Adequacy of Renewable Energy Mixes with Concentrated Solar Power and Photovoltaic in Morocco: Impact of Thermal Storage and Cost

Abstract

In this paper, we analyze the sensitivity of the optimal mixes to cost and variability associated with solar technologies and examine the role of Thermal Energy Storage (TES) combined to Concentrated Solar Power (CSP) together with time-space complementarity in reducing the adequacy risk—imposed by variable Renewable Energies (RE)—on the Moroccan electricity system. To do that, we model the optimal recommissioning of RE mixes including Photovoltaic (PV), wind energy and CSP without or with increasing levels of TES. Our objective is to maximize the RE production at a given cost, but also to limit the variance of the RE production stemming from meteorological fluctuations. This mean-variance analysis is a bi-objective optimization problem that is implemented in the Emathsizesmall4CLIMmathsizesmall modeling platform—which allows us to use climate data to simulate hourly Capacity Factors (CFs) and demand profiles adjusted to observations. We adapt this software to Morocco and its four electrical zones for the year 2018, add new CSP and TES simulation modules, perform some load reduction diagnostics, and account for the different rental costs of the three RE technologies by adding a maximum-cost constraint. We find that the risk decreases with the addition of TES to CSP, the more so as storage is increased keeping the mean capacity factor fixed. On the other hand, due to the higher cost of CSP compared to PV and wind, the maximum-cost constraint prevents the increase of the RE penetration without reducing the share of CSP compared to PV and wind and letting the risk increase in return. Thus, if small level of risk and higher penetrations are targeted, investment must be increased to install more CSP with TES. We also show that regional diversification is key to reduce the risk and that technological diversification is relevant when installing both PV and CSP without storage, but less so as the surplus of energy available for TES is increased and the CSP profiles flatten. Finally, we find that, thanks to TES, CSP is more suited than PV and wind to meet peak loads. This can be measured by the capacity credit, but not by the variance-based risk, suggesting that the latter is only a crude representation of the adequacy risk.

Wind and Solar Intermittency and the Associated Integration Challenges: A Comprehensive Review Including the Status in the Belgian Power System

“…Finally, a good correlation between wind power and demand, which is not always the case, can raise the capacity credit by about 20%. The authors of [62] investigated capacity credit of PV and wind in the Moroccon power system at the penetration levels of 16%, 20% and 27%. In all three cases, the mentioned penetration levels consist of 21.8% of PV and 78.1% wind.…”

A Minimal System Cost Minimization Model for Variable Renewable Energy Integration: Application to France and Comparison to Mean-Variance Analysis

“…Table 2 summarizes the design of some mean-variance analysis problems applied to the VRE systems [19,[21][22][23][24]. The formulation of the mean-variance problems in these studies differ from the costminization problem (Equation ( 4)) and its version ignoring curtailment (Equation ( 25)) in several aspects:…”

“…Recently, Tantet et al [23] apply mean-variance analysis to the study of the optimal recommissioning of VRE capacities in Italy using time series of both load and VRE CFs estimated from climate data. Bouramdane et al [24] and Maimó-Far et al [25] follow a similar approach to compare two different solar technologies in Morocco depending on the weight put on variability, and to analyze the role of the predictability of the photovoltaic (PV) production in Spain, respectively.…”

“…• VRE rental costs are not included in the objective functions, but the (fractional) total capacity or rental cost is instead constrained. Apart from Beltran [19], who use generation costs in the mean and variance terms, and Bouramdane et al [24], who use a total rental cost constraint, no economic costs appear in most meanvariance problems.…”

Utility-Scale PV-Battery versus CSP-Thermal Storage in Morocco: Storage and Cost Effect under Penetration Scenarios

“…A key question moving forward is how to compare interaction between PV-BES and CSP-TES in a particular prospective power generation mix based on renewable energies (REs). While both technologies collect solar radiation and produce electricity, they do so through different mean production, costs and variability [51], which creates challenges for direct comparison. associated storage (BES, TES) needs a multi-objectives optimization problem that considers the whole range of feasible solutions by determining trade-offs between mean production, cost and variability.…”