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Marwan Marwan - One of the best experts on this subject based on the ideXlab platform.

  • Optimal Demand Side Response conSidering to the peak price in the peak season
    2017 International Conference on High Voltage Engineering and Power Systems (ICHVEPS), 2017
    Co-Authors: Marwan Marwan, Syafaruddin
    Abstract:

    The aim of this research is to assist the consumer to control the air conditioning load during the peak season. Demand Side Response model was applied to manage inSide room temperature to keep comfortable for the consumer. A simulation study is illustrated the effect of Demand Side Response model application for air conditioning in reSidential house in Makassar city. In this research there are three kind of characteristic of building was analyzed. The physical characteristic of building was based on the heat transfer coefficient from floor, wall and ceiling conSidering to the total area of the room and outSide room temperature. The result of this research indicated that this model assist to the consumer to reduce energy cost. Electricity market price in South Sulawesi was chosen for the case study conSidering to the characteristic of building for reSidential house. In this case, a peak season assumed was only occurred at 18.00 during half hour.

  • Optimise Energy Cost for Air Conditioning based on the Market Price under Demand Side Response Model
    International Journal of Electrical and Computer Engineering, 2017
    Co-Authors: Marwan Marwan, Syafaruddin Syafaruddin
    Abstract:

    The increasing contribution of air conditioning (AC) to energy consumption has received conSiderable attention in the past and will continue to do so in the coming years, from Indonesian government, state electricity company and consumers. Managing Demand on the electricity system in peak sessions is the most direct way to address the AC peak Demand issue. The aim of this research is to developed a consumer Demand Side Response (DSR) model to assist both electricity consumers/aggregator and electricity provider to minimise energy cost if peak price occured in the peak season. The proposed model allows consumers to independently and proactively manage air conditioning load through an aggregator. This research examines how the control system applies DSR model if a price spike may occur at 18.00 during one hour. The results indicate, consumer and aggregator could gain collective benefits when the consumer controls the air conditioning under the DSR program. The model was tested in Makassar City South Sulawesi conSidering to the caharacteristic of the room and air conditioning in a reSidential house.

  • Demand-Side Response model to avoid spike of electricity price
    Journal of Process Control, 2014
    Co-Authors: Marwan Marwan, Gerard Ledwich, Arindam Ghosh
    Abstract:

    The aim of this work is to develop a Demand-Side-Response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity Demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load conSidering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

  • Smart grid-Demand Side Response model to mitigate prices and peak impact on the electrical system
    2013
    Co-Authors: Marwan Marwan
    Abstract:

    The aims of this project is to develop Demand Side Response model which assists electricity consumers who are exposed to the market price through aggregator to manage the air-conditioning peak electricity Demand. The main contribution of this research is to show how consumers can optimise the energy cost caused by the air-conditioning load conSidering the electricity market price and network overload. The model is tested with selected characteristics of the room, Queensland electricity market data from Australian Energy Market Operator and data from the Bureau of Statistics on temperatures in Brisbane, during weekdays on hot days from 2011 - 2012.

  • Smart grid-Demand Side Response model for optimization air conditioning
    2012
    Co-Authors: Marwan Marwan, Gerard Ledwich, Arindam Ghosh
    Abstract:

    The growing Demand of air-conditioning is one of the largest contributors to Australia's overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer Demand Side Response model to assist electricity consumers to mitigate peak Demand on the electrical network. The model developed Demand Side Response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal Response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission.

Fouad Kamel - One of the best experts on this subject based on the ideXlab platform.

  • Demand Side Response to mitigate electrical peak Demand in eastern and southern Australia
    Energy Procedia, 2011
    Co-Authors: Marwan Marwan, Fouad Kamel
    Abstract:

    The aim of this work is to develop a Demand-Side-Response (DSR) model, which assists electricity end-users to be engaged in mitigating peak Demands on the electricity network in Eastern and Southern Australia. The proposed innovative model will comprise a technical set-up of a programmable internet relay, a router, solid state switches in addition to the suitable software to control electricity Demand at user's premises. The software on appropriate multimedia tool (CD Rom) will be curtailing/shifting electric loads to the most appropriate time of the day following the implemented economic model, which is designed to be maximizing financial benefits to electricity consumers. Additionally the model is targeting a national electrical load be spread-out evenly throughout the year in order to satisfy best economic performance for electricity generation, transmission and distribution. The model is applicable in region managed by the Australian Energy Management Operator (AEMO) covering states of Eastern-, Southern-Australia and Tasmania.

  • Integrating electrical vehicles to Demand Side Response scheme in Queensland Australia
    2011 IEEE PES Innovative Smart Grid Technologies, 2011
    Co-Authors: Marwan Marwan, Gerard Ledwich, Arindam Ghosh, Fouad Kamel
    Abstract:

    Depleting fossil fuel resources and increased accumulation of greenhouse gas emissions are increasingly making electrical vehicles (EV) attractive option for the transportation sector. However uncontrolled random charging and discharging of EVs may aggravate the problems of an already stressed system during the peak Demand and cause voltage problems during low Demand. This paper develops a Demand Side Response scheme for properly integrating EVs in the Electrical Network. The scheme enacted upon information on electricity market conditions regularly released by the Australian Energy Market Operator (AEMO) on the internet. The scheme adopts Internet relays and solid state switches to cycle charging and discharging of EVs. Due to the pending time-of-use and real-price programs, financial benefits will represent driving incentives to consumers to implement the scheme. A wide-scale dissemination of the scheme is expected to mitigate excessive peaks on the electrical network with all associated technical, economic and social benefits.

  • Optimum Demand Side Response of smart grid with renewable energy source and electrical vehicles
    2011
    Co-Authors: Marwan Marwan, Fouad Kamel
    Abstract:

    The paper presents a Demand Side Response scheme, which assists electricity consumers to proactively control own Demands in such a way to deliberately avert congestion periods on the electrical network. The scheme allows shifting loads from peak to low Demand periods in an attempt to flattening the national electricity requirement. The scheme can be concurrently used to accommodate the utilization of renewable energy sources, that might be available at user's premises. In addition the scheme allows a full-capacity utilization of the available electrical infrastructure by organizing a wide-use of electric vehicles. The scheme is applicable in the Eastern and Southern States of Australia managed by the Australian Energy Market Operator. The results indicate the potential of the scheme to achieve energy savings and release capacity to accommodate renewable energy and electrical vehicle technologies.

  • Mitigation of electricity price/Demand using Demand Side Response smart grid model
    2011
    Co-Authors: Marwan Marwan, Fouad Kamel, Wei Xiang
    Abstract:

    The paper describes a Demand-Side-Response scheme, which enables electricity users to act upon electrical market information provided to them on the internet to be reducing/removing peak Demands and the associated escalated energy prices. The proposed scheme enables the customer to manage the use of electric energy using a Demand Side Response smart grid technique in order to curtail or shift loads from peak- to low-Demand periods. The technique is using computer-controlled switches and pre-programmed relays able to control loads on user's premises following the network's load profile. This technique is proposed in the first instance for East and South Australia where the Australian Energy Market Operator (AEMO) is publicly communicating information about national electrical energy Demand and price on the internet. The scheme is targeting best economic conditions for users, suppliers electrical generators and the electrical network. To evaluate the scheme simulations have been conducted using a typical Demand-price profile for Queensland. The results are indicating the impact of this scheme on possible savings in electrical energy consumption.

  • Demand Side Response load management modelling encountering electrical peak Demands in eastern and southern australia smart grid tools
    2010
    Co-Authors: Marwan Marwan, Fouad Kamel
    Abstract:

    The paper describes a Demand-Side Response scheme consisting of computer-controlled switches operated at end-users premises to shift loads targeting a homogenized national Demand profile. The paper presents further simulation of the economic model corresponding to the above described scheme representing an incentive-based Demand Response. In the simulation the impact of these programs on load shape and peak load magnitudes, financial benefit to users as well as reduction of energy consumption are shown. The results demonstrated more homogenized load curves at lesser peak load magnitudes and reduced energy cost.

Goran Strbac - One of the best experts on this subject based on the ideXlab platform.

  • endogenously stochastic Demand Side Response participation on transmission system level
    IEEE International Energy Conference, 2018
    Co-Authors: Spyros Giannelos, Ioannis Konstantelos, Goran Strbac
    Abstract:

    Electricity Demand as well as renewables capacity are about to grow globally within the next decades, potentially posing challenges related to increased peaks. The safe accommodation of these peaks may raise the need for investments both in conventional as well as in new technologies such as Demand Side Response. This paper focuses on one aspect of the uncertainty that characterizes investment planning, namely the endogenous or decision-dependent uncertainty (DDU), i.e. uncertainty that can resolve only after an investment decision has been made as opposed to exogenous uncertainty that resolves simply through the passage of time. The novel mathematical formulation is presented and applied to a case study on the Great Britain (GB) transmission system to showcase the concept of DDU.

  • Option Value of Demand-Side Response Schemes Under Decision-Dependent Uncertainty
    IEEE Transactions on Power Systems, 2018
    Co-Authors: Spyros Giannelos, Ioannis Konstantelos, Goran Strbac
    Abstract:

    Uncertainty in power system planning problems can be categorized into two types: exogenous and endogenous (or decision-dependent) uncertainty. In the latter case, uncertainty resolution depends on a choice (the value of some decision variables), as opposed to the former case in which the uncertainty resolves automatically with the passage of time. In this paper, a novel stochastic multistage planning model is proposed that conSiders endogenous uncertainty around consumer participation in Demand-Side Response (DSR) schemes. This uncertainty can resolve following DSR deployment in two possible ways: locally (at a single bus) and globally (across the entire system). The original formulation is decomposed with the use of Benders decomposition to improve computational performance. Two versions of Benders decomposition are applied: the classic version involving sequential implementation of all operational subproblems and a novel version, specific to problems with endogenous uncertainty, which allows for the parallel execution of only those operational subproblems that are guaranteed to have a unique contribution to the solution. Case studies on 11-bus and 123-bus systems illustrate the process of endogenous uncertainty resolution and underline the strategic importance of deploying DSR ahead of time.

  • Assessing the value and impact of Demand Side Response using whole-system approach
    Proceedings of the Institution of Mechanical Engineers Part A: Journal of Power and Energy, 2017
    Co-Authors: Danny Pudjianto, Goran Strbac
    Abstract:

    This paper describes the whole-system based model called Whole-electricity System Investment Model to quantify the benefits of Demand flexibility. Whole-electricity System Investment Model is a holistic and comprehensive electricity system analysis model, which simultaneously optimises the long-term investment decisions against real-time operation decisions taking into account the flexibility provided by Demand. The optimisation conSiders the impact of Demand Side Response across all power subsystems, i.e. generation, transmission and distribution systems, in a coordinated fashion. This allows the model to capture the potential conflicts and synergies between different applications of Demand Side Response in supporting particularly intermittency management at the national level, improving capacity margin, and minimising the cost of electrification. The impact and value of Demand Side Response driven by whole-system approach are compared against the impact and value of distribution system operator or trans...

  • ANALYSIS OF CUSTOMERS' PERFORMANCE IN INDUSTRIAL & COMMERCIAL Demand Side Response TRIALS
    2015
    Co-Authors: T Ustinova, M Woolf, J. E. Ortega Calderon, Mark Bilton, H O'brien, Simon H. Tindemans, Predrag Djapic, Goran Strbac
    Abstract:

    Modern distribution networks face the challenges of growing Demand and ageing assets. Demand Side Response (DSR) provided by Industrial and Commercial (I&C) customers is viewed as a means to help reduce risk of substations and feeders overloading and thus to defer network reinforcement. However, real world experience regarding the use of I&C DSR in distribution networks is currently limited, and experimental data from trials and case studies is sparse. The recently completed Low Carbon London project included I&C DSR trials aimed at understanding the potential for I&C DSR for distribution network constraint management. This paper presents the data obtained in the course of these trials and discusses in detail the process of data collection, selection, baseline construction, preparation for analysis and subsequent development of probabilistic Response models. Additionally, a potential issue – the presence of a payback effect in customers responding with HVAC units – is observed and discussed.

  • analysis of customers performance in industrial commercial Demand Side Response trials
    23rd International Conference on Electricity Distribution (CIRED 2015), 2015
    Co-Authors: T Ustinova, M Woolf, Mark Bilton, Simon H. Tindemans, Predrag Djapic, J Ortega E Calderon, H Obrien, Goran Strbac
    Abstract:

    Modern distribution networks face the challenges of growing Demand and ageing assets. Demand Side Response (DSR) provided by Industrial and Commercial (I&C) customers is viewed as a means to help reduce risk of substations and feeders overloading and thus to defer network reinforcement. However, real world experience regarding the use of I&C DSR in distribution networks is currently limited, and experimental data from trials and case studies is sparse. The recently completed Low Carbon London project included I&C DSR trials aimed at understanding the potential for I&C DSR for distribution network constraint management. This paper presents the data obtained in the course of these trials and discusses in detail the process of data collection, selection, baseline construction, preparation for analysis and subsequent development of probabilistic Response models. Additionally, a potential issue – the presence of a payback effect in customers responding with HVAC units – is observed and discussed.

Pierluigi Mancarella - One of the best experts on this subject based on the ideXlab platform.

  • Flexible investment under uncertainty in smart distribution networks with Demand Side Response: Assessment framework and practical implementation
    Energy Policy, 2016
    Co-Authors: Jonathan A. Schachter, Pierluigi Mancarella, John Moriarty, Rita Shaw
    Abstract:

    Classical deterministic models applied to investment valuation in distribution networks may not be adequate for a range of real-world decision-making scenarios as they effectively ignore the uncertainty found in the most important variables driving network planning (e.g., load growth). As greater uncertainty is expected from growing distributed energy resources in distribution networks, there is an increasing risk of investing in too much or too little network capacity and hence causing the stranding and inefficient use of network assets; these costs are then passed on to the end-user. An alternative emerging solution in the context of smart grid development is to release untapped network capacity through Demand-Side Response (DSR). However, to date there is no approach able to quantify the value of ‘smart’ DSR solutions against ‘conventional’ asset-heavy investments. On these premises, this paper presents a general real options framework and a novel probabilistic tool for the economic assessment of DSR for smart distribution network planning under uncertainty, which allows the modeling and comparison of multiple investment strategies, including DSR and capacity reinforcements, based on different cost and risk metrics.

  • Distribution network support from multi-energy Demand Side Response in smart districts
    2016 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), 2016
    Co-Authors: E A M Ceseña, Pierluigi Mancarella
    Abstract:

    This work investigates from a techno-economic perspective the potential for groups of smart buildings distributed throughout an area to provide Demand Side Response (DSR) as a means to increase electricity distribution network capacity. More specifically, intelligent multi-energy flows between buildings within a smart district are optimized with the aim of reducing energy costs for end-users and network costs for Distribution Network Operators (DNOs). For this purpose, an optimization methodology that captures the impacts of DSR by explicitly modelling (ii) interactions between different energy vectors through an integrated electricity-heat-gas model, (ii) security limits and (iii) DNO investment decisions and preferred deployment of DSR, is proposed. The methodology is illustrated with a real UK multi-energy district where an intelligent information platform (i.e., the District Information Modelling and Management for Energy Reduction (DIMMER) platform under development in the homonymous European project) is being tested. The significant flexibility of the smart district to provide DSR services without compromising end-user comfort levels (i.e., avoiding load curtailment) by intelligently exchanging different energy vectors is demonstrated. The results highlight a strong business case for DSR, as the associated deployment costs are minimal thanks to the flexibility of the smart district, while network savings are significant.

  • electrical network capacity support from Demand Side Response techno economic assessment of potential business cases for small commercial and reSidential end users
    Energy Policy, 2015
    Co-Authors: E A M Ceseña, Nicholas Good, Pierluigi Mancarella
    Abstract:

    Demand Side Response (DSR) is recognised for its potential to bring economic benefits to various electricity sector actors, such as energy retailers, Transmission System Operators (TSOs) and Distribution Network Operators (DNOs). However, most DSR is provided by large industrial and commercial consumers, and little research has been directed to the quantification of the value that small (below 100kW) commercial and reSidential end-users could accrue by providing DSR services. In particular, suitable models and studies are needed to quantify potential business cases for DSR from small commercial and reSidential end-users. Such models and studies should conSider the technical and physical characteristics of the power system and Demand resources, together with the economic conditions of the power market. In addition, the majority of research focuses on provision of energy arbitrage or ancillary services, with very little attention to DSR services for network capacity support. Accordingly, this paper presents comprehensive techno-economic methodologies for the quantification of three capacity-based business cases for DSR from small commercial and reSidential end-users. Case study results applied to a UK context indicate that, if the appropriate regulatory framework is put in place, services for capacity support to both DNOs and TSOs can result into potentially attractive business cases for DSR from small end-users with minimum impact on their comfort level.

Valerie Livina - One of the best experts on this subject based on the ideXlab platform.

  • Carbon savings in the UK Demand Side Response programmes
    Applied Energy, 2015
    Co-Authors: E. T. Lau, Q. Yang, Gareth A. Taylor, Lee Stokes, Alistair B. Forbes, Paul Clarkson, Paul S. Wright, Valerie Livina
    Abstract:

    We quantify carbon (CO2) savings in the Demand Side Response (DSR) programmes. We conSider Short Term Operating Reserve (STOR), Triad, Fast Reserve and Smart Meter roll-out, with various types of smart interventions involved (using diesel generators, hydro-pumped generation and use of tariffs). We model CO2 emissions in each of the DSR programmes with appropriate configurations and assumptions used in the energy industry. This enables us to compare carbon emissions between the business-as-usual (BAU) solutions and the smart intervention applied, thus deriving the carbon savings. Whether such DSR produces positive CO2 savings or not depends on the used technologies, as well as the scale of the interventions, which we illustrate in examples.

  • Carbon savings of Demand Side Response of a UK energy aggregator.
    2015
    Co-Authors: Engtseng Lau, Valerie Livina
    Abstract:

    We report carbon emissions and savings (tonnesCO2) of the STOR programme based on data from a UK Demand Response aggregator company that utilises diesel generators, CHP and turn down methods. Short-Term Operating Reserve, STOR, is one of the Demand Side Response (DSR) programme that are being run by the National Grid in the UK. The purpose of STOR programme is to reduce the load on the energy system by means of various subsitution and reduction techniques. In particular, STOR allows its subscribed providers to generate substituting power. In the STOR programme we study carbon savings based on data obtained from a UK based Response aggregator company. This company provides various types of intervention (using diesel generators, Combined-Heat and Power (CHP) and Demand reduction (turn-down)) at times of peak Demand. Whether such DSR produces carbon savings or not, depends on the used technologies, as well as the scale of the interventions.

  • The UK electricity Demand Side Response: Carbon savings analysis
    2015 12th International Conference on the European Energy Market (EEM), 2015
    Co-Authors: Engtseng Lau, Q. Yang, Gareth A. Taylor, Lee Stokes, Alistair B. Forbes, Valerie Livina
    Abstract:

    We quantify carbon emissions and savings in Demand Side Response (DSR) programmes, such as Short Term Operating Reserve (STOR) and Triad, substituting grid energy in the UK power networks. We model each of the DSR programmes with configurations and assumptions appropriate for the UK energy industry. This enables us to compare carbon emissions between the business-as-usual (BAU) and the smart intervention applied, thus deriving carbon savings. Standby diesel generators are the main intervention for most of the DSR programmes. Carbon emissions of standby diesel generators are compared with the BAU solution. Whether such a DSR produces carbon savings or not depends on the scale and operational policies of the interventions.