Demand response within the energy-for-water-nexus - A review. ESRI WP637, October 2019

A promising tool to achieve more flexibility within power systems is demand re-sponse (DR). End-users in many strands of industry have been subject to research up to now regarding the opportunities for implementing DR programmes. One sector that has received little attention from the literature so far, is wastewater treatment. However, case studies indicate that the potential for wastewater treatment plants to provide DR services might be significant. This review presents and categorises recent modelling approaches for industrial demand response as well as for the wastewater treatment plant operation. Furthermore, the main sources of flexibility from wastewater treatment plants are presented: a potential for variable electricity use in aeration, the time-shifting operation of pumps, the exploitation of built-in redundan-cy in the system and flexibility in the sludge processing. Although case studies con-note the potential for DR from individual WWTPs, no study acknowledges the en-dogeneity of energy prices which arises from a large-scale utilisation of DR. There-fore, an integrated energy systems approach is required to quantify system and market effects effectively

Smart Grid Control: Demand Side Management in Household Refrigerators as a tool for Load Shifting

With improved supply of renewable sources of energy the focus has shifted away from simply producing clean energy to efficient consumption of energy. Until cheaper methods of energy storage are developed, Demand Side Management (DSM) is the best option for maximising energy efficiency. This paper proposes a method of turning regular refrigerators into smart demand response fridges. First, we develop an algorithm that accounts for small fluctuations in price and switches the device for optimal performance and lowered running cost. Then, we use longer price fluctuations to predict suitable times for pre-cooling and investigate the reduction in price as a result. Finally, the two models are compared, evaluated and improvements are proposed

Demand side management analysis of a supermarket integrated HVAC, refrigeration and water loop heat pump system

Supermarkets are intensive energy consumers because of a high electricity demand, mainly due to refrigeration utilities. Thus, in this work a supermarket integrated HVAC, refrigeration and water loop heat pump (WLHP) system was analyzed according to a demand side management approach, adopting a demand response strategy coupled with real-time pricing predictive rule based controls. The system was modeled with TRNSYS and several DR strategies were applied to both the space heating/cooling and the WLHP to determine the plant configuration with the most effective electricity cost saving. It was found that two setups guarantee the highest economic savings. The first consists of a predictive rule based control applied to the space heating/cooling only, which is basically inexpensive and allows an annual cost saving of 4.06% respect to the baseline configuration. The second, instead, combines predictive rule based controls applied to both the space heating/cooling and the WLHP auxiliary heater, and shows the best performance with the adoption of a 200\u202fm3 water-based thermal energy storage. Respect to the baseline, this configuration provides an annual cost saving of 4.67%

Residential Demand Response using Electricity Smart Meter Data

The electricity industry is currently undergoing changes in a transitioning period characterised by Energy 3D: Digitalisation, Decentralisation, and Decarbonisation. Smart meters are the vital infrastructure necessary to digitalise the energy system as well as enable advancements in decentralisation and decarbonisation. As of today, more than 500 million smart meters have been installed worldwide, with that number expected to rise to several billion installations over the decade. Smart meters enable electricity load to be measured with half-hourly granularity, providing an opportunity for demand-side management innovations that are likely to be advantageous for both utility companies and customers. Among these innovations, time-of- use (TOU) tariffs are widely considered to be the most promising solution for optimising energy consumption in the residential sector, however actual use is still limited. The objective of this thesis is to investigate opportunities and problems related to TOU tariffs utilising smart meter data at the national level. The authors have identified four major research gaps which need to be filled in order to expand commercial applications of TOU tariffs. These gaps are the described and addressed in the following chapters: the "TOU load adaptation forecasting problem", the "TOU winner detection problem", the "TOU public dataset problem", and the "excess generation forecasting problem". This thesis demonstrates three modelling approaches and one new TOU dataset (CAMSL). A significant contribution to the field is through the discover of new summary statistical features (statistical moments) and assesses the capacity of these to encapsulate other more widely used explanatory variables of demand response. The thesis is concluded by discussing future works and policy implications, such as the necessity of the more tailored modelling works and public live-stream of smart meter data, which could accelerate the roll-out of the demand side management at the residential sector.EPC

Demand-Response in Smart Buildings

This book represents the Special Issue of Energies, entitled “Demand-Response in Smart Buildings”, that was published in the section “Energy and Buildings”. This Special Issue is a collection of original scientific contributions and review papers that deal with smart buildings and communities. Demand response (DR) offers the capability to apply changes in the energy usage of consumers—from their normal consumption patterns—in response to changes in energy pricing over time. This leads to a lower energy demand during peak hours or during periods when an electricity grid’s reliability is put at risk. Therefore, demand response is a reduction in demand designed to reduce peak load or avoid system emergencies. Hence, demand response can be more cost-effective than adding generation capabilities to meet the peak and/or occasional demand spikes. The underlying objective of DR is to actively engage customers in modifying their consumption in response to pricing signals. Demand response is expected to increase energy market efficiency and the security of supply, which will ultimately benefit customers by way of options for managing their electricity costs leading to reduced environmental impact

Energy storage in the UK electrical network : estimation of the scale and review of technology options

This paper aims to clarify the difference between stores of energy in the form of non-rechargeable stores of energy such as fossil-fuels, and the storage of electricity by devices that are rechargeable. The existing scale of these two distinct types of storage is considered in the UK context, followed by a review of rechargeable technology options. The storage is found to be overwhelmingly contained within the fossil-fuel stores of conventional generators, but their scale is thought to be determined by the risks associated with long supply chains and price variability. The paper also aims to add to the debate regarding the need to have more flexible supply and demand available within the UK electrical network in order to balance the expected increase of wind derived generation. We conclude that the decarbonisation challenge facing the UK electricity sector should be seen not only as a supply and demand challenge but also as a storage challenge. (c) 2010 Elsevier Ltd. All rights reserved