The effect of Demand Response and wind generation on electricity investment and operation

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte.Abstract: We present a novel method of determining the contribution of load-shifting Demand Response (DR) to energy and reserve markets. We model DR in an Mixed Complementarity Problem (MCP) framework with high levels of wind penetration. Investment, exit and operational decisions are optimised simultaneously. We examine the potential for DR to participate in both energy and reserve markets. DR participation in the energy market reduces costs and prices but the impact of DR participation in reserve markets is limited. DR and wind generation are strongly complementary, due to the ability of DR to mitigate against the variability of wind generation, with the highest impacts of DR seen at high levels of wind penetration. DR participation in the energy market gives rise to lower equilibrium levels of investment in conventional generation and induces a Pareto improvement versus a market with no DR participation. The total impact of DR is highly dependent on specific system characteristics.Abstract-We present a novel method of determining the contribution of load-shifting Demand Response (DR) to energy and reserve markets. We model DR in an Mixed Complementarity Problem (MCP) framework with high levels of wind penetration. Investment, exit and operational decisions are optimised simultaneously. We examine the potential for DR to participate in both energy and reserve markets. DR participation in the energy market reduces costs and prices but the impact of DR participation in reserve markets is limited. DR and wind generation are strongly complementary, due to the ability of DR to mitigate against the variability of wind generation, with the highest impacts of DR seen at high levels of wind penetration. DR participation in the energy market gives rise to lower equilibrium levels of investment in conventional generation and induces a Pareto improvement versus a market with no DR participation. The total impact of DR is highly dependent on specific system characteristics.

Risk aversion in flexible electricity markets

“…Studies have examined storage investment (e.g. Fernández-Blanco et al 2017;Boffino et al 2019), investment in the presence of demand response (Devine et al 2019) investment in power plant flexibility (Garðarsdóttir et al 2018), marketparticipating residential microgeneration (Calvillo et al 2016), as well as other demand-side flexibility options (Moreno et al 2017).…”

The role of power-to-gas in the future energy system: Market and portfolio effects

“…Based on EirGrid (2016), the assumed total annual electricity demand of 33.6 TWh and peak demand is 5655 MW. In terms of the quantity target for the capacity market, this is calculated as 1.2 times the system peak demand similar to Devine et al (2019) 00:00 01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00…”

“…Clastres and Khalfallah (2015) examine from an economic perspective how the price-responsiveness of consumers can be optimally harnessed to achieve the flexibility necessary to reduce costs while meeting demand, while Broberg and Persson (2016) perform choice experiments to determine the extent to which consumers are willing to accept external control of their electricity usage (via smart devices). Finally, De Jonghe et al (2012) provide one of the earlier studies on the impact of variable supply and flexible demand on the entire electricity generation portfolio, from a least cost perspective, while Devine et al (2019) and Lynch et al (2019) perform analyses of the potential for flexible demand aggregators to participate in energy and capacity markets, respectively. Specific technology investments are often proposed in order to accommodate this increased variability in electricity supply and power system optimisation tools are commonly used throughout the literature to determine the optimal depoloyment of same.…”

Probabilistic integrated framework for AC / DC transmission congestion management considering system expansion, demand response, and renewable energy sources and load uncertainties

“…In the literature, there are two general categories of demand response methods: incentive-based DRPs and timebased DRPs. 35 This paper focuses on the incentive-based DRPs, namely emergency DRPs (EDRPs) and direct load control (DLC) during the congested hour. The linear model of the responsive load is employed in this paper, which is given in Equation (2) 36 :…”