Abstract
Significant changes in the power generation mix are posing new challenges for the balancing systems of the grid. Many of these challenges are in the secondary electricity grid regulation services and could be met through demand response (DR) services. We explore the opportunities for a water distribution system (WDS) to provide balancing services with demand response through pump scheduling and evaluate the associated benefits. Using a benchmark network and demand response mechanisms available in the UK, these benefits are assessed in terms of reduced green house gas (GHG) emissions from the grid due to the displacement of more polluting power sources and additional revenues for water utilities. The optimal pump scheduling problem is formulated as a mixed-integer optimisation problem and solved using a branch and bound algorithm. This new formulation finds the optimal level of power capacity to commit to the provision of demand response for a range of reserve energy provision and frequency response schemes offered in the UK. For the first time we show that DR from WDS can offer financial benefits to WDS operators while providing response energy to the grid with less greenhouse gas emissions than competing reserve energy technologies. Using a Monte Carlo simulation based on data from 2014, we demonstrate that the cost of providing the storage energy is less than the financial compensation available for the equivalent energy supply. The GHG emissions from the demand response provision from a WDS are also shown to be smaller than those of contemporary competing technologies such as open cycle gas turbines. The demand response services considered vary in their response time and duration as well as commitment requirements. The financial viability of a demand response service committed continuously is shown to be strongly dependent on the utilisation of the pumps and the electricity tariffs used by water utilities. Through the analysis of range of water demand scenarios and financial incentives using real market data, we demonstrate how a WDS can participate in a demand response scheme and generate financial gains and environmental benefits.
Highlights
Electricity storage schemes and grid management methods are becoming ever more important as the landscape of the electricity⇑ Corresponding author.grid changes to more decentralised renewable production
We investigate three aspects of demand response from water distribution system (WDS), how optimal pump operations change to enable the provision of demand response before and during a DR event, requirements needed for the provision of DR through pump scheduling to be financially viable and the environmental aspects of DR from WDS and how it compares to other alternative response energy provision technologies
Through the use of a global optimisation technique we compared the operating schedules of a WDS system minimising the operating cost alone and minimising the operating cost while participating in different demand response schemes in the UK. Through this analysis we show that for a wide range of electricity tariffs and water demands there exist demand response mechanisms which allow the WDS to provide demand response and reduce its cost and provide response energy at low greenhouse gas (GHG) emissions
Summary
This paper shows for the first time how a WDS can provide reserve energy through demand response by optimising the pump schedules.We quantify the environmental benefits of demand response compared to alternative reserve energy systems as well as the financial profits that can be generated for the water network operator. We validate our findings through simulation of the optimal operation of the WDS using real data from National Grid in a Monte Carlo simulation Using this data, we show the potential application as an additional revenue stream that is new to water distribution companies, which could simultaneously provide the grid with more demand side response potential at low GHG emissions and competitive cost. This investigation focusses on the system hurdles using quasi steady state modelling and simplified operating constraints; we assume the operational hurdles can be met with available control and monitoring technologies and design expertise
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