Showing papers by "Pierluigi Mancarella published in 2014"

A Short-term Load Forecasting Model for Demand Response Applications

Abstract: This paper discusses a new algorithm and defines the functionality required for developing a short-term load-forecasting module for demand response applications. Feedforward artificial neural network (ANN) algorithms are used to provide high forecasting performance when dealing with nonlinear and multivariate problems involving large datasets. The approach is thus suitable for short-term load prediction for disaggregated sites to optimize the demand response process when the data relating to the operating regime or load characteristics of the individual devices and loads connected are unavailable. A detailed description of the relevant external data needed for the forecast is explained. In particular, the algorithm considers weather data for the corresponding time period. The model is tested on data from actual ground source heat pump (GSHP) and heating, ventilation and air conditioning (HVAC) loads of various non-residential buildings at several real sites in the United Kingdom (U.K.). The sensitivity of the parameters of the algorithm, including the number of hidden layers used, is also researched. The proposed algorithm is tested against a linear regression and proves to outperform the latter in all cases. The performance of the algorithm is quantitatively assessed using mean absolute per cent error and mean absolute error metrics. Further analysis plots a comparison of actual and forecasted loads and R-values to determine forecast accuracy.

Probabilistic Modeling and Simulation of Transmission Line Temperatures under Fluctuating Power Flows

Abstract: Increasing shares of fluctuating renewable energy sources induce higher and higher power flow variability at the transmission level. The question arises as to what extent existing networks can absorb additional fluctuating power injection without exceeding thermal limits. At the same time, the resulting power flow characteristics call for revisiting classical approaches to line temperature prediction. This paper presents a probabilistic modeling and simulation methodology for estimating the occurrence of critical line temperatures in the presence of fluctuating power flows. Cumbersome integration of the dynamic thermal equations at each Monte Carlo simulation trial is sped up by a specific algorithm that makes use of a variance reduction technique adapted from the telecommunications field. The substantial reduction in computational time allows estimations closer to real time, relevant to short-term operational assessments. A case study performed on a single line model provides fundamental insights into the probability of hitting critical line temperatures under given power flow fluctuations. A transmission system application shows how the proposed method can be used for a fast yet accurate operational assessment.

Distribution network reinforcement planning considering demand response support

Abstract: Recently, Electricity North West Limited (ENWL), one of the UK Distribution Network Operators (DNOs) has proposed a Demand Side Response (DSR) based scheme for reducing social costs (e.g., power losses), increasing distribution network capacity, and postponing (or even avoiding) future network reinforcements in the presence of uncertainty. This solution, named "Capacity to Customers" (C 2 C), consists of pushing the network limits beyond traditional planning standards that apply under contingency situation by resorting to temporary customer disconnection after a fault occurs. The assessment of the C 2 C solution (and other network solutions) should be consistent with the cost benefit analysis (CBA) model proposed by Ofgem (the UK regulator). However, this CBA model (i) is deterministic, which is not adequate for evaluating the impacts of the C 2 C solution on network reinforcements under uncertainty and (ii) is based on two potentially conflicting objectives that either fully acknowledge or disregard social costs. In this light, this work proposes an extension of Ofgem's CBA model based on scenarios, optimizations, and the opportunity loss (regret) criterion to assess the effects of uncertainty and tradeoffs between investment and social costs. The proposed CBA model relies on a new simulation based approach to optimize network reinforcement plans (including the C 2 C solution) while considering risk management (i.e., via the regret criterion). The proposed approach is illustrated on a real UK distribution network where the C 2 C is currently being deployed. The results show that the implementation of the C 2 C solution can lead to substantial cost reductions, particularly for social costs.

Reliability Evaluation of Demand Response to Increase Distribution Network Utilisation

Abstract: In response to distribution network challenges such as increasing demand, infrastructure ageing and integration of distributed generation, alternative approaches are being sought to release existing network capacity, before proceeding to new investments. Considering that most distribution networks in the UK are typically designed as a ring but operated radially, this paper discusses the effect of a loop operation aimed at maximizing the capacity utilisation of the existing asset. In this context, demand response schemes are implemented as a corrective action following a contingency with the aim of maintaining the system within its limits. Sequential Monte Carlo Simulations (SMCS) are used to quantify the reliability performance under different scenarios, also considering the influence of Information and Communications Technology (ICT) and automatic control schemes. Simulation studies have been performed on real UK distribution networks, showing the impact of different types of operation. The results indicate that a radial operation with automated interconnection with other circuits could result in comparable performance indicators and capacity increase as a ring operation.

Integrated electrical and gas network modelling for assessment of different power-and-heat options

Abstract: A new model has been developed for the simulation of operational interdependences between the natural gas and electrical networks, with the specific purpose of being used to study the effects of different future heating (and therefore power) scenarios on the two networks. The model has been applied to Great Britain's electrical and gas transmission systems. Numerical case studies have been run to illustrate the potential impacts of changing the domestic heating paradigm, from gas boilers to electric heat pumps and/or combined heat-and-power facilities, on the electrical and gas transmission networks. In particular, the preliminary results, which also describe future gas and electricity supply and demand implications, provide specific insights into and challenges of the operation of the gas network under significant changes in technologies for heat production.

Modelling of household electro-thermal technologies for demand response applications

Abstract: With increasing penetration of renewable and low carbon energy resources and electrification of energy consumption, Demand Response (DR) is expected to play a more important role in system balancing, network capacity support, and wholesale electricity markets. However, the side effects of DR control could cause various issues that could eventually hinder its deployment. Therefore the impact of DR needs to be properly understood and modelled. A potentially significant source of DR may be found in control of electro-thermal technologies (ETT, i.e. electric heat pump and micro combined heat and power units) installed in the domestic sector, which could help to alleviate low voltage network congestion. In this respect, this paper introduces a detailed physical model which is used to simulate, with high resolution, the load shapes of different ETT in different buildings with different thermal inertia characteristics. Simulation studies are carried out to evaluate the changes in load patterns in the different cases and the impact of possible DR control strategies, also taking into account the thermal comfort level of occupants. The high resolution model developed aims at giving insights on the expected load pattern changes when applying different DR control schemes to different ETT and in different types of houses.

Economic assessment of distribution network reinforcement deferral through post-contingency demand response

Abstract: This paper presents a methodology for the economic assessment of smarter solutions used for distribution network reinforcement planning; specifically, the methodology was developed to assess the economic value from deploying network reconfiguration and automation, and post-contingency Demand Side Response (DSR) as recommended by the Capacity to Customers (C 2 C) method, which is currently being tested in the UK at medium voltage levels (i.e., 11kV and 6.6kV). The C 2 C method combines the aforementioned smart solutions to increase distribution network capacity (limited by security considerations) and bring about several social benefits at the distribution level (e.g., reduced power losses and increased reliability); thus deferring or even averting costly network and substation reinforcements. The proposed methodology relies on scenarios, optimisations and a Cost Benefit Analysis (CBA) framework to assess the C 2 C method compared with traditional reinforcement practices. The approach is illustrated using a real UK distribution network where the C 2 C method is currently being tested, and general conclusions from other such networks are also discussed. The results highlight the conditions that encourage the deployment of C 2 C interventions as an alternative to or in combination with traditional reinforcements.

Techno-economic assessment of flexible combined heat and power plant with Carbon Capture and Storage

Abstract: As Carbon Capture and Storage (CCS) is now regarded as on its way to become a mature technology to reduce dramatically CO 2 emissions from conventional generation, its economic ineffectiveness may still be preventing its large-scale adoption. In this respect, new strategies for flexible operation of Carbon Capture and Storage systems could bring substantial benefits allowing achieving both ambitious CO 2 reductions and higher profits. In addition, further economic and environmental benefits could be achieved by adopting high efficiency Combined Heat and Power (CHP) plants. On these premises, this paper investigates the benefits of coupling a flexible CCS system and a flexible CHP plant, with the aim of deploying the flexibility available in both CCS and CHP to consume/produce more or less electricity in response to market conditions. A mathematical model is developed to maximise profit responding to volatile market prices by optimally switching the CCS and CHP plants between different operating modes. The effectiveness and the usefulness of the proposed model are demonstrated on a realistic case study with extensive sensitivity analyses.

Generation adequacy in wind rich power systems: Comparison of analytical and simulation approaches

Abstract: The analytical and simulation approaches used for generation adequacy assessment are reviewed in this paper in the context of large-scale wind penetration. The analytical approach applied by the UK system regulator and sequential Monte Carlo simulation (MCS) are compared based on a realistic model of the UK power system. It is found that the analytical approach yields a higher risk of security of supply compared to sequential MCS approach. This is due to the fact that the analytical approach fails to take into account the inherently chronological nature of wind power. A further contribution of this paper is the estimate of the duration and severity of single capacity shortfall provided via sequential MCS. This is essential to future networks in which alternative resources (mainly demand response and storage) can be deployed as proxies for capacity. Moreover, high impact and low probability events are captured properly through sequential MCS. A key conclusion of this paper is that sequential MCS should be applied to estimate generation adequacy as it provides more realistic results of the various indicators.

Modelling and assessment of the techno-economic and environmental performance of flexible Multi-Generation systems

Abstract: This paper presents a unified techno-economic and environmental mathematical model for market driven operation optimization of different Distributed Multi-Generation (DMG) options in district heating schemes. The identified concepts of DMG are capable of providing significant operational benefits in that they have the flexibility to respond to electricity market signals, which is particularly important in the presence of a less flexible and more intermittency dominated power system. At the same time, the formulation allows assessment of the environmental benefits under different scenarios. The optimization formulation cast as a mixed integer linear program (MILP), is capable to incorporate the use of different multi-energy technologies and explicitly model inter-temporal constraints that allow assessment of the benefits of thermal storage, amongst the others.

Evaluation of reliability performance of distribution networks implementing demand response schemes

Abstract: Demand Response (DR) is likely to become key to power system operation and planning in the future. In this outlook, the successful deployment of any DR scheme will be facilitated by the integration of Information and Communication Technologies (ICT), enabling Distribution System Operators (DSOs) to actively manage their networks. Various DR applications have been proposed, mostly relevant to energy markets, while few studies are yet available on DR as a means to contribute to network capacity and on the relevant reliability implications. In this work, DR is proposed as a post fault contingency action to provide capacity release in distribution networks. The reliability performance of the proposed scheme is assessed through Sequential Monte Carlo Simulations (SMCS) taking into account both electrical and ICT failures. Customer Interruptions (CI) and Customers Minutes Lost (CML) are evaluated in addition to the classical load point reliability indices. DR customers are disconnected according to a priority list with the aim of not breaching network constraints after a fault occurs. As case studies, two different DR control strategies are introduced and compared based on their reliability performance for different DR availability levels.