Smart metering of renewable microgenerators by output pattern recognition

Micro generators need to be registered and metered when connected to the distribution network, and the energy source for renewable generation needs to be certified. Pattern recognition techniques are described which allow these functions to be performed automatically as part of a smart metering system. Potential benefits are reduced costs for Distribution Network Operators, simplified installation procedures for micro generator suppliers, and for users improved performance information and access to the financial incentives for renewable generatio

Management of Demand Profiles on Mini-Grids in Developing Countries Using Timeslot Allocation

Stand-alone mini-grids provide vital energy access to rural communities across the Developing World where economic constraints necessitate optimal cost-effectiveness without compromising reliability or quality of service. Managing electricity demand to match supply availability – for example, by incentivizing consumers to operate loads at specific times – can contribute to this aim. This paper addresses a method to achieve this, whereby timeslots are sold in which additional power is made available to participating consumers with high-powered, commercial loads, such as grain mills. Using a low-cost microprocessor to control remotely-switchable power sockets by wireless communications, circuits are activated according to the timeslots purchased without interruption of low-power (e.g. lighting and phone-charging) circuits. Informed by site survey data, laboratory tests demonstrated the system to be reliable and effective in maintaining demand closer to supply availability while avoiding overloads. This reduces losses and the need for storage while increasing energy access and return on investment

Finding the Optimum Orientation for PV Systems Matched to the Timing of the Demand Profile

IEEE conference publicationElectricity consumption in the Kingdom of Saudi Arabia (KSA) has grown by about 7% annually in the last two decades due to population and economic growth. The consumption of the residential sector accounts for over 50% of the total energy generation largely due to the consumption of the buildings’ air conditioning. This factor contributes significantly to a situation where peak electricity demand occurs in early afternoon. Thus, this paper presents one of the possible ways of managing electricity peak demand by proposing deployment of PV panels with slope and orientation that are optimized with respect to the timing of the demand profile in order to contribute most effectively to national electricity generation capacity. As a case study, numerical results are presented for Riyadh city in KSA

Reducing High Energy Demand Associated with Air-Conditioning Needs in Saudi Arabia

open access articleElectricity consumption in the Kingdom of Saudi Arabia (KSA) has grown at an annual rate of about 7% as a result of population and economic growth. The consumption of the residential sector accounts for over 50% of the total energy generation. Moreover, the energy consumption of air-conditioning (AC) systems has become 70% of residential buildings’ total electricity consumption in the summer months, leading to a high peak electricity demand. This study investigates solutions that will tackle the problem of high energy demand associated with KSA’s air-conditioning needs in residential buildings. To reduce the AC energy consumption in the residential sector, we propose the use of smart control in the thermostat settings. Smart control can be utilized by (i) scheduling and advance control of the operation of AC systems and (ii) remotely setting the thermostats appropriately by the utilities. In this study, we model typical residential buildings and, crucially, occupancy behavior based on behavioral data obtained through a survey. The potential impacts in terms of achievable electricity savings of different AC operation modes for residential houses of Riyadh city are presented. The results from our computer simulations show that the solutions intended to reduce energy consumption effectively, particularly in the advance mode of operation, resulted in a 30% to 40% increase in total annual energy savings

Levelling of heating and vehicle demand in distribution networks using randomised device control

Rising demand from electrical heating and vehicles will drive major distribution network reinforcement costs unless 24-hour demand profiles can be levelled. We propose a demand response scheme in which the electricity supplier provides a signal to a “smart home” control unit that manages the consumer’s appliances using a novel approach for reconciliation of the consumer’s needs and desires with the incentives supplied by the signal. The control unit allocates demand randomly in timeslots that are acceptable to the consumer but with a probability biased in accordance with the signal provided by the supplier. This behaviour ensures that demand response is predictable and stable and allows demand to be shaped in a way that can satisfy distribution network constraints

Enhancing energy efficiency through smart control: paths and policies for deployment

Smart devices and controllers are often proposed as an effective way to both minimise and optimise the timing of energy consumption in order to minimise the peaks in demand. A key component of the Smart Grid vision is the widespread use of such devices, advanced as a way to mitigate the intermittency of renewable energy generation which in turn is crucial to the decarbonisation of electricity supply. In this paper, we focus on the use of smart controllers and the adoption of distributed renewable generation at household level as part of the transition from a conventional electricity grid to a Smart Grid. We utilise an Agent Based Model to investigate the effectiveness of both smart controllers and distributed generation in reducing household energy consumption, alone and in combination. We also investigate the possible paths to adoption of such devices and the interdependence of the case to adopt one on the other. Electricity consumption patterns for households in the model are heterogeneous and generated in accordance with data for the UK and initial adoption rates for distributed generation are calibrated from UK National data. We illustrate the potential for smart controllers to alter demand patterns over time both with and without distributed generation. We show the effect of order of adoption of devices at the householder level on the energy consumption of their building, but also on consumption at a larger scale and highlight issues for policy makers designing policies intended to incentivise a transition towards smart control of energy demand

Estimation of demand diversity and daily demand profile for off grid electrification in developing countries

Describes software downloadable from: https://github.com/peterboait/ESCoBox_Load_Model Open AccessThe potential for small self-contained grid systems to provide electricity for currently unserved regions of the developing world is widely recognised. However planning and managing the electrical demand that will be supported, so that a mini-grid system is not overloaded and its available resource is used as fully as possible, is actually more difficult than for a large scale grid system. This paper discusses the mathematical reasons why this is the case, and describes a practical software tool for mini-grid demand estimation and planning that is complementary to the widely used HOMER software. This software tool is made available for download on an open source basis. Finally a conclusion is offered that mini-grid systems should aim to serve at least 50 households so that demand variability is more manageable and economies of scale can be realised

Making Legacy Thermal Storage Heating fit for the Smart Grid

Collaborative paper with Oxford University Environmental Change Institute and Energy Local Ltd. The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Thermal storage heaters, charged using overnight off-peak electricity, have been used for domestic space heating in the UK and other countries since the 1980s. However, they have always been difficult for consumers to manage efficiently and, with the advent of a high proportion of renewables in the electricity generation mix, the time of day when they are charged needs to be more flexible. There is also a need to reduce peaks in the demand profile to allow distribution networks to support new sources of demand such as electric vehicles. We describe a trial of a smart control system that was retrofitted to a group of six dwellings with this form of heating, with the objectives of providing more convenient and efficient control for the users while varying the times at which charging is performed, to flatten the profile of demand and make use of locally-generated renewable electricity. The trial also employs a commercially-realistic combination of a static time-of-day tariff with a real time tariff dependent on local generation, to provide consumers with the opportunity and incentive to reduce their costs by varying times of use of appliances. Results from operation over the 2015-16 heating season indicate that the objectives are largely achieved. It is estimated that on an annualised and weather-adjusted basis most of the users have consumed less electricity than before intervention and their costs are less on the trial tariffs. Critical factors for success of this form of system are identified, particularly the need to facilitate hands-on control of heating by thrifty users and the importance of an effective and sustained user engagement programme when introducing the technology, to ensure users gain confidence through a readily-accessible source of support and advice

Managing complexity in the smart grid through a new approach to demand response

CASCADE was a consortium project with Cranfield UniversityAdoption of weather-dependent renewable generation of electricity has introduced additional complexity to the challenge of maintaining a dynamic equilibrium between generation and electricity demand. At the same time the need for electricity to power heating and transport in place of fossil fuels will lead to congestion in distribution networks. Part of the solution will be to manage domestic electricity demand using signals between the smart grid and smart home, but this must be done in a way that does not provoke further instability. We use an agent-based model of household electricity consumption and supply to show how the complexity of domestic demand can be shaped allowing it to make a contribution to system stability. A possible role for this method in balancing conflicting interests between electricity consumers, suppliers, and distribution network operators is discussedEPSRC under the CASCADE project (EP/GO59969/1