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Investigating the impact of demand flexibility on electricity retailers

I. MOTIVATION AND PREVIOUS WORK
Flexible demand technologies, enabling redistribution of electricity demand in time, have the potential to significantly improve the cost-effectiveness of low-carbon power systems by limiting demand peaks and increasing the use of renewable and cheaper generation sources. However, in the deregulated electricity market setting emerged during the last decades, the realization of this demand flexibility potential will also have significant implications on different market participants, an aspect which has not yet been thoroughly investigated.
In this setting, most electricity consumers are represented in the wholesale market by an electricity retailer or supplier. The latter buys energy from the wholesale market and resells it to the served consumers based on certain retail electricity tariffs. The objective of this competitive market entity lies in maximizing its individual profit by optimizing the offered tariffs to the consumers while respecting regulatory constraints and maintaining a balance between the energy bought from the wholesale market and the energy sold to the consumers.
By deploying demand flexibility, electricity consumers can modify their demand patterns according to the offered retail tariffs so as to maximize their utility. This effect will in turn impact the retailer’s decisions regarding the offered tariffs. A few recent papers have modeled this dynamic interaction between the retailer and the served consumers. However, all of them exhibit a fundamental shortcoming: the impact of the offered retail tariffs and the resulting demand response on the wholesale market is neglected. As a result, the wholesale market price is treated as an exogenous parameter. This assumption does not reflect the reality, as in most markets a relatively small number of retailers serve the whole population of consumers. Therefore, each retailer serves a relatively large number of consumers, implying that its tariff strategy and the resulting demand response will have a significant impact on the wholesale market prices and consequently on the retailer’s profit. As a result, the modeling approaches employed in these papers fail to fully capture the impact of demand flexibility on the retailer’s strategies and profit.

II. PAPER CONTRIBUTIONS AND APPROACH
This paper drops this assumption and proposes a modeling framework capturing the interactions between the offered retail tariffs, the consumers’ flexibility and the wholesale market prices in an integrated fashion. In order to achieve this, the strategic decision making of a retailer is modeled through a novel multi-period bi-level optimization problem. The upper level (UL) problem determines the optimal hourly-specific retail prices offered to the consumers and the hourly-specific bids submitted to the wholesale market so as to maximize its profit over the considered daily horizon.
This UL problem is subject to regulatory constraints (namely the maximum and average retail price cannot surpass certain levels) as well as two lower level (LL) problems. The first one represents the decision making of the consumers which determine their optimal demand response given the retail prices so as to maximize their total utility. Their demand flexibility is modeled through the ability to reduce / increase their hourly demand within certain limits, as long as energy neutrality is preserved within the daily market horizon. The second LL problem represents the wholesale market clearing process, maximizing the social welfare given the bids submitted by the examined retailer but also the bids and offers of other retailers and producers respectively. This bi-level problem is solved after converting it to a Mathematical Program with Equilibrium Constraints (MPEC), and linearizing the latter through suitable techniques.
Preliminary results from case studies with the developed model indicate that increasing demand flexibility a) reduces the retailer’s revenue since consumers can respond more effectively to strategic retail pricing patterns, but also b) reduces the retailer’s cost in the wholesale market as it flattens the overall system demand profile, leading to a lower average price over the considered daily horizon. Nevertheless, a higher demand flexibility is found to reduce the retailer’s net profit, since its effect on the retailer’s revenue is higher than its effect on the retailer’s cost. Finally, we expect that these trends will also depend on the relative size of the retailer in the wholesale market, for which reason a relevant sensitivity analysis will be carried out. More detailed analysis and discussion of the results will be provided in the full paper.

Author(s):

Dawei Qiu    
Imperial College London
United Kingdom

Yujian Ye    
Imperial College London
United Kingdom

Dimitrios Papadaskalopoulos    
Imperial College London
United Kingdom

Goran Strbac    
Imperial College London
United Kingdom

 

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