To improve the efficiency of its hydro power system and prepare for the emerging energy market in southern Africa, Swaziland Electricity Board asked RMD Consult to devise an optimisation study for its hydro power cascade

THE development of an open energy market in southern Africa is in full swing. Liberalisation, privatisation, unbundling or energy trading are no longer abstract notions but daily facts of life for operating companies. Over the past few years, southern African countries have been getting accustomed to this developing situation.

The Kingdom of Swaziland is situated in southern Africa, southwest of Mozambique. With a surface area of 17,365km2 and a population of approximately 1.1M, it is one of the smallest countries in Africa. The Swaziland Electricity Board (SEB) is a member of the Southern African Power Pool (SAPP) and operates a hydro power cascade consisting of two storage reservoirs, two buffer ponds and three hydro power stations with a total capacity of 41MW. This does not include some mini hydro and diesel stations.

In this new, emerging energy market and with increasing annual energy demands, Swaziland is only capable of producing about 30% of domestic energy demand with its existing hydro power plants. The other 70% has to be purchased and regulated in a power purchase agreement. In this agreement, energy purchase costs are fixed for peak, standard and off-peak periods, where peak period costs are relatively high compared to standard and off-peak periods. Monthly energy demands in the last few years have ranged between 55-80GWh. The highest demands are in July and August when the natural availability of water is at its lowest.

To improve the efficiency of the hydro system and prepare for the new conditions in the developing open energy market of the southern African region, SEB engaged RMD Consult at the beginning of 2001 to devise an optimisation study for its hydro power cascade.

SEB hydro power cascade

Lake Luphohlo is the head reservoir of the hydraulic system. With its annual storage capacity (see table below), the Luphohlo reservoir can be operated to compensate for annual fluctuations between dry and wet periods. Mkinkomo reservoir has a weekly buffer, while the two head ponds only have hourly buffer


In order to optimise the reservoir operation throughout the year, the hydrological regime has to be investigated. For this purpose, after a plausibility check, discharge data from the past 40 years were analysed and categorised in a statistical wet, mean and dry year. The hydrological regime is characterised by a distinct summer rain peak and a dry winter period as shown in the figure below. The analysis of the discharge data indicates that neither the beginning of the rain period, which generally occurs in October, nor the intensity of this is very reliable. In some years the start of the rain period was shifted to December. In other years there was not a rain period at all.

Optimising water management

One major goal of this study is the development of an operation system which manages reservoir outflows and water levels throughout the year while optimising energy production and reducing energy purchase costs.

The annual water management optimisation is performed using WAMOPT, an Excel-based model developed by RMD Consult. WAMOPT allows changes to any given variable and the optimised solution is found using an iterative approach. The model regulates daily outflows and water levels at Luphohlo and Mkinkomo reservoirs for the given reservoir inflows of statistically dry, mean and wet years. In this procedure Lake Luphohlo is used as a head reservoir to compensate the inner-annual discharge fluctuations between dry winter and wet summer months. This allows the generation of energy even in dry season, focusing on times when energy purchase costs are the highest (during peak periods). Finally spillage at the smaller Mkinkomo reservoir will be minimised. The following frame conditions and limits had to be considered when using the iterative approach in WAMOPT:

• Hydrological regime (dry, mean and wet year).

• Energy demand (sufficient water should be available when energy demand is high).

• Power purchase agreement (depending on water availability, water release should focus on peak first, then standard and lastly on off-peak periods).

• Maximum and minimum reservoir water levels.

• In mid-April, water level at Luphohlo reservoir must be at its maximum.

• Maximum discharges of penstocks, river and canal reaches.

• Flow times in river and canal reaches.

Such limitations and conditions are reflected in the statistically optimised water level curve (operation curve) for Lake Luphohlo. Furthermore, WAMOPT showed that the operating water level should not fall below the lower limit reflected in the minimum curve.

Daily forecast model

According to the power purchase agreement, SEB has to order firm energy one day in advance. Therefore another approach had to be developed, allowing a daily forecast of the expected production of electrical energy. On the basis of the optimisation scheme found with WAMOPT, (eg the operation curve of Luphohlo reservoir) the daily operation forecast model (DOM) has been developed by RMD Consult using visual basic for application (VBA). A general sketch of DOM is shown in the figure below.

With the user-friendly DOM, the operator is able to quickly and reliably forecast the available water amounts and energy production for each power station for the next day. Inputs into DOM are:

• Two reservoir water levels.

• Three discharge readings.

• Maintenance outage of hydro stations.

• The current date.

The program automatically distributes and assigns the available water to the hours of the day when it is most valuable – considering peak, standard and off-peak tariff times. Reports for each power station can be printed and the development of discharges and water levels can be evaluated in various graphs.

The modular structured DOM can be adjusted to changes expected in an altering southern African electricity market.

Future tasks

Using statistically analysed, long term discharge records, WAMOPT was used to optimise water management and energy production. Based on the results obtained with WAMOPT, the forecast model DOM will be a powerful tool for SEB to operate its hydro power system successfully on a daily basis.

There is still an important amount of unused water potential available in the region. Research by Bowen and Frederick suggests that there is an economically feasible hydro power potential of 20-30,000MW in southern Africa.

To reach competitive overall production costs, the owners and operating organisations of power stations and grids are forced to hold the field in the open market. In many cases this can often only be done with either personnel reduction or the increase of energy production.

An important number of smaller hydro power stations could be realised in Swaziland. Small environmental impacts, small construction expenditures and relatively low investment costs favour the construction of mini and micro hydro plants. However, new small hydro power plants will not be suitable to lower production costs for larger energy producers; therefore, additional power plants of a larger size are sometimes the only possibility.

Consequently, future investigations may also include exploitation of hydro power potential for larger stations. Assessing environmental impacts and effects on irrigation, the Kingdom of Swaziland could profit from its favourable topography along major rivers such as the Komati, Lusutfu, Lusushwana and Mbuluzi.


Data on the SEB hydro power cascade