Stochastic optimisation-based valuation of smart grid options under firm DG contracts

Abstract

Abstract-Under the current EU legislation, Distribution Network Operators (DNOs) are expected to provide firm connections to new DG, whose penetration is set to increase worldwide creating the need for significant investments to enhance network capacity. However, the uncertainty around the magnitude, location and timing of future DG capacity renders planners unable to accurately determine in advance where network violations may occur. Hence, conventional network reinforcements run the risk of asset stranding, leading to increased integration costs. A novel stochastic planning model is proposed that includes generalized formulations for investment in conventional and smart grid assets such as Demand-Side Response (DSR), Coordinated Voltage Control (CVC) and Soft Open Point (SOP) allowing the quantification of their option value. We also show that deterministic planning approaches may underestimate or completely ignore smart technologies. Power drawn by SOP at terminal (pu) Index Terms-Firm DG contracts, Option Value of smart technologies, Planning under uncertainty, Real Options I. NOMENCLATURE Sets and indices

Option Value of Demand-Side Response Schemes Under Decision-Dependent Uncertainty

“…. and respective capacities as follows: 380kW (lines [1][2], [2][3], [3][4][5]), 200kW (lines [5][6], [6][7], [7][8]) and 80kW (all remaining lines). In the initial state (first epoch) the demand is satisfied through energy imports via the substation (bus 1), while the DG unit connected to bus 11 has not yet become operational.…”

“…4 respectively where 10% and 50% represent consumer participation levels (see Table III). Note that the notation such as [1][2][3][4][5]:100 denotes 100kW line upgrades across all lines between buses 1 and 5, while DSR(x) signifies DSR deployment at bus x. Percentages, when shown, refer to customer participation levels.…”

“…In this new landscape, where flexibility becomes a central issue, smart grid technologies can constitute valuable alternatives to the conventional route of capitalintensive reinforcements [2]. Technologies such as energy storage, demand-side response (DSR) and flow control devices can offer benefits such as improved ancillary service provision [3], improved DG hosting capability [4] and interim management of long-term planning uncertainty [5]. The deployment of these technologies is seen as an integral part of planning a low-carbon energy system at least cost.…”

Stochastic integration of demand response and reconfiguration in distribution network expansion planning

“…The installed power of DGs at each substation has to respect (14) and (15), which are similar to (11). The DGs margin given by (16) is computed assuming that the minimal consumption on each substation is 20% of the peak consumption (hypothesis used by the French DSOs)…”

“…Alvarez-Herault [14] takes into consideration uncertainties on generation only and does not model the times series behaviour of loads and generation. Konstantelos et al [15,16] deal with uncertainties in DG using multi-stage scenario trees combined with optimisation methods. The number of scenarios is limited, which supposes a quite good knowledge of the future.…”