Empirical analysis of convergence and sensitivity of demand response based on real time pricing

Lokhande, Smita; Bichpuriya, Yogesh

doi:10.1109/isgt.2017.8085972

Cited by 4 publications

(2 citation statements)

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“…Next, we prove equations ( 27) and ( 28) hold. Due to similarity, here we only provide the proof of (27). We know [λ * k ] j is the shadow price associated with the j th general linear constraint in optimization problem (De-I).…”

Section: Property 53mentioning

confidence: 99%

“…Most of them focus on the flexibility or price-responsiveness of a certain type of appliances [23], [24], [25]. Some of them study the DR resources' capacity value based on simulations or empirical analysis [26], [27]. However, to the best of our knowledge, there is no related studies providing a general tool quantifying or estimating different prosumers' potential impact on social welfare under a dynamic pricing environment, which is the problem the paper provides solutions to.…”

Section: Introductionmentioning

confidence: 99%

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A General Sensitivity Analysis Approach for Demand Response Optimizations

Xiang

Wei

2018

Preprint

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It is well-known that demand response can improve the system efficiency as well as lower consumers' (prosumers') electricity bills. However, it is not clear how we can either qualitatively identify the prosumer with the most impact potential or quantitatively estimate each prosumer's contribution to the total social welfare improvement when additional resource capacity/flexibility is introduced to the system with demand response, such as allowing net-selling behavior. In this work, we build upon existing literature on the electricity market, which consists of price-taking prosumers each with various appliances, an electric utility company and a social welfare optimizing distribution system operator, to design a general sensitivity analysis approach (GSAA) that can estimate the potential of each consumer's contribution to the social welfare when given more resource capacity. GSAA is based on existence of an efficient competitive equilibrium, which we establish in the paper. When prosumers' utility functions are quadratic, GSAA can give closed forms characterization on social welfare improvement based on duality analysis. Furthermore, we extend GSAA to a general convex settings, i.e., utility functions with strong convexity and Lipschitz continuous gradient. Even without knowing the specific forms the utility functions, we can derive upper and lower bounds of the social welfare improvement potential of each prosumer, when extra resource is introduced. For both settings, several applications and numerical examples are provided: including extending AC comfort zone, ability of EV to discharge and net selling. The estimation results show that GSAA can be used to decide how to allocate potentially limited market resources in the most impactful way.

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Section: Property 53mentioning

confidence: 99%