Considerations for Demand Response Programs in the Middle East and Africa
Definition
A Demand Response (DR) program is a set of organized activities to induce customers to modify, temporarily, the time pattern of energy use in response to signals from the System Operators (SO). Essentially, the SO aims to shift the peakiest hours to and are under the load curve that’s ideally in a trough shape.
Figure 1, shows the typical peak load shape in a fast-growing country in the Middle East and Africa (MEA) region. In some countries, the annual growth in peak demand is a consistent 7% per annum. The effect of this is continuous demand for peak capacity investments and an increasingly peaky system as incomes per capita improve over time. A corollary of this, is higher investment requirements and higher system costs resulting in either higher tariffs to end consumers or spiraling subsidies.
Figure 1: Typical load profile in a MEA country
The SO compensates customers for reducing their electricity use when:
Power shortages;
- Grid reliability is threatened; or
- High power price periods (in a market) occur.
- DR programs are widely used, particularly in the USA as shown in Figure 2 for the last two consecutive years.
Figure 2: Size of DR programs in US jurisdictions
Objectives
The key objectives of a DR program may include the reduction of environmental impacts from electricity use and construction of new infrastructure; reduce electricity costs; and optimize generation. The methods and approaches to realizing these objectives and prospering from the benefits include:
- Avoid cost of building new power plants to meet the peak demand;
- Align customer electricity prices and the value of electricity to improve resource-efficiency;
- Reduce average cost of generation (fuel saving, efficiency, neglect inefficient plant dispatch);
- Defer new capacity construction (i.e. flatten demand curve); and
- Defer new transmission and distribution investment.
Figure 3 shows a schematic of how DR works practically.
Figure 3: DR Operational Procedure
Quantifying Benefits
One of the great challenges is to ensure the benefits of DR programs are quantified properly. A standard approach is to use the proxy of a peaking plant such as an open cycle gas turbine, its fuel and operating costs and associated network investments that conceptually could be avoided with shifting a target amount of demand from the peak period.
However, this could grossly underestimate the full system benefits, which may include a reliability component and other aspects of infrastructure and integration. Therefore, we recommend that a DR program is analyzed based on an optimized system plan and associated average cost which considers scenarios of with and without DR. This would provide a full comparison of average system costs under two scenarios and encompass all the system wide benefits. Knowing the system costs and benefits like this then enables the SO to appropriately price and incentivize DR resources to be available to the system on a voluntary basis.
The Role of Aggregators and Storage
Traditionally, one envisages DR programs as a range of multi-lateral contracts in a power market between the SO and customers who switch their demand behavior when asked to do so. However, there is also the role of the Aggregator in some markets. This is shown in Figure 4.
Figure 4: The Role of the Aggregator
In general, the sources of DR at the end use level are the following:
- Industrial level, when large manufacturing plants have the flexibility to adjust production processes to electricity prices;
- Commercial level, typically through automated solutions to manage air conditioning or lighting systems;
- Residential level, with smart appliances linked to automated solutions to minimize the impact of DR on daily life, motivated through commercial offers – which are usually proposed by aggregators to reach the critical number of consumers needed to make DR impactful in the wider electricity system.
Large battery storage systems are an obvious tool in this DR toolbox, able to be kept charged until needed, and able to come online immediately to smooth out changes in demand. Energy Northwest has some installations for example, 500 kW each, and the efficiency of these batteries are now up to 85%. The plan is for dozens to hundreds of these mobile lithium-ion battery energy storage systems to be spread out across the region, all acting in concert, along with the demand response customers.
Energy storage is also being deployed in other areas for DR purposes not least that costs are falling to US$ 200/kW. San Diego Gas & Electric has recently signed contracts to add 4.5MW DR program that prompts consumers to shift their energy consumption at times of high electricity prices. This prevents congestion, brownouts and facilities generation from green intermittent sources of energy.
DNV Assist with Integration
A key role DNV plays is having the experience, foresight and tools to model existing systems and project the direction of technology evolution in an integrated way. Integrated system models take into consideration future performance and price paths and stress tested configurations. For example, as part of the system modelling we can also model the impact of electric vehicle deployment and how they could be valued and integrated into the grid facilitating further DR services and enabling stability for increased renewable penetration. Part of the solution is ‘big data’ and handling these data in real-time in a way to optimize the system and apply the appropriate values to the relevant services.
Therefore, to realize the true benefit for DR resources we recommend a technology integrated solution (incorporating technology maturity and price paths) which views renewable energy penetration, energy storage and DR programs as part of an integrated whole. As well as looking at project specific economics, DNV takes an integrated approach to system level modelling and capturing the integrated benefits that both energy storage technologies and renewables can bring in shifting the peak system demand helping to reduce costs, optimize efficiency and safeguard the environment.