Exposing residential consumers to real-time pricing (RTP) can yield significant efficiency gains, but may also pose challenges due to the inherent complexity. Using an extensive spectrum of temporal granularities for retail electricity pricing, we analyze to what extent these capture the benefits of RTP while concurrently considering the influence of three distribution tariff types in distorting the pricing signal. Via a mixed complementarity model, we consider both operational and investment decisions at retail as well as wholesale levels, accounting for their interdependencies. Our analysis reveals three key findings. Firstly, we find that decreasing temporal granularity of retail electricity prices increases total system cost due to an increasingly inefficient generation mix, however, three-hourly or six-hourly pricing can approximate RTP benefits. Secondly, decreasing temporal granularity of retail electricity prices raises average offtake and lowers average injection prices for consumers due to changes in wholesale market prices as well as consumption patterns of consumers. Thirdly, capacity-based tariffs reduce system offtake peaks and associated price increases by incentivizing battery discharge during peak consumption while volumetric tariffs, over-incentivizing solar PV investments, result in highest offtake prices and injection peaks.

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This study delves into the interplay of residential electricity customers in low voltage distribution systems (LVDS) with market designs that manage local grid constraints. Within this context, residential electricity customers are self-interested agents, exposed to real-time pricing, that can invest in distributed energy resources (DER) and participate in wholesale energy as well as ancillary service market. The study specifically evaluates the trade-off between market design complexity and economic efficiency by examining market designs that employ Static Limits (SLs), Dynamic Operating Envelopes (DOEs), and Distribution Locational Marginal Pricing (DLMP) to ensure network integrity. Using a long-run equilibrium problem the study comprises both operational and investment perspective, considering feedbacks between distribution and higher voltage levels. The analysis reveals three key insights. Firstly, simpler market designs, namely SL-based and DOE-based designs, can approximate the economic efficiency of DLMP-based design, contingent on the network's characteristics. Effective in networks comprised of shorter feeders and larger consumers, the efficacy of simpler designs in approximating DLMP-based design diminishes in networks comprising longer feeders and numerous small consumers. Secondly, consumer preferences play a crucial role in DOE-based design, with consumers having a high willingness-to-pay (WTP) for grid capacity influencing economic efficiency. Thirdly, despite differences in distribution, energy, and DER investment costs, for the majority of consumers, total costs remain comparable across the three designs.

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Assessing the capability of a distribution grid to accommodate new solar PV installations, namely its hosting capacity (HC), has been a prevalent research topic. Although providing a technical limit to how much additional solar PV can be integrated into a distribution grid without trespassing operational limits, commonly used HC analysis (HCA) does not consider consumer preferences or the economic feasibility of installations. Using a market-based optimal power flow (MBOPF) and HCA, we compare the economic and technical limits of solar PV capacity integration in low voltage distribution systems (LVDS). Findings illustrate that (1) the PV HC computed using grid limits only does not give a complete picture of solar PV capacity integration potential, (2) linear, deterministic power flow is not a foolproof method for assessing the network-secure amount of PV, and (3) the number of technically feasible installation sites supersedes the economically feasible ones. @en