Abstract
Renewable-powered “undergrid mini-grids” (UMGs) are instrumental for electrification in developing countries. An UMG can be installed under a—possibly unreliable— main grid to improve the local reliability or the main grid may “arrive” and connect to a previously isolated mini-grid. Minimising costs is key to reducing risks associated with UMG development. This article presents a novel market-logic strategy for the optimal operation of UMGs that can incorporate multiple types of controllable loads, customer smart curtailment based on reliability requirements, storage management, and exports to and imports from a main grid, which is subject to failure. The formulation results in a mixed-integer linear programming model (MILP) and assumes accurate predictions of the following uncertain parameters: grid spot prices, outages of the main grid, solar availability and demand profiles. An AC hybrid solar-battery-diesel UMG configuration from Nigeria is used as a case example, and numerical simulations are presented. The load-following (LF) and cycle-charging (CC) strategies are compared with our predictive strategy and HOMER Pro’s Predictive dispatch. Results prove the generality and adequacy of the market-logic dispatch model and help assess the relevance of outages of the main grid and of spot prices above the other uncertain input factors. Comparison results show that the proposed market-logic operation approach performs better in terms of cost minimisation, higher renewable fraction and lower diesel use with respect to the conventional LF and CC operating strategies.
Highlights
This article has been motivated by the increasing blurring line separating on- and off-grid electricity supply in developing countries where adequate universal access to electricity has not been achieved
Redefining the Unit Commitment (UC) problem for mini-grids in a market-logic approach, as described above, involves three modifications compared to the formulation in a vertically integrated environment: (1) changing the objective function from cost minimisation to social welfare maximisation; (2) the demand to be served includes multiple types of customers with different reliability requirements and contracts; (3) adding slack variables to the power balance equation characterising the not-served energy (NSE) corresponding to the number of types of loads; (4) penalizing the cost of NSE in the objective function by previously stipulated price contracts
+ etDG + et where q A, q B are the number of customers—Type A and Type B; dtA, dtB are the load forecastings of customers—Type A and Type B at time t; etGridex is the electricity exported to BESSCharge the Main Grid at time t; et is the amount of battery charge at time interval t; ηCharge and ηrect are the efficiency parameter when charging the battery and the efficiency of the PV is the efficiency of PV Inverter and e PV is the electricity output rectifier, respectively; ηinv t
Summary
This article has been motivated by the increasing blurring line separating on- and off-grid electricity supply in developing countries where adequate universal access to electricity has not been achieved. Given that 840 million people still lack access to electricity [8], until recently, electrification programs included off-grid mini-grids as the least-costly technology to power rural remote areas. The most frequent situation arises as the “grid arrives”, i.e., when the distribution company, the “DisCo”, decides to extend the grid and connect to an existing mini-grid, which can be independently managed by exchanging power with the main grid under stipulated terms. The design and operation of UGMs substantially differ from those of isolated minigrids, as they have to consider the possibility of importing power from or exporting power to the main grid, which can be functional or blacked out. The algorithm provided has been formulated as a very general approach to evaluate UMG’s techno-economic and reliability indicators for different business models and regulatory schemes It considers various types of generation sources, different types of consumers, and storage and main grid as prosumers. The algorithm proposed here can be adapted to the circumstances of industrialised economies by taking out the assumption of an unreliable main grid service
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