms. The methodology employed variable selection, outlier detection, hyper-parameter tuning and nested cross-validation. The ANN models were developed to pr...
Efficient grass-based livestock production depends on precise allocation of pasture to the herd in the form of herbage mass (HM). Accurate measurement of HM results in increased utilisation of grass in the herd’s diet and consequently reductions in whole-farm feed inputs, emissions and costs. The rising plate meter (RPM) is an established method of...
The development of precision grass measurement technologies is of vital importance to securing the future sustainability of pasture-based livestock production systems. There is potential to increase grassland production in a sustainable manner by achieving a more precise measurement of pasture quantity and quality. This review presents an overview...
Accurate estimation of herbage mass (HM) is essential for optimising grass utilisation and increasing profit for pasture-based livestock agriculture. The rising plate meter (RPM) is used for predicting HM based on average compressed sward height (CSH). Sampling resolution and distribution are primary parameters in determining spatial heterogeneity...
The objective of this paper was to quantify the economic and environmental effects of changing a dairy farm’s milking start times. Changing morning and evening milking start times could reduce both electricity costs and farm electricity related CO2 emissions. However, this may also involve altering farmer routines which are based on practical consi...
Price-based demand response (PBDR) has recently been attributed great economic but also environmental potential. However, the determination of its short-term effects on carbon emissions requires the knowledge of marginal emission factors (MEFs), which compared to grid mix emission factors (XEFs), are cumbersome to calculate due to the complex chara...
The aim of this study was to develop near infrared spectroscopy (NIRS) calibrations to predict quality parameters, dry matter (DM, g kg⁻¹) and crude protein (CP, g kg⁻¹ DM), in fresh un-dried grass. Knowledge of these parameters would enable more precise allocation of quality herbage to grazing livestock. Perennial ryegrass samples (n = 1 615) were...
In this study, a grey box (GB) model for simulating internal air temperatures in a naturally ventilated nearly zero energy building (nZEB) was developed and calibrated, using multiple data configurations for model parameter selection and an automatic calibration algorithm. The GB model was compared to a white box (WB) model for the same application...
Price-based demand response (PBDR) has recently been attributed great economic but also environmental potential. However, the determination of its short-term effects on carbon emissions requires the knowledge of marginal emission factors (MEFs), which compared to grid mix emission factors (XEFs), are cumbersome to calculate due to the complex chara...
The average global cooling demand in non-residential buildings is expected to increase by over 275% between now and 2050. Controlled passive cooling is fundamental to successful operational performance of buildings and in mitigating energy that would otherwise be consumed by mechanical systems. The aim of this study was to determine the resilience...
Accurate and efficient estimation of herbage mass is essential for optimising grass utilisation and increasing profit for pasture farming. There is no definitive sampling protocol for grass measurement on Irish pastures. This paper presents the Grass Measurement Optimisation Tool (GMOT), designed to generate measurement protocols that optimise for...
The aim of this study was to develop a financial and renewable multi-objective optimization (FARMOO) method for dairy farms. Due to increased global milk production and European Union policies concerning renewable energy contributions, the optimization of dairy farms from financial and renewable standpoints is crucial. The FARMOO method found the o...
The production of milk must be balanced with the sustainable consumption of water resources to ensure the future sustainability of the global dairy industry. Thus, this review article aimed to collate and summarize the literature in the dairy water-usage domain. While green water use (e.g., rainfall) was found to be largest category of water use on...
The global consumption of dairy produce is forecasted to increase by 19% per person by 2050. However, milk production is an intense energy consuming process. Coupled with concerns related to global greenhouse gas emissions from agriculture, increasing the production of milk must be met with the sustainable use of energy resources, to ensure the fut...
The aim of this paper was to investigate the trade-offs that can be achieved between optimizing the electricity costs of a building integrated microgrid, while simultaneously facilitating high levels of wind penetration in a smart grid. This study applied multi-objective optimization to obtain a daily charge and discharge schedule of a battery bank...
As the cooling energy demand in buildings is set to increase dramatically in the future, the exploitation of passive solutions like natural ventilation could prove vital in reducing the reliance on mechanical systems. Models that can predict air temperature accurately in naturally ventilated mode are key to understanding the potential of natural ve...
This body of work pertained to the development and application of the Decision Support System for Energy use in Dairy Production (DSSED), an online portal offering decision support to dairy farmers wishing to invest in new farm infrastructure or upgrade their existing farm infrastructure. Increasing the utilization of energy efficient and renewable...
This body of work pertained to the development of the Decision Support System for Energy use in Dairy Production (DSSED), a combined energy modelling and optimization platform offering decision support for dairy farmers wishing to invest in new energy efficient and/or renewable technologies, upgrade their existing farm infrastructure or optimize th...
The objective of this study was to analyze the effect of adding meteorological data to the training process of two milk production forecast models. The two models chosen were the nonlinear auto-regressive model with exogenous input (NARX) and the multiple linear regression (MLR) model. The accuracy of these models were assessed using seven differen...
The aim of this paper was to develop a Dairy Multi-Objective Optimization (DAIRYMOO) method to carry out multi-objective optimization of dairy farm equipment, management practices and electricity tariffs, optimizing based on a user specified economic and environmental weighting factor. Models of both solar thermal water heating and heat recovery sy...
The objective of this paper was to develop a discrete infrastructure optimization model for economic assessment on dairy farms (DIOMOND) to maximize return on investment (ROI) in dairy farm infrastructure over a specified time horizon. Optimizing ROI in dairy farm infrastructure is essential since the choice of technology, electricity tariff and ma...
This paper proposes strategies to optimize the daily charge and discharge schedule of a battery bank, in order to minimize the operating cost of a building that uses renewable energy sources. The schedule was optimized using a range of battery charge and discharge rates over a 24 h period. These rates were controlled using a genetic algorithm (GA)...
Even in Northern European climates, overheating in many Nearly Zero Energy Buildings is a barrier to year round occupant satisfaction with the indoor thermal environment. Improved energy performance and enhanced thermal comfort should not be perceived as a rigid dichotomy of concepts. However, an acceptable thermal environment, during extended cool...
During cooling seasons, a progressively warmer and increasingly urban world is leading to hostile internal thermal environments in many high-performance buildings. Correctly Implemented, Ventilative Cooling can mitigate unwanted building overheating while minimising cooling loads. Identifying different solutions with proven performance
can be inval...
This study analysed the performance of a range of machine learning algorithms when applied to the prediction of electricity and on-farm direct water consumption on Irish dairy farms. Electricity and water consumption data were attained through the utilisation of a remote monitoring system installed on a study sample of 58 pasture-based, commercial...
An analysis into the impact of milk production, stock numbers, infrastructural equipment, managerial procedures and environmental conditions on dairy farm electricity and water consumption using multiple linear regression (MLR) modelling was carried out. Electricity and water consumption data were attained through the utilisation of a remote monito...
This study compared multiple linear regression (MLR) and support vector machine (SVM) models for predicting the annual electricity consumption of 20 Irish dairy farms, at a farm and catchment (combined) level. Model input variables were constrained to milk production, stock numbers, infrastructural equipment and managerial procedures to allow predi...
The aim of this paper was to perform an economic analysis on the use of photovoltaic (PV) systems on dairy farms. Dairy farm energy and economic models and a PV system model were employed in this work to ascertain the financial feasibility of PV systems in an Irish dairy farming context. Farms of three different sizes with four equipment configurat...
Accurate estimation of herbage mass is essential for optimizing grass utilization and increasing profit margins for pasture based livestock farming. The rising plate meter is a tool for predicting herbage mass based on average compressed sward height (CSH). Sampling resolution and distribution are the primary parameters in determining spatial heter...
Under European milk quotas, dairy farms in Europe were limited in the amount of milk they could produce. While quotas were gradually increased over the past four decades, European milking quotas totally were abolished in April 2015, to help meet an expected 20% increase in the global consumption of milk and dairy products by 2050. With this, Europe...
The objective of this study was to create a tool that will enable renewable energy microgrid (REμG) facility users to make informed decisions on the utilization of electrical power output from a building integrated REμG connected to a smart grid. A decision support tool for renewable energy microgrids (DSTREM) capable of predicting photovoltaic arr...
An automated rising plate meter has been developed as a system of measuring grass compressed sward height (CSH) to best estimate herbage mass (HM) within paddocks, via a link to an ICT system. The aim of this project was to improve the accuracy of this system through the development of a more robust HM prediction model and sampling protocol. Weekly...
Robust retrofitting is integral to reducing the energy consumption of the existing building stock. Simulation plays a key role in determining the most effective retrofit solution for a particular building. While many synthetic test cells provide an environment to validate whole building simulation tools, calibration reflects the real operation of b...
With the abolishment of the European Union milk quota system in April 2015, the Irish government has targeted a 50% increase in milk production by 2020 over 2007–09 levels. Resulting milk price volatility and environmental constraints are forcing farmers to produce milk at lower costs with a lower overall environmental footprint. This entails using...
We expect an increase in the demand for animal products in the future because of global human population growth (especially in developing countries), growing incomes and increasing urbanisation. The demand for animal products is expected to double by 2050 (Rae, 1998, FAO, 2009), which will create challenges to ensure that milk is produced in an env...
The development of a Virtual Laboratory for control systems simulation is presented in this paper. A mechanistic quadrotor model was created using existing theory and a feedback controller was applied for altitude and coordinate control. The simulation environment was built on a transparent modelling platform that allowed the users to easily modify...
In this study, the effectiveness of a retrofitted natural ventilation system in a low energy building was evaluated, both subjectively and objectively, in response to an overheating scenario during shoulder seasons. Four ventilation configurations were evaluated including one control (no ventilation) configuration. Standardised questionnaires were...
This paper proposes strategies for operating cost optimisation of a multi-energy source building. The optimisation is based on a day-ahead forecast of building energy usage. The building in question is powered by multiple energy sources including a wind turbine, a photovoltaic system, a lead-acid battery system, and the national power grid. The opt...